Ted TroxellTECHNOLOGY. PEOPLE. POSSIBILITY.

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

CLEVELAND, OHIO · WORKING AT THE EDGE OF AI

Complex problems.
Clear direction.

I’m Ted Troxell. Engineer, founder and technical leader. I turn complex technical problems into clear direction—and help people build what comes next.

Explore my work
Let’s build something

CURRENTLY AT ATOMIC INDUSTRIES
PREVIOUSLY DIRECTOR OF DATA SCIENCE AT CAPTIV8

Ted Troxell

TECHNICAL DEPTH.
HUMAN PERSPECTIVE.

ENGINEER → FOUNDER → TECHNICAL LEADER

Technical depth. Clear decisions. People moving together.

01 / FIND THE SIGNALScroll to connect the dots ↓

The first move is a better question.

02 / EXPERIENCE & PERSPECTIVE

The context changes.
The questions get better.

What matters here? Where should we focus? How will we know it works? Engineering, company leadership and community building give me different ways to approach those questions.

Open a chapter. Explore the thinking.

01 / Technical practice

AI in the physical world

Defense technology. Welding intelligence. Machine learning for manufacturing.

Explore the thinking
Perspective
The through line connects engineering and product work at Think-A-Move, welding data at Lincoln Electric, and machine learning for manufacturing at Atomic Industries.
Career timeline
02 / Founder & technical leader

Different seats. A wider perspective.

Founder, CTO and Director of Data Science roles built a wider view of technical leadership.

Explore the thinking
Perspective
Company leadership at liftr, technical leadership at LiftCamp, and data science leadership at Captiv8 each brought a different kind of responsibility.
Leadership roles
03 / Community leadership

A community for curiosity.

Making AI more accessible by bringing people into the conversation.

Explore the thinking
Perspective
As President & CEO of CLE AI & DATA, I help create space for people to learn, share ideas and connect around AI and data.
Community work

03 / HOW I LEAD

Direction is a
team practice.

Technical depth helps me understand the choices. Leadership means making those choices clear enough for others to act.

DEFINE THE FIT. MAKE THE WORK LEGIBLE.Drafted by your scroll ↓

01

Purpose. Choose what matters.

Start with the change we need to make, the people it serves, and the constraints that matter. A clear purpose gives a team something useful to decide against.

What would change this priority?

A useful priority has a reason and a boundary. I want to name the constraint or new evidence that would make us reconsider it.

02

People. Make ownership clear.

Connect the people closest to the problem. Make responsibilities, dependencies and decisions visible so expertise can turn into coordinated work.

Where does a decision get stuck?

Look at the handoff: who has the context, who owns the decision, and who needs to understand the tradeoff?

03

Systems. Build for the next person.

A good solution has to be understandable and repeatable. I look for the documentation, interfaces and working habits that help a team carry it forward.

Could someone else carry this forward?

Understanding should survive a handoff. Clear interfaces and written reasoning reduce reliance on any one person.

04

Feedback. Let reality answer.

Make assumptions testable. Observe what happens, invite challenge and use what we learn to change direction when the evidence calls for it.

What evidence would change our minds?

Define the observation before defending the solution. A small test can be more useful than another confident opinion.

03.2 / FROM INTENT TO DELIVERY

Make the sequence visible.

Agree on the problem. Align the people. Build in increments. Leave room to learn.

Define the problem → align ownership → build and test → review and adapt. Phases overlap as learning informs the work.

Swipe the drawing to inspect the full sequence ↔

04 / STAY CLOSE TO REALITY

A strong idea can
take a challenge.

My approach is to make an assumption, test it, and stay open to what the evidence says. Try that loop here: change the system, observe its motion, and see what the model can explain.

EXPERIMENT 001A pendulum, explained
Pendulum experiment, drawn as a mechanical test sheetA hatched support holds a pivot and hanging weight. A centerline and length dimension show the reference geometry. Changing length changes how quickly the weight swings. DYNAMIC SYSTEM / TEST RIG 01FRONT ELEVATION LVARIABLE θ ROTATION AXISMOVING MASS OBSERVE → MODEL → TEST → REVISESCHEMATIC / NTSREV. B

Give the system a nudge. Look for the pattern.

FROM OBSERVATION TO UNDERSTANDING

Find the simplest explanation.

Collect motion, then fit a small equation. A higher threshold drops weaker terms. Simpler is useful—until it stops explaining what you see.

THE MODEL

acceleration ≈ −9.81 × sin(angle)

Gravity pulls the weight toward its resting position. A longer pendulum swings more slowly. Enable JavaScript to try the experiment.

An educational illustration. Not a model of a client’s system or results.

05 / EXTEND THE CIRCLE

Better things happen
when people connect.

Technology moves forward when more people can take part. As President & CEO of CLE AI & DATA, I help build a community around that belief.

01 Learn together

Make room for questions at every level. An accessible conversation gives more people a way into AI and data.

02 Share what you know

Bring a useful idea, a hard lesson or a different perspective. Knowledge becomes more useful when others can build on it.

03 Connect across disciplines

Introduce people who see different parts of a problem. New possibilities often begin with that conversation.

A place for the curious, the experienced and the just-getting-started. Rooted in Cleveland. Open to possibility.

Meet CLE AI & DATA

DIFFERENT PARTS. A SHARED PURPOSE.Assembled by your scroll ↓

CURIOSITY IS BETTER SHARED.

06 / THE THROUGH LINE

A builder’s curiosity.
A leader’s perspective.

Engineering detail. A founder’s responsibility. Functional leadership. Each role adds another way to understand the work—and the people doing it.

2021 — PRESENT

Member of Technical Staff

Atomic Industries

Machine learning meets manufacturing.

2021

Director of Data Science

Captiv8

Functional leadership in data science.

2020 — 2021

Chief Technology Officer

LiftCamp Inc.

Technical leadership in a startup context.

2018 — 2020

Chief Executive Officer

liftr

The founder’s view of building a company.

2017 — 2018

Data Scientist

Lincoln Electric

Understanding welding through data.

2013 — 2017

Engineer & Product Manager

Think-A-Move

AI technology for the U.S. Department of Defense.

07 / IDEAS WORTH SHARING

Making the complex
more approachable.

WRITING

Notes from the technical side.

Exploring the ideas behind modern machine learning—from physical systems to the structure of data.

Selected links open the original published articles.

SPEAKING

A conversation, not a wall of jargon.

Physical AI. Technical leadership. Building an AI community. I’m interested in conversations that connect big ideas to the people doing the work.

Invite me to speak

Download headshot ↓

Short speaker bio

Ted Troxell is an engineer, founder and technical leader based in Cleveland, Ohio. A Member of Technical Staff at Atomic Industries and former Director of Data Science at Captiv8, his career spans machine learning, manufacturing and startup leadership. He is also President & CEO of CLE AI & DATA.

08 / WHAT’S NEXT

What needs
clear direction?

A leadership opportunity, an ambitious technical problem, or an idea for the community. I’d like to hear what you have in mind.

ted@tedtroxell.com ↗

CLEVELAND, OHIO · OPEN TO THE CONVERSATION

LET’S TALK

Good work starts
with a conversation.

A challenge, an opportunity, or an idea. Tell me what you have in mind.

Prefer email? ted@tedtroxell.com