Tesla Wells

Software Engineer @ comp.coop

About

I develop worker-centric automation software for worker's cooperatives, unions, and non profits. I have previously written autonomy and planning software for robots, Operations Research projects, and space satellites. At MIT, I completed a masters thesis in the field of Human Computer Interaction (HCI) out of CSAIL. Specifically, I focused on improving schedule generation for human + robot teams with the use of expressive utility functions. I have also used my research background to advise on AI-related technical strategy and produce science-communication writing, algorithm tutorials, and course lectures. You can read my technical explainer series for the startup Mobi.AI here: https://www.mobi.ai/resources/category/technical-explainersI have some resume gaps during a period in which I was competing as a semi-pro fencer! I have fenced internationally for team USA and I trained with a club in Milan during the 2024 and 2025 seasons :)

Country

United States

City

New York

Industry

Computer Software

Skill

Data Science, Process Automation, Software Industry, Co-ops, Technology Consulting, Linear Programming, Feedback Control Systems, Constraint Programming, Algorithms, Cascading Style Sheets (CSS), Robotics, Gurobi, Operations Research, Software, c++, AngularJS, Autonomous Vehicles, Real-Time Operating Systems (RTOS), Embedded Systems, Systems Engineering

Experience

Software Engineer

comp.coop

2026-2 - Present · 8 mos

New York City Metropolitan Area

Technical Writer

Mobi.AI

2023-8 - 2025-6 · 1 yr 11 mos

Cambridge, Massachusetts, United States

I am writing and developing strategy/guidelines about AI and data for both internal (research white papers, technical documentation, and product-strategy documents) and external publication (technical explainers here: https://www.mobi.ai/resources/category/technical-explainers )

Algorithm Engineer

Mobi.AI

2023-1 - 2023-8 · 8 mos

Somerville, Massachusetts, United States

I use classical AI concepts to generate schedules for robotics, transportation, and mixed-initiative teams. I modeled and integrated human preferences into scheduling recommendation systems using techniques that optimize for explainability. I also coded utility functions and heuristics to improve planner outputs.