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Luke Hollis

Luke Hollis

GitHub LinkedIn lhollis@g.harvard.edu lhollis@mit.edu

I'm a researcher in simulation and computational robotics. I'm interested in world model development and simulation environments for embodied AGI. I create simulation environments for the Harvard Computational Robotics Group and the CityScience SF Lab at the MIT Media Lab.

My last startup created XR software used by tens of thousands of schools and every top 100 university worldwide. My 3D captures have been featured in major documentaries, films, and international media.

Outside of my research, I co-founded a non-profit for 3d capture and practice western-style boxing.

EXPERIENCE

2025-
Researcher, Massachusetts Institute of Technology
Media Lab, City Science SF, World Models, Simulation, Causal Inference
2023–2024
Applied AI Engineer and Advisor, Startups
Machine Learning, Product Development, Technical Strategy
2020–2022
Lead 3d Research Engineer, Harvard University
3D Reconstruction, XR, Agent-based Modeling, Computer Vision
2019–2020
Visiting Researcher, Massachusetts Institute of Technology
Geospatial analyses, Computational Design, Human-Computer Interaction
2014–2019
Founder, Researcher, Archimedes Digital
Spatial Computing, 3D Reconstruction, Machine Learning

EDUCATION

2025-2027
Harvard University, Masters of Data Science
Harvard Kennedy School, Intelligence Project, QLab Cohort 3.0
2025
Stanford University, Graduate Coursework
Data Science and Artificial Intelligence, Applied Math
Research
MIT Media Lab, Harvard Computational Robotics, Harvard Visual Computing

ADVISORY POSITIONS

2025
Apple, iPhone Camera Team, 3d Capture
2024
IBM Almaden Research Center, Spatial Intelligence
2018-2019
Google, Artificial Intelligence (NLP) Admin, Summer of Code

OPEN SOURCE

Luke Hollis' GitHub Contribution Graph
SplatGraph
Convert any 3d capture into a segmented scene graph with physics properties
Part of real2sim pipeline using 3dgs, LangSplat, and GaussGym. Python, Nvidia IsaacSim
3
three-mlagents
Three.js + Torch implementation of Unity's ML-Agents framework for agent training and visualization in browser
Agent training and visualization in browser. Python, Three.js
26
1
llm-urban-simulations
Create multi-agent simulations in game engines for realistic human behaviors and synthetic training data
Realistic human behaviors and synthetic training data. C#
29
3
genie-bottle
Pytorch implementation of "Genie: Generative Interactive Environments", Bruce et al. (2024).
Bruce et al. (2024). Python, PyTorch
4
2
More projects →

SELECTED PRESS

Reuters Reuters Wired Wired Reddit Reddit Hacker News Hacker News BBC BBC CNN CNN National Geographic National Geographic The Guardian The Guardian Smithsonian Smithsonian PBS PBS Google Google OpenAI OpenAI Harvard Gazette Harvard Gazette The Harvard Crimson The Harvard Crimson University of Chicago University of Chicago Lonely Planet Lonely Planet Matterport Matterport Polycam Polycam Replicate Replicate LiveScience LiveScience Sharp Sharp Nerdist Nerdist Mental Floss Mental Floss Washington Post Washington Post Boston Globe Boston Globe My Modern Met My Modern Met

PUBLICATIONS

[Working Title] Predictive Real2Sim Digital Twins: A World Model Approach to Deformable Mesh and Soft-Body Simulation Physics

[Working Title] Predictive Real2Sim Digital Twins: A World Model Approach to Deformable Mesh and Soft-Body Simulation Physics

2026

Applying world model architectures to predictive physics simulation for deformable objects.

Heng Yang, Luke Hollis
Harvard Computational Robotics Group
In Progress
World Models Physics Simulation Digital Twins
[Working Title] Scaling Language-Grounded Splatting to Large Urban Spaces

[Working Title] Scaling Language-Grounded Splatting to Large Urban Spaces

2026

Novel approach to scale language-grounded 3D gaussian splatting techniques for large-scale urban environments.

Yasushi Sakai, Luke Hollis
MIT Media Lab & Harvard University
In Progress
3D Gaussian Splatting Computer Vision Urban Computing

Urban Planning and Design with 3D Street Captures and 360 Video

2025

Methodology for integrating immersive 3D captures into urban planning workflows.

Peter Hirshberg, Kate Connally, Lee Crawford, Luke Hollis
MIT Media Lab
Forthcoming
Urban Planning 360 Video 3D Capture
See all publications →

AWARDS AND HONORS

2026
E14 and MIT Media Lab, Beyond the Lab, IAP Cohort
2025
Sequoia Capital, Start-up Trek, selected founders from Harvard and MIT
AGI House, World Models Hackathon, 1st Place Winner
Replicate, Digital Twins Hackathon, 1st Place Winner
E14, Artificial Intelligence at MIT Summit, Mountain View
2024
Matterport Digital Twin Award, Top 10 Most Viewed Space of Year
National USS Hornet Hackathon, 1st Place Winner
AGI House, Simulations Hackathon, 1st Place Winner
2023
Matterport Digital Twin Award, Honorable Mention
2020
Graduate Research Fellowship, Massachusetts Institute of Technology

PRESENTATIONS AND INVITED TALKS

2025
Autonomy and Robotics, Ethics and Engineering Guest Lecture, Massachusetts Institute of Technology.
Techniques and Development in Remote Sensing, Lecture, Harvard University.
3d Capture at Stanford Campus, Part 2 of 2. Apple. Stanford University.
Language-Conditioned Simulation with Reinforcement Learning: Synthesizing Decision-Grade Digital Twins for Complex Physical Systems. Università Cattolica del Sacro Cuore
3d Capture at Stanford Campus, Part 1 or 2. Apple. Stanford University.
2024
Generative Interactive Environments: World Models and Learning from GDM Genie. Google
2023
Synthesizing Multiple Data Imports for 3d Captures of Large Architectural Features. Università degli Studi di Pavia
Techniques and Methodologies in 3d capture and 3d Gaussian Splatting. Old Dominion University.
2022
Digitization and 3d Simulations for Large Exterior Architectural Spaces. Columbia University