Mauricio Tec#

I am a research associate at Harvard University working on decision-making AI. In particular, my work focuses on reinforcement learning and deep learning methodology, often in combination with statistical modeling and causality tools. I’m also very interested in robotics and social impact applications for climate change adaptation and health.

I am taking interns and co-advising research projects. My current topics of interest include foundation models and LLMs for reinforcement learning and planning and novel deep learning architectures for graph and topological domains motivated by geospatial and computer vision data. If you are interested in working with me, please reach out.

About Me. I completed my Ph.D. in Statistics at UT Austin, where I worked on reinforcement learning and computer vision for applications in spatial domains. During that time, I held internships at Meta AI (FAIR) and Intel AI and was a member of the UT Covid-19 Modeling Consortium and the UT Austin Villa Robot Soccer Team where I worked on vision systems for autonomous robots. Before my Ph.D., I completed a B.S. in Applied Mathematics at ITAM and an M.S. in Mathematics at the University of Cambridge.

robot-detective

News#

  • [2024-02-01] 🔨 Our workshop Training Agents with Foundation Models in the Reinforcement Learning Conference (RLC) 2024 is to be held on August 9th, 2024. We will release the website and call for papers soon! Reach out to tafm.rlc@gmail.com.

  • [2024-02-01] 🔥 New manuscript: Optimizing Heat Alert Issuance for Public Health in the United States with Reinforcement Learning. My first paper as senior author.

  • [2024-01-16] 🔥 New paper: SpaCE paper has been accepted to ICLR 2024. See you in Vienna!

  • [2024-01-15] 🤖 Created a LIVE CV, powered by retrieval augmented generation. Have fun asking your own questions about my research and work experience.

  • [2023-12-10] Started this new website based on Chris Holdgraf’s new blog template.

  • [2023-09-01] Promoted to Research Associate at Harvard University. I will continue my research as usual but take on more projects in a senior role and propose grant applications.

  • [2023-05-15] New grant as Co-PI awarded by the Harvard Chan-NIEHS to develop new computer vision architectures that are robust for prediction under covariate shift (with applications to projecting climate change’s health impacts).

  • [2023-03-01] New ArXiV paper Causal Estimation of Exposure Shifts with Neural networks.

  • [2022-08-15] Started a postdoc at Harvard University, Department of Biostatistics.

CV#

Try my 🤖 Live CV Chatbot here, powered by LLMs and RAG. Have fun asking your own questions. You can also download an outdated pdf ⬇ here. Last updated: 2024-01-16.

My Family#

family