Luis Kaiser

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PhD Student at The University of Texas at Austin

Research Area

I am broadly interested in robotics, generative modeling and applied mathematics.
My long-term goals are to i) design novel reinforcement learning algorithms that use general purpose foundation models (language, vision or multimodal), and ii) ground deep learning in mathematical principles through partial differential equations.

Positions

2022–Present The University of Texas at Austin Austin, TX
PhD AI Research Scientist, Oden Institute (Advisor: Richard Tsai)
2023–2024 Bloomberg London, UK and New York, US
Software Engineer, AI modeling and forecasting systems
2021 University of Wuerzburg Wuerzburg, Germany
Research Scientist Intern, RL research at Data Science Lab (Advisor: Andreas Hotho)
2020 Cosmo Consult (formerly max-con data science) Wuerzburg, Germany
Data Science Intern, agentic systems research for an acquired startup
2020 KPMG Munich, Germany
Data Science Intern, statistical risk prediction and stochastic long-term pricing

Education

Exp. 2027 Ph.D. in Computational Mathematics and AI, The University of Texas at Austin Austin, TX

• Advised by Richard Tsai (Scientific ML Group, Oden Institute)

2023 M.Sc. in Mathematics and Computer Science, University of Wuerzburg Wuerzburg, Germany

• Advised by Richard Tsai and Christian Klingenberg.
• The University of Texas at Austin - Exchange Program in Computer Science
• Thesis: “Fast, Accurate, and Scalable Numerical Algorithms: Enhancement by Deep Learning”.

2021 B.Sc. in Mathematics and Computer Science,
Technical University of Munich (TUM) and University of Wuerzburg Munich, Germany

• Advised by Andreas Hotho, Julian Tritscher, and Padraig Davidson.
• Norwegian School of Economics - Exchange Program in Data Science
• Thesis: “Evaluation and Improvement of Deep Reinforcement Learning Agents”.

Publications

Conference

C1
Efficient Numerical Wave Propagation Enhanced By An End-to-End Deep Learning Model
Luis Kaiser, Richard Tsai, Christian Klingenberg. ENUMATH23, Springer Nature, 2024.
Paper Code arXiv Bibtex

Thesis

T1
Evaluation and Improvement of Deep Reinforcement Learning Agents
Luis Kaiser, Julian Tritscher, Padraig Davidson, Andreas Hotho. Bachelor Thesis at University of Wuerzburg, 2021.
Paper Code

Talks

Playing Games using Monte Carlo Tree Search Grounded by Partial Differential Equations

The University of Texas, Center for Autonomy

Deep Reinforcement Learning and Monte Carlo Tree Search in Game Theory

University of Wuerzburg, Department of Mathematics

Fast, Accurate, and Scalable Numerical Algorithms: Enhancement by Deep Learning

Texas Advanced Computing Center (TACC) - AI Consortium

Learning a Differentiable World Model of Wave Dynamics for Fast, Scalable Forecasting

University of Wuerzburg, Department of Mathematics

Deep Learning for Wave Propagation - Neural Operators and Surrogate Models

University of Wuerzburg, Department of Mathematics

Teaching

Fall 2025 Computational Systems Senior Design The University of Texas at Austin

Co-led student engineering teams with Raghav Mahalingam.
Capstone industry projects included:

• Spacecraft prototype modeling (Southwest Research Institute)

• Drone-based monitoring system (Clarke Lab)

• Estimation system for a satellite in orbit (Aegis Aerospace)

Fall 2019 Algorithms and Data Structures University of Wuerzburg

Designed and co-taught CS curriculum lead by Andreas Hotho

Awards

2021–2022 University of Texas at Austin Graduate Scholarship

Merit-based tuition waiver for graduate studies in Computer Science.

2022 UT A-League Men’s Soccer Champion in Spring 2022

Team captain in top-division league.

2021 UT Austin Autonomous Multi-Agent Neural Networks Price

RL Computer Vision Competition - 2v2 SuperTuxKart Ice Hockey [details].

2017–Present E-fellows Scholarship

Based on academic achievements and leadership for German high potentials.