Nathan Tsao

Applied Machine Learning Engineer with experience in generative AI, reinforcement learning, and scalable machine learning. Seeking full-time ML Engineer positions.


Please download my for the most updated version (08/17/2025).

Skills

Deep LearningGenerative AIPythonPyTorchRoboticsJAXRayLinuxDockerStable-Baselines3GitDart

Relevant Coursework

Reinforcement LearningStatistical Machine LearningTheoretical StatisticsConvex Optimization

Education

Master of Science

August 2023 - May 2025

University of Texas at Austin

Austin, TX

GPA: 3.74.
Thesis: Neural Port-Hamiltonian Differential Algebraic Equations
Major: Mechanical Engineering (ML-focused)

Bachelor of Science

August 2019 - May 2022

University of Illinois Urbana-Champaign

Urbana, IL

GPA: 3.87
Major: Mechanical Engineering

Work Experience

Autonomous Aircraft Operations Research Intern

June 2025 - August 2025

NASA Ames Research Center

Mountain View, CA

Researching how reinforcement learning driven traffic following behavior among autonomous aircraft in dense airspaces improves travel time and safety.

Hardware Engineering Intern

June 2022 - September 2022

Berkeley Lights

Berkeley, CA

Automated data-acquisition and calibration pipeline in Python.
Designed hardware and software integration for custom temperature calibration sensors.

Research Experience

Graduate Research Assistant

December 2023 - May 2025

University of Texas at Austin: Autonomous Systems Group

Austin, TX

Designed compositional machine learning frameworks for differential-algebraic systems, enabling scalable modeling of electrical networks.
Developed a low-power, low-latency human activity recognition model optimized for batteryless sensors, resulting in 15-50% relative improvement over baselines.

Publications:

  • Cyrus Neary*, Nathan Tsao*, and Ufuk Topcu. Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks. Accepted to CDC 2025.
  • Geffen Cooper*, Nathan Tsao*, Filippos Fotiadis, Ufuk Topcu, Radu Marculescu. Learning from Sparse and Asynchronous Data Streams for Batteryless Sensors. Under review at NeurIPS 2025.

Visiting Research Assistant

May 2022 - January 2023

University of California, Berkeley: Hybrid Robotics Group

Berkeley, CA

Implemented a reinforcement learning-based locomotion balancing controller for tailed quadruped robots.
Integrated hardware with custom actuators and motor controllers for robust RL deployment.

Undergraduate Research Assistant

January 2022 - May 2022

University of Illinois Urbana-Champaign: RoboDesign Lab

Urbana, IL

Prototyped a low-cost force-sensing humanoid robot foot using elastomers and Hall sensors.
Applied Gaussian processes to estimate force signals in humanoid robot feet.

Honors and Awards

Dr. J. Parker Lamb Endowed Presidential Fellowship

2023

University of Texas at Austin

Nominated by the Walker Department of Mechanical Engineering.

Highest Honors

2022

University of Illinois Urbana-Champaign

Awarded to students with at least a 3.8 Illinois GPA and continual commitment to service and education.

Dean's List

2019-2022

University of Illinois Urbana-Champaign

Awarded to undergraduate students in the top 20 percent of their college class.

Teaching Experience

ASE 370C Feedback Control Systems

January 2025 - May 2025

University of Texas at Austin

Austin, TX

Graduate Teaching Assistant

ME 314D Dynamics

September 2023 - December 2023

University of Texas at Austin

Austin, TX

Graduate Teaching Assistant