Control and Learning for Autonomous Robotics Group

Cade Armstrong is a third-year undergraduate student at The University of Texas at Austin. He is studying Aerospace Engineering with a minor in Computer Science. Cade’s main areas of interest include Orbital Mechanics, Optimization, Dynamics and Modeling, Control Systems, Computational Methods, and Game Theory. After his undergrad, Cade plans to pursue a master’s degree in Aerospace Engineering as well.

Brett Barkley is a Computer Science PhD student at the University of Texas at Austin co-advised by David Fridovich-Keil and Amy Zhang. Brett’s research interest focuses on methods that promote waste minimization in the lifecycle of deep reinforcement learning algorithms, specifically the 3 Rs: reduce, reuse, recycle.

Before enrolling at UT, Brett was an employee of the Johns Hopkins Applied Physics Laboratory where he was the sub and full-scale aircraft red team autonomy lead for DARPA ACE. Brett holds a BS and MS in Aerospace Engineering from the University of Maryland and a BS in Engineering Physics from Elon University. Outside of research, Brett enjoys being a hobbyist in brazilian jiu jitsu, playing video games with friends, and eating entirely too much H-E-B queso.

I am Kushagra, a Ph.D. student in the Department of Electrical and Computer Engineering at UT Austin since 2023, and my research interests lie at the intersection of control, learning and games for robotics. Prior to starting graduate studies, I earned my B. Tech. in Mechanical Engineering from the Indian Institute of Technology Delhi in 2023. I am co-advised by Dr. Ufuk Topcu, Dr. David Fridovich-Keil and Dr. Sandeep Chinchali.

Antonio Lopez is a Fulbright scholar from Mexico pursuing a Master’s degree at University of Texas at Austin. His interests include exploring the use of optimal control, control theroy and machine learning on autonomous systems, robot safety and spacecraft applications. Antonio completed his BS in Mechatronics at National Autonomous University of Mexico (UNAM) where he worked in two nanosatellite projects called K’OTO and KuauhtliSat. In his free time, Antonio enjoys playing chess, hiking and visit museums.

Jaehan Im is a first year PhD student in the Department of Aerospace Engineering co-advised by Ufuk Topcu and David Fridovich-Keil. He earned his BS and MS in the Aerospace Engineering Department from KAIST in South Korea. Im's research interests include decentralized control over multi-agent systems and a safety-critical human-autonomy interaction.

Hamzah Khan is a Master’s and Ph.D. student at the University of Texas at Austin in the Aerospace Engineering department and is advised by Professor David Fridovich-Keil. His interests span distributed control and planning, game theory, interpretability in learned systems, robot safety, and autonomous vehicles. He worked for three years in the self-driving vehicle industry at Uber ATG and subsequently, Aurora Innovation. Hamzah completed his undergraduate degree at Harvey Mudd College in Southern California (Class of 2018).

Dong Ho Lee is a PhD student at the University of Texas at Austin. Dong Ho’s research interests lie at the intersection between optimization, control theory and learning for autonomous multi-agent systems.

Prior to UT Austin, Dong Ho served as a First Lieutenant (Research Officer) in the ROK army for 3 years in Daejeon, South Korea. He received his B.S. and M.S. in Aerospace Engineering at the Korea Advanced Institute of Science and Technology (KAIST).

Jacob Levy is a Master’s and PhD student at the University of Texas at Austin. Jake is interested in advancing techniques in control theory and autonomy for unmanned spacecraft applications.

Prior to enrolling at UT Austin, Jake worked for 10 years at Parker Aerospace in Fort Worth, TX. His previous roles include Engineering Test Lab Manager and Test Engineer. Jake completed his B.S. in Aerospace Engineering at the University of Texas at Arlington.

Xinjie is a first-year Ph.D. student in the Department of Electrical and Computer Engineering at The University of Texas at Austin. He is very fortunate to be co-advised by Prof. Ufuk Topcu and Prof. David Fridovich-Keil. His research interests lie in developing decision-making and control strategies for autonomous systems in dynamic and uncertain environments. He is currently focused on intelligent, safe interactions of robots with other agents and efficient robot control policy learning.

Andriy Malyshchak is an undergraduate student studying Aerospace Engineering in the Engineering Honors College as well as minors in computer science, and business at the University of Texas at Austin. Andriy’s main interests lie in autonomous robot navigation/perception, numerical optimization for path planning, manipulating artifical intelligence/ML techniques to create control methods, and effective societal integration for new robot technology.

Besides helping with research, Andriy is also a part of Antler Venture Capital’s fellowship program helping grow the next generation of U.S. startups, 1/35 Microsoft Campus Leads across the U.S., founding member of Texas Guadaloop’s business/engineering teams, and former software engineer for Tuk-Tuk, an Austin startup. Andriy hopes to pursue a Master’s in engineering as well as an MBA with the hope of working at the intersection between deep-tech and venture capital.

In his free time, Andriy enjoys working out, volunteering in the community, and listening to great music.

Fernando Palafox is a PhD student at the University of Texas at Austin. Fernando is interested in understanding multi-agent autonomous systems through the lens of controls, game theory, and artificial intelligence. Fernando holds a BS and MS in Aerospace Engineering from the University of Colorado Boulder. Outside of research, he is a competitive cyclist and enjoys photography.

Ryan Park is an undergraduate student studying Computer Science in the College of Natural Sciences as a Polymathic Scholar as well as Aerospace Engineering in the Cockrell College of Engineering. Ryan’s main interests lie in theory development; currnetly in using kernel methods in place of neural ODE’s.

Besides helping with research, Ryan is also a part of the Undergraduate Computational Finance Club, a competitive club dedicated to learning and implementing trading strategies. Ryan has previously worked at Boeing as a software engineer, focusing primarily on improving sensor fusion algorithms.

In his free time, Ryan enjoys rock climbing, cooking Korean food, and light reading.

Tianyu Qiu is a first-year Ph.D. student in the Department of Aerospace Engineering and Engineering Mechanics, Cockrell School of Engineering at The University of Texas at Austin. He is advised by Prof. David Fridovich-Keil. His research interests lie in game theory, reinforcement learning and decision-making for multi-agent systems and robots.

Prior to UT Austin, Tianyu received his M.S. degree in Electronic Information from the Department of Automation, School of Electronic Information and Electrical Engineering at Shanghai Jiao Tong University. His master thesis was on Social Navigation for Mobile Robots based on Inverse Dynamic Games. Tianyu obtained his B.S. degree in Electrical and Computer Engineering from Shanghai Jiao Tong University.

Jonathan Salfity is a PhD student at the University of Texas at Austin, primarily advised by Mitch Pryor in the Nuclear and Applied Robotics Group. Jonathan’s research covers robotics, control theory, learning for control, machine learning, reinforcement learning, and dynamic game theory. His research north star is to blend the best outcomes of dynamics and control theory – safety guaranteees, robustness, sensitivity, stability – into emerging learned-based algorithms for safe, robust autonomous systems.

Prior to enrolling at UT Austin, Jonathan worked for 4 years at HP Labs in Palo Alto, CA, where his research focused on indoor mobile robots, robotic sensing and manipulation for post-processing of 3D printed parts, and reinforcement learning. Prior to HP Labs, Jonathan worked for 2 years in HP 3D-Print R&D on low-level control engineering in San Diego, CA. Jonathan completed his M.S. and B.S. in Mechanical Engineering at UCLA.

Nick Strohmeyer is a PhD student co-advised by Sriram Vishwanath in the WNCG Group. His research interests lie in the use of optimal control, machine learning, and game theory for modeling dynamical systems and the design of behaviorial planning algorithms. Prior to attending UT Austin, Nick worked as a Data Analyst in digital marketing and telcommunications for 3 years. He graduated with a B.S. in Mathematics from the University of San Francisco. In his free time, Nick enjoys playing recreational sports such as ice hockey, softball, and tennis and getting outdoors to hike or explore.