Dr. Henrik I. Christensen

Principal Investigator and Research Advisor

Henrik I. Christensen is the director of Robotics at UC San Diego and the Qualcomm Chancellor’s chair of robot systems. Dr. Christensen received his academic training (M.Sc and Ph.D.) from Aalborg University in Denmark. He has since then held positions at Aalborg University, University of Pennsylvania, and Georgia Tech before joining UC San Diego. Dr. Christensen does research on robotics, computer vision and AI with an emphasis on a systems approach to problems. He has published more than 350 papers and serves on multiple editorial boards. He is the Editor of Trends and Foundations in Robotics. Dr. Christensen was the editor of the US National Robotics Roadmap 2009, 2013 and 2016. He won the Joseph Engelberger Award 2011, which is the premier robotics industry award. He was also named Boeing Supplier of the Year and received an honorary doctorate (Dr. Techn. h.c.) from Aalborg University 2014. Dr. Christensen is the co-founder of multiple companies and serves as an advisor to companies, governments, and organizations across 4 continents.

• www.hichristensen.net/

Dr. Todd Hylton

Research Advisor

Hylton has a track record of creating successful programs and products both in government and industry, including a multi-million dollar DARPA effort to create a neuromorphic chip. His research interests include machine learning algorithms and natural intelligence. Hylton most recently served as executive vice president of strategy and research at Brain Corporation, a San Diego-based robotics startup. Prior to Brain Corp., Hylton launched a series of successful projects as a program manager at DARPA, including a multi-million dollar effort to develop a chip inspired by the function of biological nervous systems. He launched DARPA’s SyNAPSE program in 2007, which developed a chip whose architecture is inspired by the brain. Hylton also managed the Nano-Air Vehicle program at DARPA. Hylton has been awarded 19 patents. In the early 2000s, he cofounded 4Wave, a startup specializing in semiconductor equipment.

David Paz

Project Lead

David Paz is a PhD student in Computer Science at UC San Diego’s Computer Science and Engineering Department. While earning his B.S. in Computer Engineering and M.S. in Intelligent Systems, Robotics, and Control at UC San Diego, he contributed to a number of research projects involving sensor development, hardware accelerators, high-performance computing, and autonomous vehicles. At the moment, he is working for the Autonomous Vehicle Laboratory (AVL) at the Contextual Robotics Institute under the supervision of Dr. Henrik I. Christensen. Paz’ research involves road user trajectory prediction, intent recognition, and dynamic scene understanding to address the scalability constraints from current state of the art architectures. During his time at AVL, Paz has worked on the mapping, localization, planning and control strategies for UCSD’s self-driving mail delivery cars and has collaborated closely with members of the AVL to characterize overall AV performance and develop robust perception and simulation strategies.

• dpazruiz@ucsd.edu | avl.ucsd.edu/dfpazr/

Henry Zhang

Perception Lead

Hengyuan Zhang is a Ph.D. student at the CSE Department of UCSD working with professor Henrik I. Christensen. He earned his master’s degree in Intelligent Systems, Robotics and Control at the ECE Department of UCSD and Bachelor’s degree in Automation at Nanjing University. His research is in tracking and sensor fusion in Autonomous Driving. He is part of the founding team in the Autonomous Vehicle Lab and has worked on LiDAR based detection, tracking and lidar-camera fusion for object tracking and semantic mapping at AVL. He is excited about using robotics technologies to make human lives better.

• hyzhang@ucsd.edu | www.henryzhangzhy.github.io/

Srinidhi Srinivas

Dynamic Scene Modeling

Srinidhi is a graduate student in the Electrical and Computer Engineering department majoring in Intelligent Systems, Robotics and Control. He earned his Bachelor’s in Telecommunication engineering from PES Institute of Technology, Bangalore where his thesis was Brain Computer Interface for Game Control. He worked at Analog Devices Inc. as a Senior Software Engineer for 3 years in the Automotive Infotainment division developing software frameworks for next generation infotainment platforms. At AVL his research involves road network estimation and dynamic scene modeling. He is also interested about the prospects of intersection of robotics and AI.

Seth Farrell

Systems and Sensor Integration

Seth is a graduate student in the Electrical and Computer Engineering department majoring in Intelligent Systems, Robotics and Control. He graduated from the University of California, San Diego with a Bachelor’s degree in Electrical Engineering with a focus on Machine Learning. He is currently working on systems integration for the self-driving mail delivery cars.

Jing-yan Liao

Perception

Jing-Yan Liao is a master student majoring in Intelligent Systems, Robotics, and Control in UCSD ECE department, and he received his Bachelor degree in Mechanical Engineering at National Taiwan University. The project he is currently working on is auto/semi-auto labelling project at AVL.

Parthasarathi Kumar

Perception

Parthasarathi Kumar is a master’s student in the Electrical and Computer Engineering department at UCSD. He completed his undergraduate degree in Electrical and Electronics engineering from BITS-Pilani, Hyderabad and then worked as a software developer at MathWorks. He is currently working on the auto-labeling project at AVL.

Zihan Zhang

Perception

Zihan is a graduate student in the Computer Science & Engineering department majoring in Computer Science. She earned her Bachelor’s degree in Computer Science at the University of California, San Diego. She is interested in the intersection of robotics and computer vision. She is currently working on the monocular depth estimation project at AVL.

Varun Vupparige

Motion Planning

Varun Vupparige is a graduate student in Mechanical and Aerospace Engineering specializing in Dynamics and Controls. He earned his bachelor’s degree in Mechanical Engineering from the RV College of Engineering. He worked as a Mechatronics Engineer at Noccarc Robotics, an early stage startup which built ICU Ventilators during COVID pandemic. He is currently working on dynamic motion planning for autonomous micro-mobility vehicles under the supervision of David Paz and Professor Henrik I. Christensen. He is passionate about impactful technologies which can better common people’s lives.

Kai Chuen Tan

Motion Planning

Kai Chuen Tan is a M.Sc. Electrical and Computer Engineering student with a specialization in Intelligent Systems, Robotics, and Control at the University of California, San Diego. He is currently working on dynamic motion planning for autonomous micro-mobility vehicles as a Graduate Research Assistant at the UCSD Autonomous Vehicle Laboratory under the supervision of David Paz and Professor Henrik I. Christensen. He graduated with a Bachelor of Science in Mechanical Engineering with Summa Cum Laude from the Ohio State University and earned an Honor Research Distinction in Aeronautical and Astronautical Engineering. To learn more about his work, please visit https://www.kaichuentan.ml/

• kctan@ucsd.edu

Narayan Elavathur Ranganatha

Perception

Narayanan Elavathur Ranganatha is a Computer Science MS. student with a strong interest in autonomous systems and deep learning. He earned a Bachelor’s degree in Computer Science and Intelligent Systems from Manipal Institute of Technology. He has experience working with various programming languages and libraries such as C++, C, Python, ROS, PyTorch, Tensorflow and has published a paper in INTERSPEECH 2020. He has worked on various projects related to 3D object detection, cross-modality registration, and has gained experience in autonomous vehicle research and open source contributions. Currently, he is working as a research assistant at the Autonomous Vehicle Laboratory at UCSD, where he is benchmarking 3D Object Detection models on Waymo and Argoverse2 datasets and setting up testing infrastructure on CARLA simulations. His future aims include continuing to work on cutting-edge research in the field of autonomous systems and deep learning.

Parth Doshi

Prediction

Parth is a CSE MS student at UCSD. His previous experience includes internships in the autonomous vehicles, robotics, and video processing domains. His work at AVL relates to motion forecasting and prediction for multiple agents on the road.