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Ph.D., Dr. Techn. h.c. Henrik Iskov Christensen
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.
Vikas Dhiman is currently a joint Postdoc with Prof. Nikolay Atanasov and Prof. Henrik Christensen. He received his Ph.D. in 2019 from Electrical and Computer Engineering at the University of Michigan, Ann Arbor under the supervision of Prof. Jason J Corso.
Prior to this, Vikas obtained his Bachelor of Engineering (B.E.) degree in Electrical Engineering from Indian Institute of Technology, Roorkee, India in 2008.
His research interests are in the area of Machine Learning and its applications to Robotics & Computer Vision. He is currently working on applications of Reinforcement Learning for navigation in unseen environments.
Akanimoh Adeleye is a PhD student in the Department of Computer Science and Engineering at the University of California, San Diego.
His research focuses on optimal mobile robot exploration for mapping.
Carlos Nieto-Granda is a Ph.D. Candidate in Intelligent Systems, Robotics, and Control in the Department of Electrical and Computer Engineering at University of California San Diego under the advisement of the Qualcomm Chancellor’s Chair of Robot Systems Prof. Henrik Christensen and Prof. Nikolay Atanasov. He is also affiliated with the Cognitive Robotics Laboratory in the Contextual Robotics Institute.
He holds a Master degree in Computer Science with specialization in Computational Perception and Robotics from the Georgia Institute of Technology, and a B.S. degree in Electronics and Computer Engineering from Tecnologico de Monterrey, Campus Estado de Mexico. He has held visitor researcher positions at the United States Army Research Laboratory (ARL), Georgia Institute of Technology, University of Pennsylvania, Cornell University, Mathematics Research Center (CIMAT) and Tecnologico de Monterrey.
His research focuses on developing autonomous navigation and mapping architectures for heterogeneous multi-robot teams through place recognition and categorization techniques.
Anwesan Pal is a Ph.D. student in the Department of Computer Science and Engineering at UC San Diego (UCSD) under the supervision of Prof. Henrik I. Christensen.
Prior to this, he obtained his Master of Science (M.S.) degree in Electrical and Computer Engineering from UCSD in 2019, and a Bachelor of Engineering (B.E.) degree in Electrical Engineering from Indian Institute of Engineering Science and Technology, Shibpur, India in 2017.
His research interests are in the area of Machine Learning and its applications to Robotics & Computer Vision. He is currently working on Object based Semantic Mapping of indoor and outdoor environments.
Priyam Parashar is a 4th year Ph.D. student at the University of California, San Diego and holds a M.S. in Robotics from Robotics Institute, CMU. Co-advised by Dr. Henrik I. Christensen and Dr. Ashok K. Goel (Georgia Institute of Technology), Priyam is interested in using deep knowledge to formulate hybrid models (driven by both reasoning and data) to support human-robot collaboration.
She currently uses the metareasoning framework to model an assembly task where the abilities of the agents and expectations from the task progression can be used for better sub-task selection and assignment.
David Paz is a graduate student in Intelligent Systems, Robotics, and Control at UC San Diego’s Electrical and Computer Engineering Department.
While earning his B.S. in Computer Engineering 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. AVL aims to develop self-driving cars for mail-delivery and micro-transit applications on campus while collaborating with its network of industry experts. Paz’ research focus is on robust self-driving car technology under stochastic environments: motion planning and intersection logic, perception, SLAM, and controls.
Quan Vuong is a PhD student at the University of California San Diego. His advisor is Professor Henrik I. Christensen. He also works closely with Professor Hao Su and Professor Sean Gao.
His research focuses on Reinforcement Learning for control.
Shengye Wang is a PhD candidate in the Department of Computer Science and Engineering at the University of California, San Diego. His research interest includes robotics reliability engineering, long-term autonomous systems, robot software infrastructure, fault-injection on robots, and human-robot interaction. Before joining UC San Diego, he worked on accelerating applications with FPGAs. He received a Bachelor of Science degree in Microelectronics from Fudan University in 2014.
Shengye Wang currently works with Prof. Henrik Christensen at Contextual Robotics Institute, UC San Diego. He lives in La Jolla, California.
Ruffin White is a Ph.D. student in the School of Electrical and Computer Engineering, College of Engineering at the Georgia Institute of Technology. He is also affiliated with the Institute for Robotics and Intelligent Machines (IRIM) at Georgia Tech.
He was a summer research assistant at the Robotics Institute at CMU. He holds B.S. in Electrical Engineering and a Multidisciplinary Minor in Robotics from Rose-Hulman Institute of Technology.
His area of research interests is mobile robotic mapping, with a focus on semantic understanding for robot SLAM and planning.
Po-Jung Lai is a master candidate in Intelligent Systems, Robotics, and Control in the Department of Electrical and Computer Engineering at University of California San Diego. He is advised by Dr. Henrik I. Christensen to benchmark performance of Autonomous Vehicles at Contextual Robotics Institute.
Before he joined Cognitive Robotics Laboratory in the Contextual Robotics Institute, he worked in WeMo Scooter as Embedded System Engineer. He holds both B.S. in Electrical and Computer Engineering, and B.S. in Finance Management from National Chiao Tung University, Taiwan.
He is currently working on Autonomous and Manual driving comparison and environmental impact modelling.
Shixin Li is a master student in the CSE Department at UC San Diego. She is advised by Dr. Henrik Christensen. Shixin is interested in robotic perception, SLAM, and Human-Robot-Interaction.
During her first master year, she worked on Reinforcement Learning-based people tracking and following for service robot. Currently, she is working on building the framework of controlling quadcopters using gestures. Before joining UC San Diego, Shixin holds a B.S. in Electrical Engineering from Sichuan University, during which she did research in Neuromorphic computing and deep learning.
Yiding (Cassie) Qiu
Yiding Qiu is a MS student in the CSE Department at UC San Diego. She is advised by Dr. Henrik Christensen. Prior to this, she obtained B.S in Cognitive Science and Physics from UCSD. She is interested in SLAM, semantic mapping, and robotic perception.
James is a MS student in the Intelligent Systems, Robotics and Control depth, under the Electrical and Computer Engineering Department. He holds a BS in Computer Engineering from UC San Diego in 2017 and has worked previously on developing software for Cubesats and quadrotors.
James’ interests are in utilizing perception, control, and reinforcement learning to enable robotic manipulators to grasp novel objects in the real world.