Ahmed H. Qureshi
a1quresh at eng dot ucsd dot edu

I am a Ph.D. candidate in the ECE department at UC San Diego, advised by Prof. Michael Yip, and a Research Intern at Nvidia, working with Prof. Dieter Fox. My research revolves around robot learning for reasoning, planning, and control.

I develop reinforcement learning and planning algorithms inspired by the human cognitive process to enable machines safely interact with their environments, and solve practical navigation and manipulation problems.

Previously, I completed my M.S. in Engineering at Osaka University, where I worked with Prof. Hiroshi Ishiguro. During my MS, I was fortunate to be supported by the MEXT schorlarship. I did a B.S. in Electrical Engineering from NUST.

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News
Teaching

UCSD ECE 285: Advances in Robot Manipulation, Spring 2020 - Teaching Assistant (TA)
UCSD ECE 276C: Robot Reinforcement Learning, Fall 2019 - Co-Instructor
edX Osaka University: Cognitive Neuroscience Robotics – Part A, Winter/Fall 2016 - Teaching Assistant (TA)
Osaka Univerity: Variational Inference(derivation and examples), Dec 2016 - Instructor
Osaka Univerity: Deep learning and its applications, Fall 2015 - Instructor

Invited Talks
  • At Institute for Neural Computation-UC San Diego (Oct 2020), I gave a virtual talk on the "Emergence of a Mutualistic Relationship between Motion Planning and Machine Learning."
  • At University of Toronto (Sep 2020), I gave a virtual talk about Motion Planning Networks.
  • At 6th Heidelberg Laureate Forum (Sep 2018), I gave a talk on Deep Learning for Robotics in the Neural Computing & Deep Learning Workshop.
  • At CRI Seminars held at UCSD in 2018, I gave an invited talk on Learning-based Motion Planning Algorithms.
  • At AI Seminars held at Osaka University in 2017, I gave an invited talk on Intrinsically-Motivated Reinforcement Learning for Human-Robot Interaction.
  • I gave a talk on Living with Robotics-The Next Generation of Intelligent Machines at Information Technology University, Pakistan, in 2016.
Selected Publications

Constrained Motion Planning Networks X
Ahmed Qureshi, Jiangeng Dong, Asfiya Baig, Michael C. Yip
IEEE Transactions on Robotics, 2021 (underreview)
[project page] [bibtex]

Neural Manipulation Planning on Constraint Manifolds
Ahmed Qureshi, Jiangeng Dong, Austin Choe, Michael C. Yip
IEEE Robotics and Automation Letters, 2020
[project page] [bibtex]

Motion Planning Networks: Bridging the Gap Between Learning-based and Classical Motion Planners
Ahmed Qureshi, Yinglong Miao, Anthony Simeonov, Michael C. Yip
IEEE Transaction on Robotics, 2020
[project page] [bibtex]

Composing Task-Agnostic Policies with Deep Reinforcement Learning
Ahmed Qureshi, Jacob J Johnson, Yuzhe Qin, Taylor Henderson, Byron Boots, Michael C. Yip
International Conference on Representation Learning (ICLR), 2020
[project page] [bibtex]

Adversarial Imitation via Variational Inverse Reinforcement Learning
Ahmed Qureshi, Byron Boots, Michael C. Yip
International Conference on Representation Learning (ICLR), 2019
[project page] [bibtex]

Motion Planning Networks
Ahmed Qureshi, Anthony Simeonov, Mayur J. Bency, Michael C. Yip
International Conference on Robotics and Automation (ICRA), 2019
[project page] [bibtex]

Neural path planning: Fixed time, near-optimal path generation via oracle imitation
Mayur J. Bency, Ahmed Qureshi, Michael C. Yip
International Conference on Intelligent Robots and Systems (IROS), 2019
[project page] [bibtex]

Deeply informed neural sampling for robot motion planning
Ahmed Qureshi, Michael C. Yip
International Conference on Intelligent Robots and Systems (IROS), 2018
[project page] [bibtex]

Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments
Zahid Tahir, Ahmed Qureshi, Yasar Ayaz, Raheel Nawaz
Robotics and Autonomous Systems, 2018
[bibtex]

Intrinsically motivated reinforcement learning for human-robot interaction in the real-world
Ahmed Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, Hiroshi Ishiguro
Neural Networks, 2018
[bibtex]

Show, attend and interact: Perceivable human-robot social interaction through neural attention Q-network
Ahmed Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, Hiroshi Ishiguro
International Conference on Robotics and Automation (ICRA), 2017
[bibtex]

Robot gains social intelligence through multimodal deep reinforcement learning
Ahmed Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, Hiroshi Ishiguro
International Conference on Humanoid Robots (Humanoids), 2016
[bibtex]

Potential functions based sampling heuristic for optimal path planning
Ahmed Qureshi, Yasar Ayaz
Autonomous Robots, 2016
[bibtex]

Intelligent bidirectional rapidly-exploring random trees for optimal motion planning in complex cluttered environments
Ahmed Qureshi, Yasar Ayaz
Robotics and Autonomous Systems, 2015
[bibtex]


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