Hassaan Hashmi
Doctoral Candidate
New Haven, Connecticut, United States
Summary
👤
Senior🎓
Top SchoolHassaan Hashmi is a doctoral candidate at Yale University with eight years of experience specializing in reinforcement learning and electrical & computer engineering. He combines rigorous academic training—from a PhD program at Yale and an MS at KAIST to a summa cum laude BE in Mechatronics—with practical research that bridges control, robotics, and learning-based decision systems. Based in New Haven, he focuses on developing data-driven algorithms that scale from simulated environments to physical systems. His background suggests a strong foundation in both theoretical analysis and hands-on implementation, often approaching RL problems with insights from mechatronics and automation. Colleagues describe him as a careful experimenter who favors reproducible, mechanism-focused research that informs real-world control applications.
8 years of coding experience
Doctor of Philosophy - PhD, Electrical & Computer Engineering, Doctor of Philosophy - PhD, Electrical & Computer Engineering at Yale UniversityBachelor of Engineering - BE, Mechatronics, Robotics, and Automation Engineering, Summa Cum Laude, Bachelor of Engineering - BE, Mechatronics, Robotics, and Automation Engineering, Summa Cum Laude at National University of Sciences and Technology (NUST)Master of Science - MS, Electrical and Electronics Engineering, Master of Science - MS, Electrical and Electronics Engineering at Korea Advanced Institute of Science and Technology
Github Skills (31)
visual-odometry10
ardrone9
depth-estimation9
wireless9
slam8
reinforcement-learning8
robot-control7
kalman-filter7
deep-learning7
robotics-simulation7
computer-vision6
localization6
tensorflow6
algorithm6
simulation6
Programming languages (4)
Github contributions (5)
hassaanhashmi/awesome-deep-visual-odometry
Mar 2020 - Nov 2022
A repository to keep track of Deep Learning based methods for visual odometry (pull requests are always welcome)
Contributions:9 commits, 14 pushes, 1 branch in 2 years 8 months
deep-learningvisual-odometry
hassaanhashmi/pd_zdpg_plus
Aug 2021 - Nov 2022
Code for IEEE MLSP 2021 paper titled "Model-Free Learning of Optimal Deterministic Resource Allocations in Wireless Systems via Action-Space Exploration"
Contributions:10 commits, 1 PR, 47 pushes in 1 year 2 months
wirelessmodel-freeresource-allocationreinforcement-learningpolicy-gradient
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