About
Highly accomplished Robotics Engineer with a Master of Science in Robotics and a Bachelor of Science in Mechanical Engineering. Proven expertise in developing advanced AI/ML models, control systems, and robotic manipulation solutions. Skilled in Python, C/C++, PyTorch, TensorFlow, and ROS, with a strong track record of quantifiable achievements in deep learning, computer vision, SLAM, and multi-agent systems. Adept at leading technical teams and optimizing complex engineering workflows, demonstrated through contributions to cutting-edge research and competitive projects.
Work
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Summary
Conducted advanced research in deep learning for autonomous systems, focusing on semantic understanding and efficient model deployment.
Highlights
Pioneered an end-to-end deep learning model for precise relative pose estimation from KITTI semantic LiDAR point clouds, leveraging PointNet and kernel correlations for enhanced semantic encodings.
Streamlined model deployment and reproducibility by containerizing GPU PyTorch and other library dependencies using Docker, optimizing research workflows.
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Summary
Led a team of 11 student engineers in vehicle simulation and analysis for a global competition, ensuring high-performance design.
Highlights
Managed a team of 11 student engineers, overseeing the development of 3D vehicle simulations using Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD).
Initiated and delivered comprehensive training on ANSYS simulation software to 11 team members, significantly enhancing the team's analytical capabilities for vehicle performance analysis.
Contributed to the team's achievement of being recognized among the top 21 global teams, qualifying for the final round of the 2019 SpaceX Hyperloop Competition.
Education
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Master of Science
Robotics
Grade: GPA: 3.95
Courses
Self-Driving Cars (Triangularization, Stereo Vision, SIFT, SLAM, Odometry, LiDAR Point Clouds, A*)
Deep Learning for Vision (Convolutional Neural Networks, Recurrent Neural Networks, Transformers)
Dynamic Programming (Stochastic DP, Partially Observable Markov Decision Processes, Multi-Armed Bandit)
Awards
Michigan Robotics Fellowship
Awarded By
Robotics Institute at University of Michigan, Ann Arbor
Awarded for exceptional academic achievement and potential in robotics research.
Provost's Undergraduate Fellowship
Awarded By
UC Davis Undergraduate Research Center
Recognized for outstanding undergraduate research contributions.
Dean's Honor List
Awarded By
College of Engineering, UC Davis
Consistently achieved high academic standing in the College of Engineering.
United Airlines Scholarship
Awarded By
Scholarship America
Merit-based scholarship supporting academic pursuits in engineering.
Skills
Programming Languages
Python (Pandas, PyTorch, TensorFlow, OpenCV), C/C++, MATLAB, JavaScript.
Robotics & Control Systems
ROS, SLAM, Odometry, LiDAR Point Clouds, PID Control, Kinematics (Forward/Inverse), Multi-Agent Systems, Control Barrier Functions, Robotic Manipulation.
Machine Learning & Deep Learning
PyTorch, TensorFlow, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transformers, Transfer Learning, Image Classification, Deep Learning Models, Kaiming Initialization, Batch Normalization, Feature Extraction, Fine-tuning, KNN, SVM.
Computer Vision
OpenCV, Stereo Vision, SIFT, RGB-D Camera Calibration.
Optimization & Algorithms
Dynamic Programming, Stochastic DP, Partially Observable Markov Decision Processes, Multi-Armed Bandit, A* Path Planning, Bernoulli Thompson Sampling.
Tools & Methodologies
Git, Docker, Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), ANSYS.