Jingmin Wang Email & Phone Number

• Conducted extensive experiments using Twin-Delayed Deep Deterministic Policy Gradient to generate offline RL datasets. These were used for reference for an offline RL meta-learning paper submission at the Conference on Neural Information Processing Systems (NeurIPS) 2023• Implementing/researching 6+ existing offline model-based RL algorithms and devising novel methods of evaluating them within high-dimensional, long-horizon environments • Managing and debugging a large RL codebase consisting of over 20 algorithms and over 40,000 lines of code, reducing error rates and improving overall code coherence

Toronto, On

• Established a unique method of optical flow motion estimation for a camera with up to 20000 exposures/second by calculating pixel intensity frame differences and using RAFT, convolutional gated recurrent unit based deep learning model. • The previous method was included in an International Solid States Circuits Conference (ISSCC 2024) paper submission.• Worked with Coded Exposure Pixel (CEP) cameras, and engineered custom banded mask patterns for more precise light exposure control, filtering out indirect light and reducing glare• Developed a hardware framework in Xilinx Vivado and external oscilloscopes and function generators to generate custom FPGA signals, allowing synchronization between a raster scanning projector and CEP camera• Implemented 4+ lossless compression schemes, from Huffman encoding, Run-Length encoding, LZW encoding, and more

Toronto, Ontario, Canada

• Will be developing a reinforcement learning full lecture series and course, covering RL fundamentals to advanced topics such as decision transformers, offline RL, and RL with human feedback• Will be delivering course content to hundreds of students

Toronto, On

• Directing a project and leading 8-10 developers to construct a reinforcement learning and natural language processing based novel framework for real-time Forex and commodity trading.• Devising innovative features in addition to well-known market indicators, such as predicting the change in asset prices using the risk-to-reward ratio and a classification network

Toronto, On

• Developed the semantic segmentation submodel for PhotoML, an innovative photo culling software, using BEiT, which is a transformer (BERT) pre-trained on image data

Bachelor Of Applied Science - Basc, Electrical And Computer Engineering, 3.95/4

Full Ib Diploma, Math Analysis And Approaches Hl, Physics Hl, Chemistry Hl, Economics Hl, 45/45