Courses
CS234
- Solid introduction to the field of reinforcement learning
- Covered topics such as Tabular MDP planning, Tabular RL policy evaluation, Q-learning, RL with function approximation, Policy search, Fast Learning, and Batch Reinforcement Learning
- Developed my own RL agents with PyTorch and OpenAI gym
CS144
- Computer networking principles and protocols
- Used C++ to create reliable data transport mechanisms
- Implemented core functionalities of TCP/UDP from scratch, gaining understanding of internet architecture and data flow
- Routing and congestion theory
CS107E
- Bare metal C programming in a Raspberry Pi
- Developed my own kernel modules from scratch, including memory allocation, keyboard and mouse drivers, graphics library and cpu-gpu message handling
Chinese
- My objective is to reach intermediate fluency until I graduate, so I plan to take it every quarter
AI Alignment
- Understand existing AI safety technical research
- Discuss efforts to implement policy measures that reduce AI risk
- Good overall perspective into the field of AI and its most cutting-edge advancements
Math 61DM
- Rigourous, proof-based Linear Algebra through a innovative Discrete approach with combinatorics
CS109
- Probability for Computer Scientists
- Formal Probability, Bayesian Networks, and basic Machine Learning
CS231n
- Computer Vision and Deep Learning
- Developed new road segmenation model
CS111
- Operating Systems
CS137a
- All-emcompassing introduction to autonomous robotics
CS149
- Parallel Computing. ISPC, CUDA, Triton, etc.
CS143
- Compilers. I built my own!
CS155
- Cybersecurity
EE108
- Digital System Design: Digital Logic, Verilog, Combinational and Sequential Logic, Flip-flops, timing constraints, etc.
EE180
- Computer Architecture: Pipelining, Assembly, ISAs, etc.
CS161
- Proof based algorithm theory
CS227
- Robot Perception