Hello, I am Brandon

I am a (Taiwanese) third-year undergraduate double majoring in Cognitive Science and Computer Science at U.C. Berkeley. (You may see my publications from my CV.)

My research experience and areas have a somehow stark difference: one being a human-centered field, another being a robot-centered one. But, from my experiences in these groups, and deeply impacted by Picard et al.’s report “Affective Computing” from the last century, I have found my area of interest to be in closing the distance between existing AI applications (be it models, or robots, or humanoid robots) and the human society that we live in. Particularly, I believe the demand of human-centered AI will still be prevalent in future if we still strive to integrate AI into human society, and considered that making my work contributing to this development would be a great way to live. I aim to pursue a related path as I eventually apply to a PhD program.

Over summer of 2023, I was interning at Max Planck Institute for Empirical Aesthetics in Computational Audition Group, working with several projects regarding computational psychology and cross-cultural alignment, and I continue this effort as an ongoing collaborator. To broaden my horizon and vision on different research disciplines within machine learning, I am currently performing reinforcement learning robotics research at Robot Learning Lab, where my works mostly concern humanoid robots– an archetype of robot enabled by humanoid anatomy but with a large research gap to fill before its existence become frequent in the public sphere.

Now, as an undergraduate in U.C. Berkeley, I have primarily focused on pedagogical works outside of my courses. This is my second semester as an undergraduate student instructor of the largest upper-division course in U.C. Berkeley regarding industry-prevalent data science techniques: DATA C100, and also my second semester coordinating the EECS 16A branch of Computer Science Mentors. In terms of fun projects, I have completed an awarded Data Science Discovery project in collaboration with Creative Commons, a course project in Convex Optimization course regarding “Provably Deep Classifiers under Adversarial Attack”, and another course project regarding “Diffusion Model as State-Diffuser for Deep Reinforcement Learning”. If possible, my hope is at making another project about Japanese Mahjong before I graduate (for the recent addiction my friends and I have arrived at this strategic, stochastic game).