About Me & Research

I'm Travers 'Hyunmin' Lee.

Belows are mind direction of research I want to (study/learn more) and challenge (try) at the future lab and|or company.

My main interests are grounded on {Algorithms, Theory of Computation, and Programming Paradigms} (the Spirit of CSE), Mathematics, and Curiosity on Nature. With that ground, my questions are centered around its interface with Computational Structures, {Learning Mechanism} of Brains (Intelligence), Cybernetics, and Computational Learning and Data Analysis (A.I).

- Algorithm Design and Analysis (Complexity) / Computability For purposeful (good) problems (in an appropriate sense, ~theoretically beautiful ~describing the nature ~solving societal problems), does algorithm exist that can solve it efficiently? Is it computable on formal models of computation? How's computational complexity of it?
- Computational Structures (s.a Social System) With a connection to the previous idea, many scientific fields (inc. nature, math, statistics, biology, economics, and others) are intrinsically computational in nature (as also stated at the Simons Institute for the Theory of Computing). I enjoy viewing problems arising in human society (social system - game theory, brains, etc.) through a computational lens at the structural and systems level. Which computation runs in nature and society?

- Math, Prob. to Statistics I have interests in the principal of proofs of (pure) mathematics, and the concept of a probability and statistics with a mathematical language.
- {Learning and Memorization} of Brains (Intelligence) Humans do complex tasks thanks to their learning and memorization abilities. Basically, I am interested in the information processing functions and reasoning mechanisms of the brain at the systems level (systems neuroscience).

- {Algorithmic and Theoretical Aspects} of -
- Computational Learning and (Big) Data Analysis (A.I)
Here, I want to challenge the algorithmic aspects (s.a. reducing the computational complexity, understanding the pareto-optimal (tradeoffs) between computational efficiency and statistical accuracy) and the theoretical aspects ('why it works') and various learning models on processors. In addition, I'm interested in the development of the practical (high-performant) data analytic algorithms (learning, pattern recognition, inference, decision, prediction) which is suitable for solving societal problems.

- Crowdsourcing Systems (Learning from Crowd) Extracting truth from opinions (or choices) from various mind (and quality) of human workers are very important and hard problem which needs careful consideration. I'm interested in formulating state-of-the-art reliable and efficient crowdsourcing systems. (Mechanism Design)

My study is driven by 'Understanding the Nature (Physical Reality)' and 'Solving Societal Problems'. I pursue where Theory and Science meets Practical Engineering Problems.

Travers 'Hyunmin' Lee
(email) travers.hy.lee _at_ gmail dot com
(mobile) +82-lO-8g38-6736