About Me, Research [details] and Fun Stuffs
I am an ANSYS Apache software developer (since June 2015) and Computer Science PhD student at University of California, San Diego (UCSD CSE, since September 2012). I became Ph.D. candidate after receiving my C.Phil. (FYI: M.S. < C.Phil. < Ph.D.) degree in Computer Science in June 2015.
For PhD research, I mainly work with Prof. Chung-Kuan Cheng (PhD UC Berkeley EECS), who is an IEEE Fellow and Distinguished Professor, in EDA algorithms, and sometimes with other colleagues in the areas of (distributed) computer systems, computation systems for (so-called big) data processing. My major research interest focus is algorithm design for analyzing dynamical systems, circuits, and networks at large, in order to improve the algorithmic complexities, as well as design practical algorithms. The current application is design automation for very large integration systems. My interest starts to shift towards big graph data processing and analysis, internet mathematics, and building intelligent computer systems since 2016. The other topics I touched since 2011, which still attracts me: graph algorithms (massive data and massive graphs), parallel programming via different computing resources (GPU, MPI, distributed computing), tensor computation, and network optimzation. For exampple, I have written code or designed some industrial products for large-scale matrix solvers, Krylov subspace methods, random walk, simulated annealing, which can also be used in the computation systems for big graph and data analysis, machine learning (see the details). My Erdős number is 3 (Me -> Chung-Kuan Cheng -> Ronald Graham -> Paul Erdős).
Meanwhile, I have been writing software as Software Developer II for ANSYS Apache at ANSYS, (another kind of "Big Data" and "Internet of Things" company). I was hired by this market-leading product team because of the research contributions in the summer of 2015, and work directly with Senior Architect Dr. S. P. McCormick (PhD, MIT EECS) and Vice President Dr. N. Chang (PhD, UC Berkeley EECS) for ANSYS Apache's Redhawk, Totem, etc. Therefore, along with my PhD study, I build commerical products to solve extremely large-scale problems in the real world (for example, in terms of computer science, my daily algorithmic problems can be reduced to analyzing the network flow in a graph with over billions vertices. Sometimes I need to optimize the network). This keeps me staying at the state-of-the-art industrial technology and exploring the academic frontiers.
[misc. (if interested):] Besides daily PhD research and writing software for Ansys, I spend time on reading the papers in Theory of Computer Science (Theory of Computing) and also have fun writing code for computing systems and infrastructures, helping startups (no COI since they are outside of EDA area, etc.). The most recent one was TrustedBridge Corp., which was started from one project of UCSD CSE computer system course CSE223B with my classmates (after one year, I left the team for focusing on the PhD research). I am open to the practical implementations in consistency models, efficient matrix solver, matrix computations for machine learning, big data analytics, recommendation systems, scaling database, caching layer design as well as applying my numerical and network analysis research for related areas.
Selected Publications in Top Venues [full list] [my citations]
Selected Patent [full list]
Industrial/R&D Lab Experience [details]
Academic Experience [details]
Selected Talks [full list]