I am highly interested in computational mathematics, (scalable) algorithms, optimization (magic), and language & signal processing.
Since June 2015, I am an ANSYS Apache Software Engineer, building scalable computation infrastructure, machine learning systems, big data applications, and matrix computation algorithms in the current market leading software platform, which conducts large-scale dynamical network simulation, analysis and verification for making successful tape-outs of modern low power CPU, GPU, and ASIC (Those chips are used by different purposes of computing, such as general logic operations, deep learning, big data processing, data center traffic, etc). It is my privilege to work with the R&D teams consist of legends in the area of design automation algorithms, such as the forerunner and researchers of AWE, the creators of MIT FastCap, CMU PRIMA, UT RICE, Synopsys PrimeTime and Apache Redhawk.
I was hired as an official employee when I was finishing my 3rd year PhD study (Note: I am still pursuing my final PhD degree). Previously, I received my C.Phil. degree in Computer Science in June 2015. Since then I am a Ph.D. candidate (ABD) at UCSD CSE. Thanks to Powell Fellowship and Qualcomm FMA Fellowship, I finished my full-time PhD study training as grad student within 3 years, including my coursework, teaching assignment, 3 research related internships (Qualcomm Research, ANSYS Apache, Synopsys), and published 13 papers (September 2012 - September 2015). Check out NEWS and PAPERS (2011-now) if you are interested.
For Master/PhD research, I work with Prof. Chung-Kuan Cheng, Prof. Wenjian Yu, Prof. Quan Chen, Prof. Xinnan Lin, Prof. Mansun Chan, and Prof. Pengwen Chen, mainly in algorithms for design automation and compauter aided design (CAD) to design computer chips (FYI, "AI has been applied to the design of computer chips, and in fact was one of the first applications of AI."). My PhD research interest focus is algorithm design, (sparse) matrix computation, numerical analysis and optimization 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 circuit theory, network analysis and physical design of very large integration systems. My Erdős number is 3 (Me -> Chung-Kuan Cheng ->Ronald Graham -> Paul Erdős). I write software for Apache at ANSYS (another kind of "Big Data" and "Internet of Things" company). I was hired by this market-leading product team (maybe) 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. (Those products have been used by many well-known companies to help design their CPU and GPU chips.) 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 (computationally) reduced to analyzing the network flow in a network/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.
Other Fun Stuffs
My interests of research applications are also exteneded to numerical algorithm and computation infrastructure for machine learning, signal processing, natural language processing (NLP), speech recognition, internet mathematics, big (graph) data processing, high performance computing (HPC), and building intelligent computer systems since 2016. Sometimes, I work with other colleagues of our CSE department in the areas of (distributed) computer systems, computation systems for data processing. For example, with Zhou Fang at Dean/Prof. Rajesh Gupta's team, we are building real-time and multiprocessors systems using programming languages like Google Go. The other topics, which I touched since 2011 and still attract me, are: graph algorithms (massive data and massive graphs), parallel programming via different computing resources (GPU, MPI, distributed computing), Markov chain, 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). I also spend time on reading the papers in Theory of Computer Science (Theory of Computing) and 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).
Selected Publications [full list] [my citations]
Selected Patent [full list]
Industrial/R&D Lab Experience [details]
Academic Experience [details]
Selected Talks [full list]