Dr. Yongchao LIU is currently a Research Scientist II (research faculty member) in the School of Computational Science & Engineering, Georgia Institute of Technology (USA) (from 01/2015 to present). Before that, he worked as a postdoctoral researcher in the Institute of Computer Science, University of Mainz (Germany) (from 11/2011 to 01/2015). He earned his Ph.D degree in computer engineering from Nanyang Technological University (Singapore) in 2012 (supervised by Dr. Bertil Schmidt and Dr. Douglas Maskell). Prior to that, he earned the Master and Bachelor degrees in computer science and technology from Nankai University (China) in 2008 and 2005, respectively.
His research philosophy is to inspire technological innovation for healthcare and serve people around the globe. He has been an active researcher in parallel computing and bioinformatics and his technical contributions to this interdisciplinary research field are demonstrated in his novel parallel algorithms and software tools for large-scale biological data analysis. These parallel algorithms and tools streamline fundamental and computationally challenging biological issues with parallel computing, via in-depth exploration of current high performance computing techniques and technologies such as hardware accelerators (e.g. GPUs and Intel Xeon Phis) and clusters (e.g. CPU/GPU/Xeon Phi clusters). On the other hand, these algorithms and tools investigate a set of related critical issues in bioinformatics and have actually established an innovative and unique analysis platform for large-scale biological datasets, especially next-generation sequencing reads. His research interests focus on parallel and distributed algorithm design for bioinformatics, heterogeneous computing with accelerators (GPUs and Xeon Phis), high performance computing on big data, and parallelized machine learning.
He has released a set of software tools for reproducible research and public use, most of which are open-source, associated with his paper publications. Among these algorithms, three CUDA-based open-source software tools, i.e. CUDASW++, mCUDA-MEME and CUSHAW, are rated by NVIDIA Corporation as popular GPU-accelerated applications, while DecGPU (the first parallel and distributed error correction algorithm for high-throughput short reads) was reported by GenomeWeb. Furthermore, some of his other open-source tools are also leading in their respective areas, including MSAProbs (multiple protein sequence alignment), Musket (Illumina reads error correction), CUSHAW2 (NGS base-space read alignment), CUSHAW3 (NGS base-space and color-space read alignment), PASHA (NGS de novo genome assembly), SNVSniffer (NGS germline and somatic SNV calling), SWAPHI (Xeon-Phi-based protein database search), SWAPHI-LS (Xeon-Phi-based pairwise DNA sequence alignment), ParaBWT (parallel construction of Burrows-Wheeler transform and suffix array), and LightSpMV (CUDA-based sparse matrix-vector multiplication).
He won two Best Paper Awards at IEEE ASAP 2009 and 2015, got one paper recommended for Best Paper Award at IEEE Cluster 2014 and won the Program to Empower Partnerships with Industry (PEPI) Award from South Big Data Hub of USA in 2016. Meanwhile, he is listed in the reputable Who's Who in America (Marquis Research) in 2016. He founded the Workshop on Accelerator-Enabled Algorithms and Applications in Bioinformatics (WACEBI) in 2016 and co-chaired the first Workshop on Parallel Software Libraries for Sequence Analysis (pSALSA) in 2015. In addition, he serves as a reviewer for some prestigious journals, such as Nature Methods, Nature Communications, Genome Biology, Nucleic Acids Research, Bioinformatics, ACM Computing Surveys, IEEE TPDS and IEEE/ACM TCBB, and as a program committee member for some prestigious conferences such as IEEE CCGrid, ICA3PP, IEEE HiPC and IEEE IPDPS.
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