I am a Professor at Department of Biomedical Informatics and Department of Computer Science at Stony Brook University. I received my Ph.D. in Computer Science from University of California, Los Angeles, and M.S. and B.S. in Engineering Physics from Tsinghua University, China. Prior to joining Stony Brook University, I was an assistant professor at Emory University. I was a research scientist at Siemens Corporate Research (Princeton, NJ) before joining Emory University.
My research goal on big data management and analytics is to address the research challenges for delivering effective, scalable and high performance software systems for managing, querying and mining complex big data at multiple dimensions, including 2D and 3D spatial and imaging data, temporal data, spatial-temporal data, and sequencing data. My research goal on biomedical informatics is to develop novel methods and software systems to optimize the acquisition, extraction, management, and mining of biomedical data with much improved efficiency, interoperability, accuracy, and usability to support biomedical research and the healthcare enterprise.
Prof Wang's research spans several disciplines including quantum dynamics theory, quantum computation and information, atomic physics, and computational science. She has published extensively, including a recent book published by Springer, four book chapters, and numerous journal papers. Prof Wang currently leads the quantum dynamics and computation group at The University of Western Australia. She and her research team have developed advanced numerical techniques to solve problems in both quantum and classical domain.
Dr Dapeng Wang is a Senior Bioinformatician in Integrative Analysis at the COMBAT consortium at the University of Oxford using multi-omics techniques in combination with the cutting-edge bioinformatic approaches and statistical methods to explore the pathogenesis of COVID-19 and stratification of patients as well as inform the treatment strategy based on genomics information.
Dr Wang received a bachelor’s degree in mathematics from the Shandong University in 2006 and obtained a PhD degree in bioinformatics from the Beijing Institute of Genomics of the Chinese Academy of Sciences in 2011. After his graduation, he continued to conduct research at the same institute from 2011 to 2014 and afterwards moved to the UK to take up various roles at the Cancer Institute at the University College London (2014-2016), the Department of Plant Sciences at the University of Oxford (2016-2018) and the LeedsOmics at the University of Leeds (2018-2020).
I’m a statistician / quantitative ecologist at the Northwest Fisheries Science Center (NOAA) in Seattle and an affiliate professor at the School of Aquatic and Fishery Sciences (SAFS) at the University of Washington. I work on a wide range of statistical problems – population dynamics, extinction risk, conservation genetics, fisheries stock assessment, reproductive success studies, etc. Most of the species I study are fish, but I also work with data from marine mammals, seabirds, and turtles. Much of my recent modeling interests have been pursuing applications of multivariate state-space time series and spatio-temporal models, isotope mixing models, and Bayesian model selection techniques.
Mary-Anne is a data scientist and roboticist with transdiscipinary expertise in computer science, artificial intelligence, business, and law. She works in disruptive innovation and bio-inspired technologies that make smart real-time decisions using backgroung knowledge and insights from data analytics.
I develop statistical methodology and software for the analysis of -omics data. I am particularly interested in the regulation of transcription: the molecular mechanism as well as its association with disease.
Dr. Keli Xiao is an Associate Professor in the College of Business at Stony Brook University. He received his Ph.D. from Rutgers University. Dr. Xiao’s research interests include business analytics, data mining, real estate/urban computing, economic bubbles and crises, and asset pricing. His research has appeared in many high-quality journals and conference proceedings, such as IEEE Transactions on Knowledge and Data Engineering (TKDE), Real Estate Economics, ACM Transactions on Knowledge Discovery from Data (TKDD), ACM Transactions on Management Information Systems (TMIS), ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), etc. He regularly serves as an SPC or PC of numerous prestigious conferences, such as AAAI, IJCAI, KDD, ICDM, SDM, CIKM, etc.. He is a senior member of the IEEE and the ACM.
Lexing Xie is Professor in the Research School of Computer Science at the Australian National University. She leads the ANU Computational Media lab (http://cm.cecs.anu.edu.au/). Her current research interests are in machine learning on graphs and time series, especially on understanding individual and aggregate behaviour in online social networks, at the intersection of media, language and behaviour. She was research staff member at IBM T J Watson Research Center 2005-2010. She is Associate editor for ACM TOIS, ACM TiiS and PeerJ CS.
Prof. Dr. Jiachen Yang is an Associate Editor for “Journal of Ambient Intelligence and Humanized Computing”, “Alexandria Engineering Journal”, “IEEE Access”, “IET Image Processing”, “Sensors”, etc. Currently, he is a Professor at the School of Electronical and Information Engineering, Tianjin University. From 2014 to 2015, he was a visiting scholar with the Department of Computer Science, School of Science, Loughborough University, U.K. In 2019, He was a visiting scholar with Embry-Riddle Aeronautical University. His recent research interests include image processing, artificial intelligence, and information security. He has published more than 150 technical articles in highly ranked journals, such as IEEE Transactions on Neural Network and Learning System, IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, etc. His Google Scholar H-index is 28.
Dr. Yang is an assistant professor and section leader for cancer genomics at the Hormel Institute. Dr. Yang obtained his PhD in the China Agricultural University, where his work involved the topic of microarray data analysis. Briefly he developed two statistical models, called ARSER and LSPR, to detect periodically expressed transcripts from evenly or unevenly sampled temporal microarray gene expression profiles respectively. By applying these algorithms to Arabidopsis and rice transcriptome, a list of novel clock-controlled genes that regulating plant circadian rhythm were identified. Dr. Yang finished his postdoctoral training at Emory University, where his research switched to cancer genomics and epigenomics. Working with researchers in Winship Cancer Institute, he developed a bioinformatics pipeline to analyze the whole genome mate-pair and pair-end sequencing and RNA-seq data from three tumor cells in multiple myeloma, which leads to discovering a novel SPI-ZNF287 t(11;17) translocation. After postdoctoral training, Dr. Yang joined Supercomputing Institute at University of Minnesota as a Bioinformatics Analyst working on both clinical genomics and prostate cancer research to define and characterize AR gene rearrangements from DNA-seq data, and also to interrogate genome-wide binding profiles of AR and AR variants in prostate cancer cells and tissues.
Longzhi Yang is the Director of Education and an Associate Professor (Reader) in the Department of Computer and Information Sciences at Northumbria University, U.K. He is the founding Chair of the IEEE Special Interest Group on Big Data for Cyber Security and Privacy. His research in the filed of AI, robotics, cyber security, and digital forensics has been supported by multiple research councils, charity organisations, and the industry. He is a Senior Member of IEEE, a professional member of British Computer Society, and a Senior Fellow of Higher Education Academy of United Kingdom.