Featured Event:

ACSIC ANNUAL Conference ：SOFC 2025 

第8届北美计算机华人学者年会暨计算技术前沿研讨会于2025年5月30-31日在华盛顿特区举行。本次会议的目的如下：（1）探讨计算技术的前沿问题；（2）促进华人计算机学者的交流与合作；（3）凝聚华人计算机学者的共识

2025 ACSIC BoD Candidates

Yiran Chen

Dr. Yiran Chen is the John Cocke Distinguished Professor of Electrical and Computer Engineering at Duke University. He serves as the Principal Investigator and Director of the NSF AI Institute for Edge Computing – Athena, the NSF Industry–University Cooperative Research Center for Alternative Sustainable and Intelligent Computing (ASIC), and Co-Director of the Duke Center for Computational Evolutionary Intelligence (DCEI). Dr. Chen has authored over 600 publications and holds 96 U.S. patents. His work has received widespread recognition, including two Test-of-Time Awards and 14 Best Paper/Poster Awards. He is the recipient of the IEEE Circuits and Systems Society’s Charles A. Desoer Technical Achievement Award and the IEEE Computer Society’s Edward J. McCluskey Technical Achievement Award. Dr. Chen is a Fellow of the AAAS, ACM, IEEE, and NAI. He also serves as the inaugural Editor-in-Chief of IEEE Transactions on Circuits and Systems for Artificial Intelligence (TCASAI) and the founding Chair of the IEEE Circuits and Systems Society’s Machine Learning Circuits and Systems (MLCAS) Technical Committee. He chaired the ACM Special Interest Group on Design Automation (SIGDA) between 2021-2024. 

Xubin He

Dr. Xubin He is a Professor in the Department of Computer and Information Sciences at Temple University. He is also the Director of the Storage Technology and Architecture Research (STAR) lab. Dr. He received his PhD in Electrical and Computer Engineering from the University of Rhode Island, USA in 2002 and both his MS and BS degrees in Computer Science from Huazhong University of Science and Technology, China, in 1997 and 1995, respectively.  His research interests focus on data storage and I/O systems, including big data, cloud storage, Non-Volatile Storage, and scalability for large storage systems. He has published more than 100 refereed articles in prestigious journals such as IEEE Transactions on Parallel and Distributed Systems (TPDS), Journal of Parallel and Distributed Computing (JPDC), ACM Transactions on Storage, and IEEE Transactions on Dependable and Secure Computing (TDSC), and at various international conferences, including USENIX FAST, USENIX ATC, Eurosys, IEEE/IFIP DSN, IEEE INFOCOM, IEEE IPDPS, MSST, ICPP, MASCOTS, LCN, etc. He is the general co-chair for ACSIC SOFC’024 and IEEE NAS’2009, the program co-chair for ccGRID’2024, IPCCC’2017, ICPADS’2016, and MSST’2010, Doctoral program co-chair for SC’2023. Dr. He has served as a proposal review panelist for NSF and a committee member for many professional conferences in the field. He was a recipient of the ORAU Ralph E. Powe Junior Faculty Enhancement Award in 2004, the TTU Chapter Sigma Xi Research Award in 2010 and 2005, TTU ECE Most Outstanding Teaching Faculty Award in 2010, and VCU ECE Outstanding Research Faculty in 2015. He holds one U.S. patent. He is a senior member of the IEEE, a member of the IEEE Computer Society, USENIX (University campus representative), and ACSIC. 

Heng Huang

Dr. Heng Huang is a Brendan Iribe Endowed Professor in Computer Science and Electrical and Computer Engineering at the University Maryland College Park. Dr. Huang received the PhD degree in Computer Science at Dartmouth College. His research areas include machine learning, AI, data mining, and biomedical data science. Dr. Huang has published more than 350 papers in top-tier conferences and many papers in premium journals, such as ICML, NeurIPS, KDD, IJCAI, AAAI, RECOMB, ISMB, ICCV, CVPR, Nature Machine Intelligence, Nucleic Acids Research, Bioinformatics, Medical Image Analysis, Journal of Machine Learning Research, IEEE TPAMI, TMI, TIP, TKDE, TNNLS, etc. As PI, Dr. Huang currently is leading NIH R01s, U01, and multiple NSF funded projects on machine learning, AI, imaging-omics, precision medicine, electronic medical record data analysis and privacy-preserving, smart healthcare, and cyber physical system. He is a Fellow of AIBME and served as the Program Chair of ACM SIGKDD Conference 2020. 

Jiliang Tang

Dr. Jiliang Tang is a University Foundation Professor in the Department of Computer Science and Engineering at Michigan State University. He received early promotion to Associate Professor in 2021 and was promoted to Full Professor—designated as an MSU Foundation Professor—in 2022. Prior to joining MSU, he was a Research Scientist at Yahoo Research. He earned his Ph.D. from Arizona State University in 2015, and his M.S. and B.E. from Beijing Institute of Technology in 2010 and 2008, respectively. His research focuses on graph machine learning, trustworthy AI, and their applications in education and biology. He is the author of the book Deep Learning on Graphs (Cambridge University Press) and has developed several widely used open-source tools, including scikit-feature for feature selection, DeepRobust for trustworthy AI, and DANCE for single-cell analysis. Dr. Tang has received numerous prestigious awards, including the 2024 ACSIC Rockstar Award, 2022 AI’s 10 to Watch, 2022 IAPR J. K. Aggarwal Prize, 2022 SIAM SDM/IBM Research Award, 2021 ACSIC Rising Star, 2021 IEEE ICDM Tao Li Award, 2021 IEEE Big Data Security Award, 2020 ACM SIGKDD Rising Star, and a 2019 NSF CAREER Award. He has also received multiple industrial faculty awards from Amazon, Microsoft, Cisco, Johnson & Johnson, JP Morgan, Criteo Labs, and Snap, along with eight best paper awards or runner-ups. He actively contributes to the research community as a conference organizer (e.g., KDD, SIGIR, WSDM, SDM) and journal editor (e.g., TKDD, TKDE, TOIS). His work has been published in top-tier journals and conferences, amassing over 44,000 citations with an h-index of 99, and has received significant media attention.