Short biography

Approximately 130 words — for panel slides and spoken session introductions.

Shaikh Arifuzzaman is an Assistant Professor of Computer Science at the University of Nevada, Las Vegas, where he directs the Data-intensive Scalable Computing (DiSC) Lab and is a Faculty Affiliate at Lawrence Berkeley National Laboratory. He designs machine learning methods and parallel algorithms for massive, dynamic graphs, and applies them to problems such as earthquake fault mapping, IoT intrusion detection, and epidemic modeling. His research is supported by the National Science Foundation, the U.S. Department of Energy, and state and institutional agencies, and has been recognized by awards and honors including two U.S. DOE SRP-HPC Fellowships and the Nevada Department of Education AI Partnership Award. He has published more than 55 peer-reviewed papers, mentored over 30 researchers, and served on more than ten review panels for NSF, DOE, and the Department of Defense.

Medium biography

Approximately 220 words — for conference programs and seminar announcements.

Shaikh Arifuzzaman is an Assistant Professor of Computer Science at the University of Nevada, Las Vegas, where he directs the Data-intensive Scalable Computing (DiSC) Lab and is a Faculty Affiliate at Lawrence Berkeley National Laboratory. His research develops graph machine learning methods and parallel algorithms for massive, dynamic graphs, together with high-performance computing methods for AI and scientific discovery. Supported by the National Science Foundation, the U.S. Department of Energy, and state and institutional agencies, his group applies these methods to earthquake fault mapping, urban resilience, epidemic modeling, and cybersecurity, and runs at scale on DOE leadership-class systems.

He has published more than 55 peer-reviewed papers and has mentored over 30 doctoral, master’s, undergraduate, and high-school researchers; both of his doctoral graduates now hold faculty positions, and his students routinely complete national laboratory internships. His work has been recognized by awards and honors including two U.S. DOE SRP-HPC Fellowships, the Nevada Department of Education AI Partnership Award, and first place in the IEEE Big Data Cup Competition. He has served on the program committees of ACM and IEEE conferences including SC, IPDPS, ICPP, IEEE Big Data, Cluster, CCGrid, ICS, HPCA, and ISC, reviews for journals including Nature Communications, IEEE TKDE, and ACM TKDD, and has evaluated proposals on more than ten review panels for NSF, DOE, and the Department of Defense.

Long biography

Approximately 450 words — for keynote introductions, award nominations, and press materials.

Dr. Shaikh Arifuzzaman is an Assistant Professor of Computer Science in the Howard R. Hughes College of Engineering at the University of Nevada, Las Vegas, where he directs the Data-intensive Scalable Computing (DiSC) Lab. His research develops algorithms, systems, and learning methods for data that is too large, too irregular, or too incomplete for standard tools. Most of this work concerns graphs: graph machine learning and graph neural networks, and parallel and distributed algorithms for massive, dynamic graphs. Across these areas he builds high-performance computing methods for AI and scientific discovery, with related work on the reliability of machine learning and language-model pipelines.

His projects, supported by the National Science Foundation, the U.S. Department of Energy, and state and institutional agencies, apply these methods to problems with a public stake, including data-driven mapping of the world’s active earthquake faults, urban and infrastructure resilience, epidemic modeling, and cybersecurity. As a Faculty Affiliate at Lawrence Berkeley National Laboratory, he develops and evaluates methods on DOE leadership-class systems, including NERSC platforms. Before joining UNLV he was an assistant professor at the University of New Orleans, and he has held positions at Sandia National Laboratories and the Biocomplexity Institute at Virginia Tech, where he earned his Ph.D. in Computer Science.

Dr. Arifuzzaman has published more than 55 peer-reviewed papers, and his work has been cited over 850 times. He has mentored more than 30 doctoral, master’s, undergraduate, and high-school researchers: both of his doctoral graduates now hold faculty positions, one dissertation was selected among the top ten worldwide for the SC21 Doctoral Showcase, and his undergraduate researchers have co-authored papers with national laboratory scientists.

He has served on the program committees of ACM and IEEE conferences across high-performance computing and data science, among them SC, IPDPS, ICPP, IEEE Big Data, Cluster, CCGrid, ICS, HPCA, and ISC. He has also organized conference and workshop programs as co-chair of the BigGraphs workshop at IEEE Big Data, local arrangements chair for IEEE HPCA 2025, and General Vice-Chair of the High Performance Computing Symposium. He reviews for journals including Nature Communications, IEEE TKDE, IEEE TAI, IEEE TNSE, ACM TKDD, and JPDC, and has evaluated proposals on more than ten review panels for NSF, DOE, and the Department of Defense, as well as computing time on the largest U.S. supercomputers as a reviewer for the DOE ASCR Leadership Computing Challenge. His work has been recognized by awards and honors including two U.S. DOE SRP-HPC Fellowships, the Nevada Department of Education AI Partnership Award, the UNLV Top Tier Doctoral Graduate Research Assistantship Award, two UNLV President’s innovation and research challenge wins, and first place in the IEEE Big Data Cup Competition. He serves on the Nevada Department of Education AI Executive Steering Committee.