Faculty Profile for Dr. Tanzima Islam
Biography and EducationI am an Assistant Professor at Texas State University (TXST). Before joining TXST, I was an assistant professor at Western Washington University (2017-2019), and a postdoctoral scholar at Lawrence Livermore National Laboratory (2013-2017). Broadly, I am interested in leveraging data science methodologies to address challenging questions that pertain to extreme-scale computing environments. My research spans fault-tolerance, performance modeling, prediction, and reproducibility for large-scale applications. I earned my Ph.D. in Electrical and Computer Engineering from Purdue University, and B.Sc. in Computer Science and Engineering from Bangladesh University of Engineering and Technology. My work enables large-scale simulations, often used in different fields such as bioinformatics, earthquake engineering, material science, to leverage the incredible computational capabilities of modern clusters.
Teaching InterestsHigh Performance Computing, Systems, Compiler Construction, Parallel Computing, fault-tolerance
Research InterestsMy research involves both modeling compute performance and designing scalable data movement strategies for large-scale applications in HPC environments. In the short-term, I am interested in leveraging data-driven analysis approach for comparative modeling with a focus on HPC co-design. My long-term research objective revolves around developing software solutions to ensure scalable performance under resilience and power constraints for large-scale systems.
Selected Scholarly/Creative Work
- Islam, T. Z., & Phelps, C. (2021). HPC@SCALE: A Hands-on Approach for Training Next-Gen HPC Software Architects. https://doi.org/10.1109/HiPCW54834.2021.00011
- Patki, T., Thiagarajan, J. J., Ayala, A., & Islam, T. Z. (2019). Performance optimality or reproducibility: that is the question (pp. 1--30). ACM/IEEE.
- Islam, T. Z., Ayala, A., Jensen, Q., & Ibrahim, K. (2019). Toward a Programmable Analysis and Visualization Framework for Interactive Performance Analytics. In International Conference for High Performance Computing, Networking, Storage and Analysis (SC) (pp. 70--77). IEEE. https://doi.org/10.1109/ProTools49597.2019.00015
- Islam, T. Z. (2019, March). SCR: Scalable Checkpoint / Restart (SCR) Library. Retrieved from https://github.com/LLNL/scr
- Thiagarajan, J. J., Anirudh, R., Kailkhura, B., Jain, N., Islam, T. Z., Bhatele, A., … Gamblin, T. (2018). PADDLE: Performance Analysis using a Data-driven Learning Environment (pp. 784--793). IEEE. https://doi.org/10.1109/IPDPS.2018.00088
- Award / Honor Recipient: R&D 100, R&D 100 Magazine. November 2019
- Award / Honor Recipient: Best Poster Award, Lawrence Livermore National Laboratory Annual Scholars Poster Symposium. 2016
- Award / Honor Recipient: LLNL Director’s Science & Technology Award for Excellence in Publication, Lawrence Livermore National Laboratory. October 2014
- Award / Honor Recipient: Achievement Award in Scholarly Activities, College of Science and Engineering. August 2021
- Award / Honor Recipient: Best Poster Award, Lawrence Livermore National Laboratory Annual Scholars Poster Symposium. 2015
- Lewis, Karen A, Whitten, Steven T (Co-Principal), Hough, Loren (Co-Principal), Hodby, Eleanor (Co-Principal), Theodoropoulou, Nikoleta (Supporting), Close, Eleanor W (Supporting), Rangelov, Blagoy (Supporting), Islam, Tanzima Z (Supporting), Betancourt, Tania (Supporting), Berry, Joe (Supporting), Finklestein, Noah (Supporting), MacGregor, Meredith (Supporting), Brown, Jed (Supporting), Eaves, Joel (Supporting). Creating Equitable Pathways to STEM Graduate Education, Sloan Foundation, Private / Foundation / Corporate, $249299. (Submitted: September 2, 2022, Funded: January 2023 - Present). Grant.
- Fulton, Lawrence V (Principal), Villagran, Melinda Morris (Co-Principal), , Bing Zhou (Co-Principal), Mendez, Francis A (Co-Principal), Ekin, Tahir (Co-Principal), Qasem, Apan Muhammad (Co-Principal), Konur, Dincer (Supporting), Alanis, Emmanuel (Supporting), Zihagh, Fereshteh (Supporting), Dong, Zhijie (Co-Principal), Shen, Xiaoxi (Supporting), De Nadai, Alessandro Stevens (Supporting), Zhu, Ye (Co-Principal), Hewitt, Barbara A (Co-Principal), Valles Molina, Damian (Supporting), White, Alexander (Supporting), Dolezel, Diane M (Supporting), Ioudina, Vera (Supporting), Islam, Tanzima Z (Supporting), Lee, Chul Ho (Supporting), Metsis, Vangelis (Supporting), Moradi, Masoud (Supporting), Gao, Ju (Supporting), Li-Jen, Lester (Supporting), Jones, Dustin (Supporting), Pham, Vung (Supporting), Holt, Melinda (Supporting), Kyung An, Min (Supporting), Islam, ABM (Supporting), Cho, Hyuk (Supporting), Liu, Quigzhoung (Supporting), Liang, Fan (Supporting), Topinka, Joseph Baar (Supporting). The Accelerating Credentials of Purpose and Value for the Texas Innovation Corridor (TIC) Consortium Grant, THECB, State, $1450000. (Submitted: November 2021, Funded: February 2022 - October 2022). Grant.
- Islam, Tanzima Z (Principal). Deep Learning for Predictive Performance Analysis during Application Development, Texas State University, $8000. (Funded: January 1, 2021 - Present). Grant.
- Islam, Tanzima Z (Principal), Ayala, Alexis, Jensen, Quentin. Proxy Application Validation for Exascale Co-design, Department of Energy, Federal, $40000. (Funded: June 2019 - September 2019). Grant.
- Islam, Tanzima Z (Co-Principal). Scientific Data Visualization course development, Oﬃce of Research and Sponsored Programs at Western Washington University, Institutional (Higher Ed), $12000. (Funded: 2018). Grant.
Selected Service Activities
Board of Directors
Bangladeshi Women in Computer Science and Engineering
Reviewer / Referee
DOE SciDAC Proposal Reviewer Panel
May 1, 2021-2021
Coordinator / Organizer
International Workshop on Big Data Computation, Analysis & Applications (BDCAA)
Attendee / Participant
NSF OAC Proposal Review Panel
Attendee / Participant
NSF SHF Proposal Review Panel