I 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.
I am the co-founder of Bangladeshi Women in Computer Science and Engineering (BWCSE) -- research and mentoring platform for encouraging female students in Bangladesh to get involved in scholarly activities. Since its inauguration in 2014, this pioneering effort has provided hundreds of female students with information and guidance to apply for national and international opportunities and engaged them in resume-building activities. A list of student scholars who have benefitted from the mentorship and resources provided by BWCSE can be found here.
[Graduate] Are you interested in machine learning and its applications in automated decision-making for various domains? This project will provide opportunities to work with various technologies including machine learning, optimization, workflow applications, system software, and avail research internships at national laboratories. Please send me your CV if interested to learn more.
[Undergrad] I strongly encourage undergraduate students to get involved in research and my work has several components where they can meaningfully contribute such as software development and information visualization. Contact me if interested to get involved.
Recent news (Phone-friendly version here)
Congratulations to Chase Phelps and Tarek Ramadan for securing internships at LLNL and LBNL, respectively!
Our paper "College Life is Hard! - Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis" accepted at COMPSAC'21.
Our paper on "comparative Code Structure Analysis using Deep Learning for Performance Prediction" has been accepted at ISPASS'21.
RobustScience Community I
Excited to be in the RobustScience virtual café talking about scalability, reproducibility, and trustworthy issues of scientific workflows.
Received funding from the Research Enhancement Program at TXST for developing deep learning models using code structure to predict performance.
AMD Research Gift
My team will develop performance models for the next-gen AMD GPUs and improve their performance profiler rocprof. Thanks AMD for the gift!
AMD Equipment Grant
AMD has granted $100K worth of on-prem and Cloud HPC resources to TXST for COVID-19 related research. Read here: https://www.amd.com/en/corporate/hpc-fund
Organized a panel at ACM Richard Tapia Celebration of Diversity in Computing Conference on High Performance Computing. Take a look: video presentation and slides: https://drive.google.com/file/d/18daQuN8CCdkrIKgm2cHNrUBKJDggfZyx/view?usp=sharing
I gave a talk at AMD on my research in performance analysis on various architectures.
Invited talk at the Exascale Computing Project's annual hackathon organized by ORNL and BNL on Dashing (here).
Gave invited talk "Learning to Manage in Grad School for a Sustainable Career in Future" at Purdue University. Here is an uncut version.
R&D 100 Award Winner
Our research on scalable checkpoint restart won the R&D 100 award.
Our paper titled "Towards A Programmable Analysis and Visualization Framework for Interactive Performance Analytics" accepted in the ProTools workshop at SC'19.
I have moved! I have joined Texas State University in San Marcos. It was incredibly hard to leave my colleagues, students, and friends in beautiful Bellingham behind.
Our paper titled "Performance Optimality or Reproducibility: That is the Question" has been accepted in the performance track at SC'19 (acceptance rate: 72/344 = 20%)! Congratulations to Alex for his first SC paper.
Visiting faculty scholar at LBNL with my students for the summer.
Received the DOE SRP fellowship for my proposal titled "Proxy application validation for Exascale Co-design".
Congratulations to Gian-Carlo for getting his first research poster accepted at ISC'19!
Super excited to be a part of the Computer Systems Engineering (CSE) track at GHC 2019. About time women working in computer systems meet!
I am organizing the first workshop on how different application domains generate and analyze big data by leveraging HPC. The workshop (BDCAA) will be organized in conjunction with the IEEE COMPSAC'19 in Mulwaukee.
Attending the CRA-W Career mentoring workshop in Phonix, AZ.
Invited to present my research at the Sustainable Research Pathways Program in Lawrence Berkeley National Laboratory
I am the vice-chair of the performance track at ICPP 2019. Make sure to submit your work at the conference.
Our poster titled "Automatic Generation of Mixed-Precision Programs" has been accepted at SC'18. This work has been done in collaboration with LLNL.
Received XSEDE allocation grant for my Parallel Computing course. Happy computing!
Several of my students are interning at research labs such as LLNL, PNNL. Happy summer!
Our paper titled "Low Rank Smoothed Sampling Methods for Identifying Impactful Pair-wise Mutations" has been accepted at ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. Congratulations Nick!
Our paper titled "PADDLE: Performance Analysis using a Data-driven Learning Environment" has been accepted at IPDPS 2018!
Joined as an Assistant Professor in CS at WWU.
Our paper on scalable file system for burst buffers titled "MetaKV: A key-value store for metadata management of distributed burst buffers" has been accepted in IPDPS'17 [Acceptance rate ~22%].
I am a TPC member of the workshop "Advancing Science via Large Scale Text Analytics over Scientific Articles" that will be hosted as a part of the IEEE International Conference on Distributed Computing Systems (ICDCS) 2017.
I will serve as a TPC member for the performance track in SC'17.
Our paper titled "CMT-bone - A Proxy Application for Compressible Multiphase Turbulent Flows" has been accepted in the 23rd IEEE International Conference on High Performance Computing, Data, and Analytics that will be held in Hyderabad, India during Dec 19-22 2016.
My paper with the title "A Machine Learning Framework for Performance Coverage Analysis of Proxy Applications" has been accepted in the International Conference for High Performance Computing, Networking, Storage and Analysis (SC) 2016!
Started my own project as the PI on applying machine-learning to analyze application performance. The coolest parts of my project are (a) managing an awesome team; (b) working directly with the applications that are important for LLNL. Excited!
Attending IPDPS 2016 in Chicago. Our paper on "I/O aware power shifting" will be presented in the "I/O and Storage Track".
Heard back from the LLNL research council and they are interested to move forward with my LEARN proposal. The idea is about developing machine-learning techniques for correlating a plethora of system performance metrics to application performance.
I have been invited as a Program Committee member at the workshop "Tools for Program Development and Analysis in Computational Science" co-located with ICCS 2016.
Our paper titled "I/O Aware Power Shifting" has been accepted in IPDPS 2016.
Our paper titled "Fault Tolerance Assistant (FTA): An Exception Handling Approach for MPI Programs" has been accepted in the ExaMPI workshop at SC'15.
Best poster 2015
Our poster titled "Towards Scientific-Data Compression Using Variable Clustering" received the Best Poster Award in the Computation Directorate's scholar poster session at LLNL.
Our paper titled "Exploring the MPI Tool Information Interface: Features and Capabilities" has been accepted in IJHPCA.
My work titled "Reliable and Efficient Distributed Checkpointing System for Grid Environments" has been accepted in Journal of Grid Computing.
My work on proxy application validation is one of the few projects that have been selected to showcase LLNL's research in achieving the laboratory's mission to the External Review Committee (ERC).
I presented my work on proxy application validation at the Joint Operations Weapons Operations Group (JOWOG) 34 meeting at Sandia National Laboratory in New Mexico.
Our poster on the feasibility of applying lossy compression on checkpoints has been accepted in SC'14.
Our poster titled "Lossy Compression for Checkpointing: Fallible or Feasible?" received the Best Poster Award in the 2014 Computation Directorate's scholar poster symposium.
My poster on proxy application validation secured the 2nd place in Computation's Annual Postdoc Poster Symposium.