Our paper titled "Reproducibility for HPC and Distributed Environments: Committees, Nondeterminism, Performance and Workflows" was published at ACM REP and is now available in the ACM Digital Library.

Honored to give an invited talk at EuroPar's Women in HPC session on bridging key gaps in performance-aware code development.

Our paper "QuantumX: A Few-Shot-Learning Approach for Quantum Performance Modeling in HPC" has been accepted at the International Workshop on Software Frameworks for Integrating Quantum and HPC Ecosystems in conjunction with ICS'25!

Our paper, "xAMM: Attention to Details Improves Cross-Platform Prediction Accuracy," (pronounced as "Exam") has been accepted in the ML4Sys/Sys4ML track at CCGrid 2025 (Acceptance rate: 25%)! This research has been funded by LLNL's Fractal project. Kudos, Aakash and the team! 

I will be giving a talk about our research on performance and result reproducibility in the Reproducibility BoF on Tuesday from 5:15-6:45pm in B201 @SC'24.

I had a great time at the CCDSC'24 workshop in Lyon, France. Fun fact: You get invited by Jack Dongarra, the 2022 Turing Award winner, to be in one of those. [Turing Award is equivalent to the Nobel Prize in Computer Science]

I am honored to have been selected as this year's Presidential Seminar Award winner! This award is presented to a TxState faculty for their superlative scholarly and creative activities. 

Our paper titled "Building the I (Interoperability) of FAIR for performance reproducibility of large-scale composable workflows in RECUP" has been accepted at the Reproducible Workflows, Data Management, and Security workshop.

I have been invited to the Rising Stars Panel at UT Austin.

Excited! Our collaborative proposal with Brookhaven National Lab and Argonne National Lab has been funded by DOE. 

I have been invited to give a talk at the CHEOPS workshop colocated with EuroSys'22. 

My invited paper talks about designing an HPC course focusing on distributed memory parallelism and scalable parallel I/O patterns.

Our paper on "comparative Code Structure Analysis using Deep Learning for Performance Prediction" has been accepted at ISPASS'21. 

Our paper titled "Attention-Informed Surrogates for Navigating Power-Performance Trade-offs in HPC" has been accepted at ML For Systems workshop@NeurIPS! 

Invited Talk @ Monterey Data Conference (Monterey, CA) — Exciting discussions on deploying ModelX into HPC production facilities!

📄 Paper Accepted @ HPDC’25 (19% acceptance) — “ModelX: A Novel Transfer Learning Approach Across Heterogeneous Datasets” (led by Arunavo Dey), considered for Best Paper Award!

I have been awarded the prestigious NSF CAREER award this year! This project will achieve my vision of AI4Performance!

Our paper, titled 'Performance Characterization and Provenance of Distributed Task-based Workflows on HPC Platforms,' has been accepted in the WORKS workshop at SC'24. 

Congratulations to Aakash for securing a data analytics internship at LLNL for summer'24!

Our research poster, "Graph-Based Anomaly Detection in Chimbuko: Feasible or Fallible?" has been accepted in the SC'23 research poster session. 

I have been awarded the "Presidential Distinction Award", the highest award for creative and scholarly activities in the College of Science and Engineering (COSE) at TxState.

Thanks AMD for supporting our research through generous gifts!

I have received the Early Career Research award from the Department of Energy (DOE) for the innovative application of deep learning to accelerate real-time performance analytics!

Our paper "libNVCD: An Extendable and User-friendly Multi-GPU Performance Measurement Tool" has been accepted at IEEE COMPSAC'22 (acceptance rate: 23%)!

I won the College of Science and Engineering's "Achievement Award in Scholarly Activities" at TxState. Honored!

Excited to be in the RobustScience virtual café talking about scalability, reproducibility, and trustworthy issues of scientific workflows. 

Promoted to Associate Professor! Grateful to my students, collaborators, mentors, and the Almighty.

My Ph.D. student Elvis Fefey’s research on heterogeneous scheduling algorithms just won the Best Paper Award at IEEE Cloud Summit! Proud advisor moment! 🎉

Elvis Fefey passed his prelim exam! This milestone is especially exciting because Elvis is the first Ph.D. student to join Per4ML and also the first from our lab to reach and pass this critical stage. Congratulations, Elvis!

Congratulations to Banooqa for her paper titled "On the role of prompt construction in enhancing efficacy and efficiency of llm-based tabular data generation", funded by my ECRP. This project was done in collaboration with Kowshik Thopalli@LLNL and Dr. Jayaraman J. Thiagarajan@Apple.

I am grateful to have received the College of Science and Engineering (CoSE)’s “Research Millionaire” award. This award honors CoSE faculty that have been awarded $1M or more in research grant funding over the past three fiscal years (FY2022-2024). 

Congratulations to Banooqa, Zaeed, Chase+Ankur, and Arunavo for their respective papers at IEEE COMPSAC in Osaka, Japan! These papers range from addressing gaps that enable the effective use of LLMs, GNNs, and transfer learning for performance analytics.

Our paper on using graph-based representation learning for performance analytics has been accepted at International Conference on Machine Learning and Applications (ICMLA)! (Acceptance rate ~25%)

We have two papers accepted at IEEE COMPSAC'23. Congratulations to Arunavo and Chase (acceptance rate: < 27%)! 

Our joint proposal with University of Colorado Boulder to the Sloan Foundation has been funded!

I have received DOE's SRP-HPC fellowship and will be conducting research over the summer as a visiting scholar at Brookhaven National Laboratory. My students--Chase Phelps, Arunavo Dey, and Alicia Guite (sophomore) will also join me.

I am chairing the Performance measurement, modeling, and analysis track at SC this year. Excited and honored!

Congratulations to Chase Phelps and Tarek Ramadan for securing internships at LLNL and LBNL, respectively!

Honored to serve as Performance Track Chair for SC’26.

Invited Talk @ ML4SW Workshop (PASC’25, Switzerland) — Great interest in integrating ModelX into HPC+AI/ML libraries!

Our paper titled "Structure‐Aware Representation Learning for Effective Performance Prediction" has been published in Concurrency and Computation: Practice and Experience.

Gave an invited talk about my career path in the SDSC booth #3107 (exhibition floor) on Wednesday at 2pm. Thank you WHPC!

I am co-chairing the poster session at ISC'24. Please consider submitting your work. If you would like to serve as a reviewer, please contact me.

Thank you, AMD for continuing to support research on AI/ML-driven performance analytics!

The faculty senate has awarded me the prestigious and selective Valero Award. Thanks!

We have received DOE's SRP-HPC fund again this year, which will allow faculty-led (that's me) research team of 4 students (2 Ph.D.s, 1 M.S. and 1 undergrad) to visit Brookhaven lab in the summer.

Congratulations to Elvis, Zaeed, and Arunavo for getting their lightening talks accepted at NYSDS on how they plan to leverage ML for HPC.

Congratulations to Tarek Ramadan for successfully defending his M.Sc. thesis. 

Thanks to AMD for the 50K gift! This is the second year of our collaboration. Here is to many more!

Our paper "College Life is Hard! - Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis" accepted at COMPSAC'21.