niranjan[dot]hasabnis[at]intel[dot]com
I am currently a Research Scientist at Machine Programming Lab in Intel Labs. My research interests are at the intersection of application of artificial intelligence, machine learning, and formal method techniques to problems in compilers, HPC, software systems, and software engineering. Recently, along with my collaborators, I am also exploring ability of AI models to automatically parallelize serial code for shared-memory and distributed-memory systems. Previously, I implemented and published an automated system, named ControlFlag, that learns to detect programming errors in code. ControlFlag is open-source now, and has been covered by several news outlets such as Communications of ACM, Venturebeat, ZDNet, TechRepublic, etc.
Prior to joining Intel, I was a PhD student at Secure Systems Lab at Stony Brook University, and I was advised by Prof. R. Sekar. At Stony Brook, I conducted research in program analysis, symbolic execution, machine learning techniques to learn code translators, and binary analysis.
(Complete list is in Google Scholar)
Quantifying OpenMP: Statistical Insights into Usage and Adoption [pdf]
Tal Kadosh, Niranjan Hasabnis, Timothy Mattson, Yuval Pinter, Gal Oren
In 27th IEEE High Performance Extreme Computing (HPEC), 2023
Advising OpenMP Parallelization via a Graph-Based Approach with Transformers [pdf]
Tal Kadosh, Nadav Schneider, Niranjan Hasabnis, Timothy Mattson, Yuval Pinter, Gal Oren
In 19th International Workshop on OpenMP (IWOMP), 2023
MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformers [pdf]
Nadav Schneider, Tal Kadosh, Niranjan Hasabnis, Timothy Mattson, Yuval Pinter, Gal Oren
In AI4Dev workshop (AI4Dev) at SuperComputing, 2023
CWD: A Machine Learning based Approach to Detect Unknown Cloud Workloads [pdf]
Mohammad Hossain, Derssie Mebratu, Niranjan Hasabnis, Jun Jin, Gaurav Chaudhary, Noah Shen
In The MLSys Workshop on Cloud Intelligence (AIOps), 2022
Are Machine Programming Systems using Right Source Code Measures to select Code Repositories [pdf], [video]
Niranjan Hasabnis
In MaLTeSQuE 2022 workshop to be held with ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC-FSE), November 2022
GitRank: A Framework to Rank GitHub Repositories [pdf], [video], [git]
Niranjan Hasabnis
In Mining Software Repositories (MSR), 2022
ControlFlag: A Self-supervised Idiosyncratic Pattern Detection System for Software Control Structures [pdf]
Niranjan Hasabnis and Justin Gottschlich
In the 5th Annual Symposium on Machine Programming (MAPS), 2021
Automatic Tuning of Tensorflow’s CPU Backend Using Gradient-Free Optimization Algorithms [pdf]
Derssie Mebratu, Niranjan Hasabnis, Pietro Mercati, Gaurit Sharma, Shamima Najnin
In Machine Learning on HPC Systems (MLHPCS-ISC), 2021
Distributed MLPerf ResNet50 Training on Intel Xeon Architectures with TensorFlow [pdf]
Wei Wang and Niranjan Hasabnis
In the International Conference on High Performance Computing in Asia-Pacific Region, 2021
ControlFlag: A Self-supervised Idiosyncratic Pattern Detection System for Software Control Structures [pdf]
Niranjan Hasabnis and Justin Gottschlich
In Workshop on ML for Systems at NeurIPS, 2020
Auto-tuning TensorFlow’s Threading Model for CPU Backend [pdf]
Niranjan Hasabnis
In IEEE/ACM Machine Learning in HPC Environments (MLHPC), 2018
Accelerating TensorFlow on Modern Intel Architectures
Niranjan Hasabnis, et al.
In Workshop on Architectures for Intelligent Machines, 2017
Synthesizing Instruction-set semantics using Symbolic Execution of Code Generators [pdf]
Niranjan Hasabnis and R. Sekar.
In ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE), 2016
Lifting Assembly to Intermediate Representation: A Novel Approach Leveraging Compiler [pdf]
Niranjan Hasabnis and R. Sekar.
In ACM Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2016
[PhD Thesis] Automatic Synthesis of Instruction Set Semantics and its Applications [pdf]
Niranjan Hasabnis
Stony Brook University
Checking Correctness of Compiler Code Generators [pdf]
Niranjan Hasabnis, Rui Qiao, and R. Sekar.
In International Symposium on Code Generation and Optimization (CGO), 2015
Automatic Generation of Assembly to IR Translators Using Compilers [pdf]
Niranjan Hasabnis and R. Sekar.
In Workshop on Architectural and Microarchitectural Support for Binary Translation (AMAS-BT), 2015
A Platform for Secure Static Binary Instrumentation [pdf]
Mingwei Zheng, Rui Qiao, Niranjan Hasabnis, and R. Sekar.
In International Conference on Virtual Execution Environments (VEE), 2014
Light-weight Bounds Checking [pdf]
Niranjan Hasabnis, Ashish Misra, and R. Sekar.
In International Symposium on Code Generation and Optimization (CGO), 2012