Rahul Krishna

IBM Research (Application Modernization)


Research Scientist, IBM Research, NY.

imralk AT gmail DOT com

I work in the intersection of Machine Learning and Programming Languages for modernizing and mainitaining cloud-native applications. Prior to this, I was Post doctoral fellow at Columbia University working with Dr. Baishakhi Ray where my research explored the ways in which Machine Learning can be used to trigger, detect, and repair various problem across the software lifecycle.

I obtained my PhD at NC State University, guided by Dr. Tim Menzies. I worked on actionable analytics for software engineering. I created algorithms that go beyond prediction to provide insights that might help developers make better decisions. I focused on data mining approaches (e.g., transfer learning) that can create insights even when there isn’t enough data.


Oct 12, 2022 CARGO has been awarded 🏆ACM SIGSOFT Distinguished Paper Award🏆
Jul 20, 2022 CARGO has been acepted at ASE’22.
Feb 1, 2022 STABILIZER has been acepted at MSR’22.
Jan 24, 2022 Unicorn has been acepted at EuroSys’22.
Nov 15, 2021 A tutorial on refactoring application to microservices with mono2micro was presented in ASE.

selected publications

  1. ASE
    CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture
    🏆 ACM SIGSOFT Distinguished Paper
    Nitin, Vikram, Asthana, Shubhi, Ray, Baishakhi, and Krishna, Rahul
    In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE ’22), October 10–14, 2022, Rochester, MI, USA. 2022
  2. EuroSys
    Unicorn: Reasoning about Configurable System Performance through the lens of Causality
    Iqbal, Md Shahriar,  Krishna, Rahul, Javidian, Mohammad Ali, Ray, Baishakhi, and Jamshidi, Pooyan
    In The European Conference on Computer Systems (EuroSys). 2022
  3. TSE
    Deep learning based vulnerability detection: Are we there yet?
    Chakraborty, Saikat,  Krishna, Rahul, Ding, Yangruibo, and Ray, Baishakhi
    IEEE Transactions on Software Engineering. 2021
  4. FSE
    MTFuzz: Fuzzing with a Multi-Task Neural Network
    She, Dongdong,  Krishna, Rahul, Yan, Lu, Jana, Suman, and Ray, Baishakhi
    In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ECSE/FSE). 2020
  5. TSE
    ConEx: Efficient exploration of big-data system configurations for better performance
    Krishna, Rahul, Tang, Chong, Sullivan, Kevin, and Ray, Baishakhi
    IEEE Transactions on Software Engineering 2020
  6. TSE
    Whence to learn? transferring knowledge in configurable systems using beetle
    Krishna, Rahul, Nair, Vivek, Jamshidi, Pooyan, and Menzies, Tim
    IEEE Transactions on Software Engineering 2020