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👋 Hi there, I am Rahul.

I work in the intersection of Machine Learning and Programming Languages for modernizing legacy applications and mainitaining cloud-native applications. Prior to this, I was Post doctoral fellow at Columbia University working ARiSE Lab with Dr. Baishakhi Ray (see rayb.info) 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 form RAISE Lab at NC State University under the guidance of Dr. Tim Menzies (see menzies.us). During my PhD, I worked on actionable analytics for software engineering. I developed algorithms that go beyond prediction to generate insights that can assist decision making. I also worked on developing data mining techniques (transfer learning) to generate insights even when sufficient data is not available. For more details, see:

Rahul Krishna's Projects

101 icon 101

intro example of combing data miners with optimizers

aici icon aici

AICI: Prompts as (Wasm) Programs

al-folio icon al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

appdocs icon appdocs

Application Performance Optimization Summary

bellwether icon bellwether

Simpler Transfer Learning (Using "Bellwethers"). ARXIV link: https://arxiv.org/abs/1703.06218

cadet icon cadet

Causal Debugging Toolkit for diagnosing and fixing non-functional faults in misconfigured systems

cause-effect icon cause-effect

Distinguishing Cause from Effect using Observational Data.

ck4py icon ck4py

Compute CK Metrics in python

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