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saikat107

saikat107

👋 About me

Hi, I am Saikat, currently a Senior Researcher at the Research in Software Engineering (RiSE) group at Microsoft Research, working towards Trusted AI for Programmers. In particular, I am researching towards building AI assisted code generator with provable correctness guarantee w.r.t. certain specification from both programming languages and user intent. Earlier, I graduated with Ph.D. in omputer Science from Columbia University in the City of New York advised by Professor Baishakhi Ray. I wrote my Ph.D. thesis on Learning to Edit Code.

👀 My Interest

I’m interested in Artificial Intelligence for Software Engineering (AI4SE). My research passion is Programming Language Processing (PLP) -- A coalescence between Software Engineering and Machine Learning. More specifically, I am motivated by building tools and techniques that reduces software engineering practitioners' burden by automating tasks they have to undergo in their everyday job. Over the years, I have been building developer assistance tools with research collaboration across Software Engineering, Machine Learning, Natural Language Processing.

👐 My Goal

😇 Learning:

  • Formal Properties of Programming Languages, Program Synthesis, Specification Mining, Verification, and Testing.

👋 Looking for Collaboration:

  • Use of Artificial Intelligence and/or Machine (Deep) Learning for software engineering tasks.
  • Use of Large Language Models for Program Synthesis/Editing

✨ Connect with me

Saikat Saikat Saikat

📢 What's new

  • 🔔 [February 2024] Release the Official code for Invariant Ranker.
  • 🔔 [December 2023] Our work on Re-ranking Loop Invariants is published in EMNLP-findings 2023.
  • 🔔 [November 2022] Presented NatGen to FSE in Singapore.
  • 🔔 [September 2022] Joined RiSE team at Microsoft Research as Senior Resercher.

Saikat Chakraborty's Projects

cleverhans icon cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

code2seq icon code2seq

Code for the model presented in the paper: "code2seq: Generating Sequences from Structured Representations of Code"

codemining-utils icon codemining-utils

Utility classes for serialization, parameter loading, sampling and math

dataset icon dataset

Code for dataset dataset for MDPVRP

defects4j icon defects4j

A Database of Real Faults and an Experimental Infrastructure to Enable Controlled Experiments in Software Engineering Research

dfa-tool icon dfa-tool

This tool can be used to create and simulate DFA.

fuzz4all icon fuzz4all

🌌️Fuzz4All: Universal Fuzzing with Large Language Models

modit icon modit

MODIT: On Multi-Modal Learning of Editing Source Code.

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