image of myself

Natarajan Chidambaram

I am a PhD student and researcher at the Department of Computer Science at University of Mons (UMONS), Belgium.

LinkedIn | Twitter | Google Scholar | GitHub | Email: natarajan.chidambaram@umons.ac.be

About Me

I am a PhD student and researcher at the Department of Computer Science at University of Mons (UMONS), Belgium. Also, a part of DigitalWallonia4.ai and TRAIL Factory.

My research is focussed on Detecting development bots in GitHub based on their activity sequences. I depend on machine learning techniques to develop a model that detects bot accounts in GitHub and develop a CLI tool that researchers and practitioners can use in practice. In TRAIL, my research lies in Active Learning, semi supervised learning and Stable diffusion with ControlNet. My other interests span over Reinforcement Learning, Data analysis, Data science and mining software repositories. Prior to my current position, I received a Master's degree in Data Science from the Eindhoven University of Technology, The Netherlands.

Publications

    2024
  1. Mohamed Benkedadra, Dany Rimez, Tiffanie Godelaine, Natarajan Chidambaram, Hamed Razavi Khosroshahi, Horacio Tellez, Matei Mancas, Benoit Macq, Sidi Ahmed Mahmoudi, CIA: Controllable Image Augmentation Framework based on Stable Diffusion, International Conference on Multimedia Information Processing and Retrieval (MIPR), 2024. PDF, Framework
  2. Natarajan Chidambaram, Tom Mens, Alexandre Decan, RABBIT: A tool for identifying bot accounts based on their recent GitHub event history, 21th International Conference on Mining Software Repositories (MSR) Data and Tools Showcase Track, 2024. PDF, Tool repository, Slide
    3. 2023
  3. Natarajan Chidambaram, Alexandre Decan, Tom Mens, Distinguishing Bot From Human Developers Based on Their GitHub Activity Types, Seminar on Advanced Techniques & Tools for Software Evolution (SATToSE), 2023. PDF, Slide
  4. Natarajan Chidambaram, Alexandre Decan, Tom Mens, A Dataset of Bot and Human Activities in GitHub, 20th International Conference on Mining Software Repositories (MSR) Data and Tools Showcase Track, 2023. PDF, Slide, Dataset
  5. Laura Gálvez Jiménez, Lucile Dierckx, Maxime Amodei, Hamed Razavi Khosroshahi, Natarajan Chidambaram, Anh-Thu Phan Ho, Alberto Franzin, Computational Evaluation of the Combination of Semi-Supervised and Active Learning for Histopathology Image Segmentation with Missing Annotations, Computer Vision for Automated Medical Diagnosis (CVAMD), IEEE/CVF International Conference on Computer Vision Workshop (ICCV) 2023. PDF
    6. 2022
  6. Mehdi Golzadeh, Tom Mens, Alexandre Decan, Eleni Constantinou and Natarajan Chidambaram, Recognizing bot activity in collaborative software development, IEEE Software, vol. 39, no. 5, pp. 56-61. PDF
  7. Natarajan Chidambaram, Pooya Rostami Mazrae, Bot Detection in GitHub Repositories, 19th International Conference on Mining Software Repositories (MSR), Hackathon, 2022. PDF, Slide, Presentation video
  8. Mehdi Golzadeh, Alexandre Decan, Natarajan Chidambaram, On the Accuracy of Bot Detection Techniques, 4th International Workshop on Bots in Software Engineering (BotSE) 2022. PDF
  9. Natarajan Chidambaram, Alexandre Decan, Mehdi Golzadeh, Leveraging Predictions From Multiple Repositories to Improve Bot Detection, 4th International Workshop on Bots in Software Engineering (BotSE) 2022. PDF, Slide
  10. Natarajan Chidambaram, Predicting the Impact of Using Bots in Collaborative Software Development, 20th International Conference on Software and System Reuse (ICSR), Doctoral Symposium, 2022. PDF, Presentation video
    11. 2018
  11. Natarajan Chidambaram, Devi Vijayan, Detection of Exudates in Diabetic Retinopathy Using SVM Classifier, International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018. PDF

Tools/Frameworks Developed

  • RABBIT: RABBIT is an Activity Based Bot Identification Tool, 2024
  • CIA: Controllable Image Augmentation Framework based on Stable Diffusion, 2024
  • HALF: Heterogeneous Active Learning Framework, 2022

News

Latest news:
  • May 2024: Our paper CIA: Controllable Image Augmentation Framework based on Stable Diffusion got accepted as a full regular paper at the IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR 2024)
  • Apr 2024: Attended and presented my recent work at the International conference on Mining Software Repositories (MSR) 2024.
  • Jan 2024: Our tool paper RABBIT: A tool for identifying bot accounts based on their recent GitHub event history has been accepted at MSR 2024 Data and Tools Showcase Track.
Past news:
  • Nov 2023: Presented on the topic A Bot Identification Model Based on Activities in GitHub Repositories at BENEVOL 2023 in Nijmegen, Netherlands.
  • Sept 2023: Attended TRAIL Summer Workshop 2023 at Nantes, France. I worked on one of the grand challenges proposed by Multitel innovation center. Topic: Identifying ControlNet models that can work with Stable Diffusion for data augmentation process.
  • Aug 2023: Our paper Computational Evaluation of the Combination of Semi-Supervised and Active Learning for Histopathology Image Segmentation with Missing Annotations was accepted for poster presentation at CVAMD 2023.
  • May 2023: Our paper Distinguishing Bot From Human Developers Based on Their GitHub Activity Types was accepted at SATToSE 2023.
  • May 2023: Gave an invited presentation at BotSE 2023 for the published paper: Recognizing bot activity in collaborative software development. I highlighted the importance of detecting bots in GitHub, the performance and limitations of existing state-of-the-art techniques. Further, I provided one of the possible solutions to address these limitations and improve bot detection in GitHub.
  • Mar 2023: Our dataset paper A Dataset of Bot and Human Activities in GitHub was accepted at MSR 2023 Data and Tools Showcase Track.
  • Sept 2022: Attended TRAIL Summer workshop 2022 at Berlin, Germany. I worked on one of the grand challenges that were proposed along with Multitel innovation center. Topic: Identifying the best Active Learning strategy for annotating histopathology images.
  • Jun 2022: Won the MSR 2022 best Hackathon Paper Award!
  • Jun 2022: Presented at the ICSR Doctoral Symposium Track, 2022 on the planned work for my PhD.
  • May 2022: Our paper Recognizing Bot Activity in Collaborative Software Development was accepted at IEEE Software Journal Special Issue, 2022.
  • Apr 2022 - Sep 2022: Publicity Chair for the 21st Belgium-Netherlands Software Evolution Workshop (BENEVOL) 2022.
  • Mar 2022: Our hackathon paper Bot Detection in GitHub Respositories was accepted at MSR Hackathon Track, 2022.
  • Feb 2022: Our paper Leveraging Predictions From Multiple Repositories to Improve Bot Detection was accepted at the International Workshop on Bots in Software Engineering (BotSE) 2022.
  • Feb 2022: Our paper On the Accuracy of Bot Detection Techniques was accepted at the International Workshop on Bots in Software Engineering (BotSE) 2022.
  • Nov 2021: Presented on the topic A Curated Dataset of Bots in GitHub Repositories at BENEVOL 2021.
  • Sept 2021: Attended TRAIL Summer Workshop 2021 at Paris, France. I worked on one of the grand challenges proposed by Sirris research organization.

Experience

Data Science & Software Engineering Researcher | Topic: Bot Detection in Collaborative Software Development Using Machine Learning
Software Engineering Lab, University of Mons, Belgium | August 2021 - present
Supervisor: Prof. Tom Mens | Co-supevisor: Prof. Souhaib Ben Taieb

Graduate course teaching assistant | Course: Software Evolution
University of Mons, Belgium | February 2024 - June 2024

Graduate course teaching assistant | Course: Software Evolution
University of Mons, Belgium | February 2023 - June 2023

Publicity chair | Workshop: 21st Belgium Netherlands Software Evolution Workshop (2022)
Univeristy of Mons, Belgium | April 2022 - September 2022

Research intern | Data Science Research team | Topic: Decision Support System for Crop Growth Using Reinforcement Learning
Signify, Eindhoven, Netherlands | March 2020 - September 2020
Supervisors: Prof. Joaquin Vanschoren and Sri Andari Husen

Research intern | Data Science Research team | Topic: Discover Patterns in Large Data Sets Generated by Real-time Locating Systems
Philips Research, Eindhoven, Netherlands | September 2019 - January 2020
Supervisors: Prof. Wouter Duivesteijn and Dr. Supriyo Chatterjea

Junior Data Scientist | Automotive Business Unit
Tata Elxsi, Trivandrum, India | July 2016 - July 2018

Education

Masters (M.Sc.) | Data Science in Engineering
Eindhoven University of Technology, Netherlands | September 2018 - September 2020

Bachelors (B.Tech) | Electronics and Communication Engineering
Amrita School of Engineering, Coimbatore, India | August 2012 - May 2016

Invited Talks & Awards

  • Invited talk: 5th International Workshop on Bots in Software Engineering (BotSE) 2022, on the topic "Recognizing bot activity in collaborative software development".Slide
  • Award: 19th International Conference on Mining Software Repositories (MSR) 2022, Best Hackathon Paper award.