Sankarshan Damle

I am a post-doctoral researcher at the Artificial Intelligence Laboratory (LIA), EPFL, under Prof. Boi Faltings.

Before that, I did my Ph.D. in Computer Science at Machine Learning Lab, IIIT Hyderabad, under Dr. Sujit Gujar. My Ph.D. was fully funded through the Ripple-IIITH Fellowship. I completed my Bachelor of Technology (w/ Honors) in Computer Science, also at IIIT Hyderabad.

My research focuses on designing fair, private, and strategy-proof mechanisms for multi-agent systems, combining insights from machine learning, game theory, and privacy. I have collaborated with researchers from premier institutions such as IIIT Hyderabad, EPFL, and HKUST, as well as industry labs including Microsoft Research India and Samsung Research India, working on real-world applications that require trustworthy and robust AI solutions.

Google Scholar · DBLP · CV

Other Roles

• Microsoft Research India, Intern with Dr. Navin Goyal (Mar–Aug 2024)
• Microsoft Research India, Intern with Dr. Satya Lokam (Apr–Nov 2023)
• TalentSprint, Chief Mentor (Apr 2022–Mar 2023)
• Samsung Research India, Student Trainee (May–Jul 2021)
• EPFL LIA, Visiting Researcher (Mar–Jul 2020)
• HKUST Cybersecurity Lab, Visiting Researcher (Jul–Oct 2019)

News

• [July '25] LLMs for Resource Allocation accepted at ECAI
• [June '25] Adversarial FL work accepted at CFAgentic @ ICML
• [Dec '24] Guest lecture at EPFL on transaction fee mechanisms
• [Oct '24] NeurIPS Workshop papers with MSR India!
• [Oct '24] Started Postdoc at EPFL LIA
• [July '24] Fair Transaction Fees to appear at ECAI
• [Apr '24] AVeCQ accepted at IEEE TDSC
• [Mar '24] Joined MSR India, Bangalore
• [Jan '24] Private Multi-agent Optimization accepted at JAAMAS
• [Dec '23] Three papers accepted at AAMAS'24

Publications

*: Equal contribution

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Talks

• Tutorial on Fair and Private Deep Learning
  With Manisha Padala and Sujit Gujar, at ACM CODS-COMAD 2024
  Tutorial Material
• Guest Lecture: Transaction Fee Mechanism Design
  Part of "Intelligent Systems" course @ EPFL (Fall 2024)
  Slides
• Guest Lecture: Intro to Differential Privacy
  Part of "Ethics & Fairness in AI" course @ IIIT-H (2022 & 2023)
  Slides

Ph.D. Dissertation

Title: Designing Game-theoretically Sound, Fair, and Private Multi-agent Systems [PDF]

🏅 Nominated for:
• ACM India Doctoral Dissertation Award 2024
• IKDD Doctoral Dissertation Award 2024

Professional Services

PC Member: WI-IAT, ECAI, IJCAI, IJCAI (AI4G), AAAI, AAMAS, BLOCKCHAIN, GAIW@AAMAS, PPAI@AAAI

Reviewer: ICONIP, IEEE TMC, IJPR, JAIR, NeuroAI@NeurIPS, ContinualFoMo@NeurIPS, LLMReasoning@ICLR

Volunteer: IJCAI 2019, CODS-COMAD 2020, ACML 2022, OAML 2022

Contact

Email: sankarshandamle [at] gmail.com

LinkedIn: linkedin.com/in/sankarshandamle