Bengaluru, India
Joined February 2023
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Nirjhar Das retweeted
Using hunger strike Gandhi could force Dr Ambedkar to compromise on his people's representation, the other way round couldn't have been possible. In a caste society, life is graded, some lives are more important than others. For Dalits, hunger strike as protest method never works
🎉 Our paper accepted at ICLR 2026!
We study the backbone of applications like search, recommendation, & RAG: “Nearest Neighbor Search.”
But instead of optimizing only relevance, we ask
👉 Can we balance relevance & diversity in a principled way?
Paper: arxiv.org/abs/2602.08742
Prior work: diversity via hard constraint→not query-dependent
Our insight:
📐 View attributes (seller, color, brand) as “agents”
⚖️ Nash Social Welfare to balance relevance & diversity
Result: query-dependent solution.
“shirts” → diverse results 🌈
“blue shirt” → all blue 🔵
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Theory → Practice 📈
• Provable efficient algorithms
• Works with standard ANN systems
• Strong empirical gains in diversity while maintaining relevance in several real-world datasets
Joint work with @BarmanSiddharth, @shivi98g & @KShiragur.
See you at ICLR 2026 in Rio 🇧🇷
Nirjhar Das retweeted
Drop by our posters to talk about imperfect data and responsible AI. @stochastic_nir is seeking a PhD position this year, and I am seeking postdoctoral opportunities. (3/3)
Nirjhar Das retweeted
2. Cost-Efficient Fairness Audit Under Partial Feedback (openreview.net/pdf?id=DSIWPU…), at the Reliable ML (Sat 6 Dec 4 p.m. — 5 p.m. PST) and Regulatable ML workshop (Sun 7 Dec 8 a.m.— 5 p.m. PST). Led by @stochastic_nir , with Praharsh Nanavati, @KShiragur and Amit Deshpande.(2/3)
Nirjhar Das retweeted
There *may* be some collusion, but how prevalent is this? Maybe a few papers, maybe a hundred?
Clearly not enough to revert the whole ICLR discussion phase! Plus, organizers can closely track papers where the scores jumped drastically.
Thrilled that our paper arxiv.org/abs/2510.03734 will be presented by Amit Deshpande (MSRI) as poster @ 𝐍𝐞𝐮𝐫𝐈𝐏𝐒 𝟐𝟎𝟐𝟓 Workshop on Reliable ML from Unreliable Data! 🚀
Visit our poster on Dec 6 to know about this exciting work!
#NeurIPS2025 #FairML #ResponsibleAI
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We give:
• A realistic cost model for acquiring labels
• Near-optimal audit algorithms in black-box
• Cost-improved algo for mixture-model settings
• Empirically ~50% lower audit cost vs. natural baselines
• Extends to many fairness metrics
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Joint work with awesome collaborators @mohitsharmaj29 Praharsh Nanavati @KShiragur Amit Deshpande
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It was an awesome course! Thoroughly enriching. Please check out the course webpage for the amazing resources curated by Prof @arindamkhan and Prof @BarmanSiddharth .
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Travelling to @AshokaUniv to attend exSPLORe2025 workshop (ashoka.edu.in/event/exsplore…) from 14th to 18th January. Looking forward to learning and interacting with researchers and fellow students.
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Not to be missed... Awesome opportunity for undergrads!
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Excited to share our work got accepted as #NeurIPS2024 Spotlight!
Joint work of Ayush Sawarni, Nirjhar Das, Siddharth Barman, and Gaurav Sinha on “Generalized Linear Bandits with Limited Adaptivity” has been accepted at NeurIPS 2024: arxiv.org/abs/2404.06831
#LaapataLadies in #Oscars2025 plays into the Western gaze of India as a backward society. It's is more of an educational film than a cinematic masterpiece. Subtlety and layers are definitely missing—think #Parasite (2019). Not sure why #AllWeImagineAsLight wasn't the first choice
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Attending @ECMLPKDD 2024 in Vilnius, Lithuania to present our paper "Linear Contextual Bandits with Hybrid Payoff: Revisited".
If you're attending, would love to discuss anything cool including Learning Theory and ML Theory.
Joint work with @sinhagaur88
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Started my Masters journey @IIScCSA with an electric orientation by Profs at the dept (in the photo Prof @BarmanSiddharth) and the fabled Probability Theory class by Prof. Manjunath. Feels amazing to be a student again, that too @iiscbangalore!
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