Piyushi Manupriya

Publications & Pre-prints

(Online) Optimization

8 ★. Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness
P Manupriya, Himanshu, JS Nath, G Ghalme
AAMAS 2025 (CORE A*) as an Oral

7. Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
S Kale, P Manupriya, P Marion, F Bach, A Raj
Under review.

Optimal Transport & Kernels

6 ★. MMD-regularized unbalanced optimal transport
P Manupriya, JS Nath, P Jawanpuria
Transactions on Machine Learning Research, 2024
Among the 100 papers invited at ICLR 2025 (CORE A*)

5 ★. Submodular framework for structured-sparse optimal transport
P Manupriya, P Jawanpuria, KS Gurumoorthy, JS Nath, B Mishra
ICML 2024 (CORE A*)

4. Consistent optimal transport with empirical conditional measures
P Manupriya, RK Das, S Biswas, JS Nath
AISTATS 2024 (CORE A)

Statistical Learning Theory

3. On the Generalization and Robustness in Conditional Value-at-Risk
D K Mulumudi, P Manupriya, G Aminian, A Raj
Under review.

Deep Learning Interpretability

2. Neural network attributions: a causal perspective
A Chattopadhyay, P Manupriya, A Sarkar, VN Balasubramanian
ICML 2019 (CORE A*) as an Oral

1. Improving attribution methods by learning submodular functions
P Manupriya, TR Menta, JS Nath, VN Balasubramanian
AISTATS 2022 (CORE A); initial version accepted at ICML '20 workshops (XXAI - Poster, WHI - Spotlight)

Research Grants Availed

ANRF-National Post Doctoral Fellowship (NPDF) grant

50K USD Early-Stage Google PhD Fellowship in Machine Learning

Ministry of Education (MoE) PhD Fellowship

Other Grants Not Availed

2021-Fall Prime Minister's Research Fellowship (conflict with Google PhD Fellowship)

2017 IASc-INSA-NASI Summer Research Fellowship, BIBL Lab, ISI Kolkata (pre-empted following a medical condition)

Teaching Assistant Roles at IIT Hyderabad

AI5030 Probability and Stochastic Processes & CS6660 Mathematical Foundations of Data Science (Fall '24)
Role: Tutorials (theory), grading quizzes, assignments & exams
Course Instructor: Prof. P.N. Karthik

CS5590 Foundations of ML (Fall '22)
Role: Tutorials (theory & coding), grading quizzes & assignments
Course Instructor: Prof. J. Saketha Nath

CS5580 Convex Optimization Theory (Fall '21 & '23)
Role: Grading quizzes
Course Instructor: Prof. J. Saketha Nath

CS5560 Probabilistic Models for ML (Spring '21 & '22)
Role: Grading quizzes
Course Instructor: Prof. J. Saketha Nath

CS5350 Bayesian Data Analysis (Spring '24)
Role: Grading exams
Course Instructor: Prof. Srijith P.K.

CS6510 Applied ML (Fall '19 & '20)
Role: Grading quizzes & exams
Course Instructor: Prof. Vineeth N Balasubramanian

Other

Maths tutor (Dec '21 - Mar '22) for a batch of 3 Class-X students at the Aksharamaala Program.

Mentoring

Gautham Bellamkonda (IIT-H BTech CSE '24 batch)

Vanshika Mittal (IISc Predoc in Prof. Anant's lab)

G. Y. Srikrishna (IISc PhD student in Prof. Anant's lab)

Services

Reviewer for ICML '26, TMLR '26, ISIT '25, AISTATS '24

Sub-reviewer for NeurIPS '23, NeurIPS '20, ICML '20, ECCV '20, WACV '20, ICCV '19, ECML-PKDD '19

Volunteer for Women in ML (WiML) symposium at ICML '24 and for virtual conferences: NeurIPS ('20 & '21) and ICML '20

News

• Jan '26 Presented our AAMAS '25 paper as an invited (Best Paper Finalist) talk at exSPLOre '26
• Sep '25 Our proposal on optimization received the ANRF-NPDF grant
• Aug '25 Presented poster for our AAMAS '25 paper at the ICTS event
• Jul '25 Attended the BIRS-CMI Game-Theoretic Statistical Inference workshop. Grateful to Prof. Shubhada Agrawal & Prof. Aaditya Ramdas for the opportunity.
• Jun '25 Presented my PhD work on Optimal Transport at IIT Madras. Thanks to Prof. Harish Guruprasad for the kind invitation.
• Apr '25 Presented our TMLR '24 work as an invited poster at ICLR '25 in Singapore
• Mar '25 PhD Thesis, Improving Optimal Transport using Kernel Methods, released on HAL. BibTeX.
• Mar '25 Defended my thesis (slides)
• Mar '25 Started postdoc research in Prof. Anant's lab
• Feb '25 Presented our ICML '24 work as an invited poster at ACM ARCS '25
• Dec '24 Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness (link) got accepted at AAMAS '25 (CORE A*) as an Oral
• Dec '24 Submitted my PhD thesis and gave the open colloquium at IIT Hyderabad
• Nov '24 My exploratory observations on fairness in matchings will be presented as an extended abstract at AFME, NeurIPS '24 workshop.
• Jul '24 Presented our ICML '24 work at the conference in Vienna, Austria
• May '24 Submodular Framework for Structured-Sparse OT (link) got accepted at ICML '24 (CORE A*)
• Jan '24 Consistent OT with Empirical Conditional Measures (link) got accepted at AISTATS '24 (CORE A)
• Dec '23 MMD-Regularized OT (link) got accepted at TMLR Journal
• Sep '23 Attended the global Google PhD Fellowship summit (online)
• Jan '23 Attended the Research Week with Google
• Jul '22 Attended the global Google PhD Fellowship summit (online)
• Mar '22 Presented our AISTATS '22 work at the virtual conference
• Jan '22 My M.Tech project on ensembling saliency maps using submodular functions (link) got accepted at AISTATS '22 (CORE A).
• Oct '21 Got selected for the PMRF Fellowship (courteously declined for Google's)
• Sep '21 Received the early-stage Google PhD Fellowship in Machine Learning
• Aug '21 Cleared the Comprehensive exam. Chosen seminar paper: Scaling Algorithms for Unbalanced Optimal Transport Problems (Chizat et al., 2017)
• Aug '20 Converted from MTech-Research to PhD at IIT Hyderabad
• Jul '20 Presented Submodular Ensembled Attribution, accepted at ICML Workshops (XXAI - Poster; WHI - Spotlight), at the virtual conference
• May '19 Neural Network Attributions: a Causal Perspective (link) got accepted at ICML '19 (CORE A*) as an Oral