Conference Papers (last updated July 2026)

Verifying Alignment Constraints Under Finite-Sample Uncertainty with Inferred Data

B. Metevier, M. Springer, B. Turbal

ACM EAAMO 2026


Greedy Coordinate Diffusion: Effective and Semantically Coherent Adversarial Attacks via Diffusion Guidance

B. Turbal, M. Springer, B. Metevier, A. Korolova

ICML 2026


Bi-Criteria Metric Distortion

I. Gholami, M. Springer, K. Banihashem, S.C. Jahan, M. Mahdavi, D. Chakraborty, M.T. Hajiaghayi

ICLR 2026


Greedy Coordinate Diffusion: Effective and Semantically Coherent Adversarial Attacks via Diffusion Guidance

J. Castleman, M. Springer, B. Metevier, Z. Shen, A. Korolova

IASEAI 2026


Fairness and Efficiency in Online Class Matching

S.C. Jahan, M.T. Hajiaghayi, M. Sharifi, S. Shin, M. Springer

NeurIPS 2024


Dynamic Metric Embedding into lp Space

K. Banihashem, M.T. Hajiaghayi, D.R. Kowalski, J. Olkowski, M. Springer

ICML 2024


Almost Envy-Free Allocations of Goods or Chores with Entitlements

M.T. Hajiaghayi, M. Springer, H. Yami

AAAI 2024

Fair Polylog Approximate Low-Cost Hierarchical Clustering

J.P. Dickerson, M.T. Hajiaghayi, M. Knittel, M. Springer

NeurIPS 2023


An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits

K. Banihashem, M.T. Hajiaghayi, S. Shin, M. Springer

NeurIPS 2023


Generalized Reductions: Making any Hierarchical Clustering Fair and Balance with Low Cost

J.P. Dickerson, M.T. Hajiaghayi, M. Knittel, M. Springer

ICML 2023


Analysis of a Learning Based Algorithm for Budget Pacing

M.T. Hajiaghayi, M. Springer

AAMAS 2023


Optimal Sparse Recovery with Decision Stumps

K. Banihashem, M.T. Hajiaghayi, M. Springer

AAAI 2023

Online Algorithms for the Santa Claus Problem

M.T. Hajiaghayi, M.R. Khani, D. Panigrahi, M. Springer

NeurIPS 2022


Workshop Papers:

Towards Statistical Verification of Fairness in Agentic Alignment 

B. Metevier, M. Springer, B. Turbal, A. Korolova

ICLR 2026 - Workshop on Algorithmic Fairness Across Alignment Procedures and Agentic Systems

Less is More: Adaptive Coverage for Synthetic Training Data

M. Springer, S. Tavakkol, L. Chen, A. Schantz, B. Bratanič, V. Cohen-Addad, M.H. Bateni

ICLR 2026 - Workshop on Navigating and Addressing Data Problems for Foundation Models

SYNAPSE-G: Bridging Large Language Models and Graph Learning for Rare Event Classification

S. Tavakkol, L. Chen, M. Springer, A. Schantz, B. Bratanič, V. Cohen-Addad, M.H. Bateni

ICLR 2026 - Workshop on Navigating and Addressing Data Problems for Foundation Models

Positive Mining from LLM Seeds: A Semi-Supervised Graph Based Approach to Train Rare Events Classifiers

S. Tavakkol, L. Chen, M. Springer, A. Schantz, B. Bratanič, V. Cohen-Addad, M.H. Bateni

KDD 2025 - Machine Learning on Graphs in the Era of Generative Artificial Intelligence


Journal Papers:

A Mathematical Model-Derived Disposition Index without Insulin Validated in Youth with Obesity

J. Ha, J. Kim, M. Springer, A. Chhabra, S. Chung, A. Sumner, A. Sherman, S. Arslanian

The Journal of Clinical Endocrinology & Metabolism

Estimating Insulin Sensitivity and Beta-Cell Function from the Oral Glucose Tolerance Test: Validation of a New Insulin Sensitivity and Secretion (ISS) Model

J. Ha, S. Chung, M. Springer, J. Kim, P. Chen, A. Chhabra, M. Cree, C. Behn, A. Sumner, S. Arslanian, A. Sherman

American Journal of Physiology--Endocrinology, and Metabolism

A Machine-Learning Approach for Predicting Impaired Consciousness in Absence Epilepsy

M. Springer, A. Khalaf, P. Vincent, J.H. Ryu, Y. Abukhadra, S. Beniczky, T. Glauser, H. Krestel, H. Blumenfeld

Annals of Clinical and Translational Neurology

The Pulse: Transient fMRI Signal Increases in Subcortical Arousal Systems During Transitions in Attention

R. Li, J.H. Ryu, P. Vincent, M. Springer, D. Kluger, E. A. Levinsohn, Y. Chen, H. Chen, H. Blumenfeld

NeuroImage


Invited Talks:

Pulling Back the Curtain on the Voting Booth

DEF CON 34 - Voting Village, August 2026

Fair Polylog Approximate Low-Cost Hierarchical Clustering

Northwestern Junior Theorists Workshop, December 2024

Distorting the Vote: How Metric Spaces Shape Elections

UMD JAMS Seminar, November 2024

Online Class Fair Matching

Max Planck Institute for Informatics - Algorithms and Complexity Seminar, October 2024



Invited Workshops / Seminars:

Diffusion Generative Modeling: Progress and Next Steps

Simons Institute for the Theory of Computing, Summer 2026

Algorithmic Foundations for Emerging Computing Technologies

Simons Institute for the Theory of Computing, Fall 2025

AI Policy Summer School

Brown University - Center for Technological Responsibility, Reimagination & Redesign, July 2025

Ranked Choice Voting Modeling Workshop

Cornell University - Data & Democracy Lab, June 2025

Seminar on Fair Division: Algorithms, Solution Concepts and Applications

Dagstuhl Seminar 24401, September 2024


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Awards & Honors: