ARC supports competitive research projects put forth by graduate students.

Details of the fellowships awarded, listing student, semester, title, and advisor.
Student(s) Semester Awarded Fellowship Title Advisor(s)sort descending
Qie He, ISyE 2010 Fall A Polyhedral Study of Stochastic Integer Programming Shabbir Ahmed and George Nemhauser, ISyE
Zhehui Chen (ISyE) 2018 Spring Online Generalized Eigenvalue Decomposition: Min-max Formulation, Primal Dual Landscape and Efficient Optimization Tuo Zhao (ISyE)
Ravi S. Ganti CS 2010 Spring Design and Analysis of Local Kernel Machines Alexander G. Gray, CSE
Tianxin Tang (CS PhD, CS), ARC-IISP Fellowship 2016 Fall Keyless Fuzzy Search on Encrypted Data Alexandra Boldyreva
David Cash, CS 2009 Spring Circular-Secure Encryption from Learning Problems Alexandra Boldyreva, CS
Jing Yu (ACO) 2022 Spring Fast Distributed Algorithm Conjecture for Lovasz Local Lemma Anton Bernshteyn (Math)
Vinod Cheriyan, ISyE 2010 Fall A Model of Asset Price Bubbles that Shows Chaotic Dynamics Anton J. Kleywegt, ISyE and Federico Bonetto, Math
Rui Gao (ISyE) 2018 Spring Wasserstein Distributional Robustness and Generalization Anton Kleywegt (ISyE)
Robert Krone (Math) 2014 Spring Algorithms for Equivariant Ideals and Varieties Anton Leykin
Timothy Duff (ACO Math) 2020 Spring Challenges in Computational Algebraic Vision Anton Leykin (Math)
Cristóbal Guzmán, ISyE 2013 Spring A New Model for Image Regularization Arkadi Nemirovski, ISyE
Sara Krehbiel (CS) 2014 Spring Paying for Privacy Chris Peikert
Abhishek Banerjee, CS 2011 Spring Efficient Cryptographic Pseudorandom Generators Chris Peikert, CS
Sara Krehbiel, ACO/CS 2011 Fall Threshold Lattice Cryptography Chris Peikert, CS
George Kerchev (Math) 2018 Spring Asymptotic behavior of the length of the longest common subsequence in hidden Markov models Christian Houdre (Math)
Sarah Miracle (CS) 2014 Spring Markov Chains to Model Segregation and Biased Surfaces Dana Randall
Prateek Bhakta (ACO PhD, CS) 2011 Fall Markov Chain Convergence in Discrete and Continuous Spaces Dana Randall
Prateek Bhakta (ACO PhD, CS) 2012 Fall Mixing Times of the Schelling Segretation Model and Biased Permutations Dana Randall
Zhanzhan Zhao (CS) 2021 Spring Mitigating Residential Segregation Through Urban Infrastructure Dana Randall (CS)
Amanda Pascoe 2009 Fall Cluster Algorithms for Discrete Models of Colloids Dana Randall, CS
Daan Rutten (ISyE) 2021 Spring Improving Capacity Scaling With Machine Learning Predictions Debankur Mukherjee (ISyE)
Di Wu (OR PhD, ISyE) 2017 Spring Computing Budget Allocation Under Input Uncertainty Enlu Zhou
Tianyi Liu (OR, ISyE) 2019 Spring Online Risk Quantification of Input Uncertainty Enlu Zhou (ISyE)
Andreas Galanis (CS) 2014 Spring Hardness of Approximately Counting Colorings Eric Vigoda
Zongchen Chen (ACO, CS) 2019 Spring Distribution Testing for Markov Random Fields Eric Vigoda (CS)
Linji Yang, CS 2011 Spring Analysis of the Hard-core Model on Square Lattices Beyond the Tree Uniqueness Threshold Eric Vigoda, CS
Mohamed El Tonbari (OR, ISyE) 2020 Spring On Two-Stage Distributionally Robust Optimization with Binary Variables. George Nemhauser(ISyE) and Alejandro Toriello (ISyE)
Kevin Shu (ACO Math) 2023 Spring Sparsity and Randomness in Optimization Greg Blekherman (Math)
Shengding Sun (ACO Math) 2020 Spring Sparse positive semidefinite relaxations with S^{n,k}. Greg Blekherman (Math) and Santanu Dey (ISyE)
Da Kuang, CSE 2010 Spring Matrix Factorization for Clustering: NMF and Beyond Haesun Park, CSE
Adrian Rivera Cardoso (ISyE) 2018 Spring Online Risk Averse Minimization with Bandit Feedback Huan Xu (ISyE)
Jun-Kun Wang (CS) 2018 Spring Online Frank-Wolfe and its Application in Herding Jacob Abernethy (CS)
Marcel Celaya (ACO PhD, Math) 2017 Spring An Algorithmic Approach to the Gohberg-Markus-Hadwiger Conjecture Josephine Yu
Shen Zhang (ML) 2022 Spring Toward optimal multi-agent reinforcement learning: From consensus to policy evaluation Justin Romberg (ECE), Ashwin Pananjady (ISyE/ECE)
Bo Xie (CSE) 2015 Fall Convergence of Non-Convex Optimization in Deep Learning Le Song
He Guo (Math) 2018 Spring Semi-Random Algorithmic Constructions Lutz Warnke (Math)
Andrew Massimino (ECE) 2014 Spring Constrained Adaptive Sensing Mark Davenport
Andrew McRae (ECE) 2020 Spring Exploiting low-dimensional manifold structure with kernel methods. Mark Davenport (ECE)
Spencer Backman (Math) 2014 Spring A Complex Valued Hypergraph Laplachain Matt Baker
Farbod Shokrieh, Math 2012 Fall Random Basis Algorithm for Regular Matroids Matt Baker, Math
Farbod Shokrieh, Math/ECE 2010 Fall A Torelli Theorem and a New Set of Invariants for Graphs Matt Baker, Math
Gagan Goel, CS 2009 Spring Efficient Allocations when the Agents have Submodular Utility/Cost Function Milena Mihail and Vijay Vazirani
Uthaipon Tantipongpipat (CS) 2018 Spring Design and Analysis of Approximation Algorithms for Optimal Design Mohit Singh (ISyE)
Adam Brown (Math ACO) 2022 Spring Diverse Subset Selection Mohit Singh (ISyE)
Sebastian Perez-Salazar (ACO, ISyE) 2019 Spring Dynamic allocation in the Cloud with Near-Optimal Efficiency Mohit Singh (ISyE) and Alejandro Toriello (ISyE)
Luyi Gui, ISyE 2009 Fall Collaboration Mechanism Design under Data Uncertainty in Multicommodity Flow Networks Ozlem Ergun
Ning Tan, ACO/Math 2011 Fall Constraint Satisfaction Problems with Global Constraints Prasad Raghavendra, CS
Emma Cohen (Math) 2015 Fall Mixing with Monotone Censoring Prasad Tetali
Ricardo Restrepo, Math 2009 Spring Reconstruction in Random Factor Graphs Prasad Tetali (GT Math) and Andrea Montanari (Stanford)
Ioannis Pannageas 2014 Fall Replicator dynamics, Equilibria and Diversity in Evolution Prasad Tetali (Math)
Ricardo Restrepo, Math 2011 Spring Spatial Mixing: Refinements and Applications Prasad Tetali, CS/Math
Ricardo Restrepo, Math 2010 Spring Convergence of Local Interactions in Catalan Structures Prasad Tetali, CS/Math
Arindam Khan 2012 Fall Algorithms for 3-D Geometric Bin Packing Prasad Tetali, CS/Math and Henrik I. Christensen, IC
Yuliia Lut (ISyE) 2020 Spring Improving accuracy for dynamic differential privacy with change-point detection. Rachel Cummings (ISyE)
Jiaming Liang (ISyE) 2020 Spring First-Order Methods for Nonconvex Smooth Composite Optimization Problems Renato Monteiro (ISyE)
Camilo Ortiz, ISyE 2011 Fall Implementation of Fast First-Order Methods for Solving Large-Scale Convex Optimization Problem Renato Monteiro, ISyE
Atish Das Sarma, CS 2009 Spring Efficient Approaches for Random Walks Richard J. Lipton, CS
Atish Das Sarma, CS 2009 Fall Walk Fast Distributively and Learn Despite Byzantine Failures Richard J. Lipton, CS
David Durfee (ACO PhD, CS) 2016 Fall Vertex Elimination Techniques and their Applications to Graph Algorithms Richard Peng
Chun-Hung Liu and Peter Whalen, Math 2011 Fall Tiny Robots: A Resource Allocation Problem Robin Thomas, Math
Chun-Hung Liu, Math 2013 Spring Well-quasi-ordering Graphs by the Immersion Relation Robin Thomas, Math
Youngho Yoo (ACO, Math) 2019 Spring Packing zero A-paths in undirected group labelled graphs Robin Thomas (Math)
atharth Dubey (ISyE) 2021 Spring On the Success of Strong Branching Santanu Dey (ISyE)
Burak Kocuk (ISyE) 2014 Fall A Polyhedral Study of DC Transmission Switching Problem Santanu Dey and Andy Sun (ISyE)
Diego Morán, ISyE 2013 Spring On Cutting Planes for Convex Mixed-integer Programs Santanu Dey, ISyE
Kevin Lai (ACO PhD, CS) 2016 Fall Parameter Estimation for Mixtures of Gaussians with Adversarial Noise Santosh Vempala
Ben Cousins (ACO PhD, CS) 2016 Spring Theoretical and Applied Tools for High-dimensional Sampling Santosh Vempala
Samira Samadi (CS PhD) ARC-IISP Fellowship 2017 Spring Human Computation with Application to Humanly Usable and Secure Password Methods Santosh Vempala
Samantha Petti (ACO, Math) 2019 Spring Testing Geometric Convexity Santosh Vempala (CS)
Yumbum Kook (CS) 2023 Spring Further Development of High-dimensional Sampling Santosh Vempala (CS)
Xinyuan Cao (ML CS) 2023 Spring Unsupervised Learning of Halfspaces and Beyond Santosh Vempala (CS)
Aditi Laddha (ACO CS) 2020 Spring Better Approximation for Uniform Sparsest Cut Santosh Vempala (CS)
He Jia (CS) 2021 Spring Robustly Learning of Mixtures of Gaussians Santosh Vempala (CS)
Mirabel Reid (CS) 2022 Spring Graph Parameterization in the Assembly Model Santosh Vempala (CS)
Mehrdad Ghadiri (CS ACO) 2022 Spring Tall p-norm Regression in Input Sparsity Time Santosh Vempala (CS)
Daniel Dadush, ISyE 2011 Fall Towards Faster Integer Programming Santosh Vempala, CS
Karthekeyan Chandrasekaran, CS/ACO 2010 Fall The Complexity of Cutting Plane Methods for Random Integer Programs Santosh Vempala, CS
Ying Xiao, CS/ACO 2010 Fall Tensors and Random Constraint Satisfaction Problems Santosh Vempala, CS
Daniel Dadush, ISyE 2009 Fall Towards the KLS Conjecture for Convex Bodies Santosh Vempala, CS
Anand Louis, CS 2012 Fall A New Approach Towards Graph Coloring Santosh Vempala, CS and Prasad Tetali, Math
Anand Louis, CS 2011 Spring Towards a Spectral Algorithm for Small-set Expansion and Graph Multi-partitioning Santosh Vempala, Prasad Raghavendra, CS and Prasad Tetali, CS/Math
Aurko Roy (ISyE) 2014 Spring Learning a Polytope Sebastian Pokutta
Alfredo Torrico (OR PhD, ISyE) 2017 Spring Online Constrained Submodular Minimization with Bandit Feedback Sebastian Pokutta
Xie Weijun (ISyE) 2016 Spring On Distributionally Robust Joint Chance-Constrained Problems Shabbir Ahmed
Ezgi Karabulut (OR PhD, ISyE) 2016 Fall Auction Algorithms for Distributed Integer Programming Shabbir Ahmed and George Nemhauser
Gustavo Angulo (ISyE) 2014 Spring A polyhedral study of all-different polytopes Shabbir Ahmed and Santanu S. Dey
Daniela Hurtado Lange (OR, ISyE) 2019 Spring Performance analysis of scheduling algorithms in a switch Siva Theja Maguluri (ISyE)
Sajad Khodadadian (OR ISyE) 2023 Spring Sharp Analysis of Two-Time-Scale Stochastic Approximation with Applications in Reinforcement Learning Siva Theja Maguluri (ISyE)
Zaiwei Chen  (ML) 2021 Spring Unified Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms Siva Theja Maguluri (ISyE)
Jai Moondra (ACO CS) 2023 Spring Fair and interpretable combinatorial optimization using symmetric weights Swati Gupta (ISyE) and Mohit Singh (ISyE)
Hassan Mortagy (ISyE) 2021 Spring First-Order Methods for Combinatorial Structures and Machine Learning Swati Gupta (Spring 2021)
Guido Lagos (ISyE) 2014 Fall Exact Sampling of Random Walk Paths up to the Maximum Ton Dieker
Xuefeng Gao, ISyE 2011 Spring Capacity Allocation in Queueing Networks Ton Dieker
Xuefeng Gao (ISyE) 2010 Spring Capacity Allocation in Queueing Networks Ton Dieker, ISyE
Minshuo Chen (ML, ISyE) 2019 Spring On Nonconvex Stochastic Optimization of Residual Networks Tuo Zhao (ISyE)
Haoming Jiang (ML ISyE) 2020 Spring Nonparametric Regression on Low Dimensional Manifolds using Neural Networks. Tuo Zhao (ISyE)
Guanghui Wang (ML CS) 2023 Spring Adaptive and Oracle-Efficient Online Learning Vidya Muthukumar (ISyE) and Jacob Abernathy (CS)
Tung Mai (ACO PhD, CS), 2016 Fall Approximating the Non-symmetric Nash Social Welfare Vijay Vazirani
Sadra Yazdanbod (ACO PhD, CS) 2016 Spring A Market for Scheduling, with Applications to Cloud Computing Vijay Vazirani
Pushkar Tripathi, CS 2011 Fall Simple Randomized Algorithms for Assignment Problems Vijay Vazirani, CS
Stas Minsker, Math 2010 Fall Plug-in Approach to Active Learning Vladimir Koltchinskii, Math
Yongchun Li (OR ISyE) 2023 Spring On the Strength of Dantzig-Wolfe Relaxation of Rank Constrained Optimization: Exactness, Rank Bound, and Algorithm Weijun Xie (ISyE)
Yuzhou Wang (ACO Math) 2023 Spring Hardness of finding balanced independent sets in d-regular random bipartite graphs Will Perkins (CS)
Tian-Yi Zhou (ISyE OR) 2023 Spring Classification of Unbounded Data by Gaussian Mixture Models Using deep ReLU Networks Xiaoming Huo (ISyE)
Yujie Zhao (ISyE) 2020 Spring Homotopic Methods can Significantly Speed up the Computation of the Non-differential Optimization Problems. Xiaoming Huo (ISyE)
Yiling Luo (OR) 2022 Spring Towards Understanding Statistical Properties of Model Parameters in Stochastic First Order Optimization Algorithms Xiaoming Huo (ISyE)
Qunzhi Xu (OR) 2022 Spring Active Sequential Change-Point Detection Under Sampling Control Yajun Mei (ISyE)
Wanrong Zhang (IE, ISyE) 2019 Spring Online Monitoring Streaming Data Under Privacy or Resources Constraints Yajun Mei (ISyE) and Rachel Cummings (ISyE)
Liyan Xie (ISyE) 2020 Spring Distributionally Robust Nonparametric Hypothesis Testing. Yao Xie (ISyE)