hartline-jasonJason Hartline.  Prof. Hartline’s research introduces design and analysis methodologies from computer science to understand and improve outcomes of economic systems. Optimal behaviour and outcomes in complex environments are complex and, therefore, should not be expected; instead, the theory of approximation can show that simple and natural behaviours are approximately optimal in complex environments. This approach is applied to auction theory and mechanism design in his graduate textbook Mechanism Design and Approximation which is under preparation.

 

aravind_headshotAravindan Vijayaraghavan. Prof. Vijayaraghavan’s research interests are broadly on the algorithmic foundations of problems in machine learning, data science,  combinatorial optimization, and more recently, in quantum information. His research often uses paradigms that go beyond worst-case analysis like smoothed analysis, average-case analysis and instance stability to obtain much better algorithmic guarantees than we can obtain in the worst-case.

 

kostya-ph25Konstantin Makarychev. Prof. Makarychev is a Professor of Computer Science at Northwestern University. He is interested in designing efficient algorithms for computationally hard problems, and introducing new core techniques and design general principles for developing and analyzing algorithms that work in theory and practice. His research interests include approximation algorithms, beyond worst-case analysis, theory of machine learning, and applications of high-dimensional geometry in computer science.

 

Samir Khuller. Prof. Khuller is a Professor of Computer Science and the Peter and Adrienne Barris Chair of Computer Science at Northwestern University. He is an expert in graph algorithms, discrete optimization, and scheduling, and has published nearly 200 journal and conference papers, as well as several book chapters. He was named a 2022 Association for Computing Machinery (ACM) Fellow “for contributions to algorithm design with real-world implications and for mentoring and community-building” and also a 2021 European Association for Theoretical Computer Science (EATCS) Fellow “for his fundamental contributions to combinatorial approximation algorithms“.

 

wang-xiaoXiao Wang. Prof. Wang is an Assistant Professor of Computer Science at Northwestern University. His research interests include computer security, privacy, and cryptography. Recently, he is mainly working on practical multi-party computation, zero-knowledge proofs, oblivious RAM, and post-quantum cryptography. He likes building real systems based on advanced cryptographic techniques and pushing their limits of practicality.

 

golub-ben
Ben Golub.  Prof. Golub is a Professor of Economics and (by courtesy) Computer Science. His research focuses on the theory of social and economic networks, including the dynamics of learning and influence, targeting interventions for behavior change, and systemic risk and fragility in financial and production systems. He is interested in methods from probability theory, including random graphs and percolation, as well as the foundations and statistics of network centrality measures. He has served as an Associate Editor of Theoretical Economics and the Journal of Economic Theory.

 

Annie Liang. Prof. Liang is the Assistant Professor of Economics and (by courtesy) Computer Science. Her work focuses on economic theory and the application of machine learning techniques in the social sciences. She has studied the dynamics of strategic information acquisition, as well as the use of machine learning to evaluate and improve economic models.

 

Miklos Z. Racz. Prof. Racz is an Assistant Professor in Statistics and Data Science with a joint appointment in Computer Science. He is joining us from Princeton University, where he is an assistant professor in the ORFE department. He received his PhD in Statistics from UC Berkeley and was then a postdoc in the Theory Group at Microsoft Research, Redmond. Miki’s research interests lie broadly at the interface of probability, statistics, computer science, and information theory. Miki’s research and teaching has been recognized by Princeton’s Howard B. Wentz, Jr. Junior Faculty Award, a Princeton SEAS Innovation Award, and an Excellence in Teaching Award.

 

Edith Elkind is a GinnyEdith Elkind Rometty Professor of Computer Science. She is interested in algorithms for collective decision making, including cooperative games, voting (in particular multiwinner voting and participatory budgeting) and fair division, as well as their applications to the foundations of AI. She is the recipient of the 2023 ACM SIGAI Autonomous Agents Research Award and a Fellow of the European Association for Artificial Intelligence.

 

Dmitrii (Dima) Pasechnik is a Research Professor of Computer Science. He is interested in mathematical foundations of computer algebra and symbolic computing, in implementation of software for pure and applied mathematics, and computer-aided verification of mathematics. On his more mathematical side he works in real algebraic geometry, group theory, sums of squares techniques in nonlinear optimization and approximation algorithms, and combinatorics. He is a member of the editorial board of Journal of Software for Algebra and Geometry, and active contributor to SageMath and GAP computer algebra systems.
Sidhanth Mohanty‘s research interests lie broadly in probability theory and theoretical computer science.  Specifically, he is interested in analyzing mixing times of Markov chains, high-dimensional expansion, random matrix theory, and error-correcting codes.

Postdoctoral Researchers

Dmitrii Avdiukhin

Dmitrii Avdiukhin. Dmitrii joined the Theory group in September 2023, after receiving a Ph.D. from Indiana University, advised by Grigory Yaroslavtsev. He is broadly interested in approximation algorithms, learning theory, and theoretical foundations of machine learning, in particular continuous optimization, generalization, and hierarchical clustering.

 

Suprovat Ghoshal. Dr. Ghoshal’s primary research interests are in Hardness of Approximation and Computational Learning Theory. He is also interested in Error Correcting Codes, Combinatorics and Geometry. Prior to joining Northwestern, he was a research associate at U.Mich hosted by Euiwoong Lee. He received his Ph.D. from the Indian Institute of Science, Bangalore, advised by Arnab Bhattacharyya and Siddharth Barman.

Dravyansh (Dravy) Sharma is an IDEAL postdoctoral researcher, hosted by Avrim Blum at TTIC and Aravindan Vijayaraghavan at Northwestern University. He obtained his PhD at Carnegie Mellon University, advised by Nina Balcan. His research interests include machine learning theory and algorithms, with a focus on provable hyperparameter tuning, adversarial robustness, and learning in the presence of rational agents. His work develops principled techniques for tuning fundamental machine learning algorithms to domain-specific data, including decision trees, linear regression, graph-based learning and, most recently, deep networks. He has published several papers at top ML venues, including NeurIPS, ICML, COLT, JMLR, AISTATS, UAI and AAAI, has multiple papers awarded with Oral presentations, won the Outstanding Student Paper Award at UAI 2024, and has interned with Google Research and Microsoft Research.

Affiliated Faculty

Visiting Faculty

Varun Gupta is a visiting associate professor at Northwestern University. His research interest includes stochastic processes, applied probability, and mechanism design.

RajniRajni Dabas is a visiting faculty at Northwestern University and an Assistant Professor at P.G.D.A.V. College, University of Delhi. She did her Ph.D. from the University of Delhi under the supervision of Prof. Neelima Gupta. Her research focuses on theoretical computer science,with particular interest in approximation algorithms and combinatorial optimization. She has worked on constrained clustering problems such as Facility Location and k-Median, especially with capacity and outlier constraints. Currently, she is working on fairness in clustering algorithms.

Professor Emeritus

Past Members

  • Lance Fortnow, Professor, 2008 –  2012, now Dean of the College of Computing at Illinois Institute of Technology
  • Nicole Immorlica, Assistant Prof., 2008-2013, now Senior Principal Researcher at Microsoft Research New England
  • Azarakhsh Malekian Postdoc, 2010-2011, now Associate Prof. at University of Toronto, Rotman
  • Anindya De, Assistant Prof., 2015-2018, Adjunct Assistant Prof., 2019-2021, now Associate Prof. at University of Pennsylvania
  • Huck Bennett, Postdoc, 2017-2019, now Assistant Prof. at CU Boulder
  • Xue Chen, Postdoc, 2018-2020, now Assistant Prof. at University of Science and Technology of China
  • Hedyeh Beyhaghi, Postdoc, 2019-2021, now Assistant Prof. at University of Massachusetts Amherst
  • Shravas Rao, Postdoc, 2019-2022, now Assistant Prof. at Portland State University
  • Jinshuo Dong, Postdoc, 2020-2024, now Yau Mathematical Sciences Center, Tsinghua University
  • Sheng Yang, Postdoc, 2021-2022, now Huawei
  • Vaggos Chatziafratis, Postdoc, Fall 2021, now Assistant Prof. at UC Santa Cruz
  • Sami Davies, Postdoc, now Research Scientist at Simons Institute and Berkeley
  • Quanquan C. Liu. Postdoc, now Assistant Prof. at Yale University
  • Eric Evert. Postdoc, now Assistant Prof. at University of Florida
  • Don Stull. Postdoc, now Dickson Instructor in the Department of Mathematics at the University of Chicago