Randomness Extractors Professors and Supervisors

Tobias Gehringمشاهده پروفایل

دانشیار

Technical University of DenmarkDenmark

Tobias Gehring is an Associate Professor in the Department of Physics at the Technical University of Denmark (DTU). He is affiliated with the Quantum Physics and Information Technology research groups and actively contributes to the Center for Quantum Technologies and the Center for Macroscopic Quantum States. His contact information includes the phone number +4593511649 and the email tobias.gehring@fysik.dtu.dk. He can be reached at Fysikvej, 307, 262, 2800 Kgs. Lyngby, Denmark. His research interests encompass quantum key distribution (QKD), continuous variable systems, squeezed light applications, and high-speed quantum technologies. He investigates filter shape optimization for noise reduction in QKD, quantum metrology for gravitational wave detection, and the integration of photonic-electronic systems to advance communication networks. Tobias also explores composable security frameworks in finite-size key generation and quantum-enhanced interferometry for foundational physics experiments. Tobias Gehring's recent work trends emphasize practical implementations of quantum communication protocols and fundamental physics applications. His projects include developing real-time quantum random number generators and optimizing QKD systems for higher bandwidth and security. He collaborates on applying quantum techniques to biomolecule detection and multi-user QKD networks. As a supervisor, Tobias is involved in multiple PhD projects: Quantum Communication and Co-Existence with Classical Communication (PhD Student: F. Sirovich, 01/02/2025–31/01/2028) Quantum information security and randomness certification (PhD Student: M. I. Moreno Babuglia, 01/09/2024–31/08/2027) Long Distance Device-Independent Quantum Key Distribution (PhD Student: E. B. Klarlund, 15/01/2024–14/01/2027) Quantum-enhanced biomolecule detection (PhD Student: M. F. Schmidt, 01/01/2024–31/12/2026) Multi-user quantum key distribution (PhD Student: R. Zhang, 01/11/2022–01/05/2026, Main Supervisor) He collaborates through the Center for Quantum Technologies and Center for Macroscopic Quantum States, fostering interdisciplinary research in quantum physics and technology.

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Shaoquan Jiangمشاهده پروفایل

استادیار

University of WindsorCanada

Dr. Shaoquan Jiang is an Assistant Professor at the University of Windsor's School of Computer Science. He holds a Ph.D. in Electrical & Computer Engineering from the University of Waterloo (2005). Research interests: His work spans network security architectures, cryptographic protocol design, blockchain implementations, quantum-resistant cryptography, and security education frameworks. Current projects focus on post-quantum security and authentication systems. Teaching: He instructs courses in cryptography, network security, and cyber security fundamentals at undergraduate and graduate levels.

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Thomas Vidickمشاهده پروفایل

استاد

California Institute of Technology (Caltech)United States

Thomas Vidick is a Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech). As of 2022–2023, he held a visiting position at the Weizmann Institute in Israel. He earned his Ph.D. from the University of California, Berkeley in 2011. His research focuses on quantum information, complexity theory, and cryptography, with a particular emphasis on applying complexity-theoretic tools to quantum computing challenges. Notably, his work resolved Tsirelson's problem and demonstrated that MIP* = RE, a landmark result in computational complexity and operator algebras. Research Interests: Quantum information and its intersections with complexity theory Entanglement in multi-prover interactive proofs and device-independent cryptography Quantum verification, cryptography, and protocols Applications of semidefinite programming and approximation algorithms in quantum contexts Awards and Honors: Simons Investigator (2021) NSF CAREER Award (2015) AFOSR Young Investigator Award (2015) Presidential Early Career Award for Scientists and Engineers (2016) Okawa Research Grant (2014) Teaching and Academic Contributions: Regularly teaches courses such as Analysis and Design of Algorithms (CMS/CS/IDS 139) and Introduction to Cryptography (CS 152) at Caltech. Co-organizes the TCS+ online seminar series and contributed to QIP 2022 as a host. Research activities include collaborations on quantum-proof extractors, certifiable randomness, and cryptographic protocols.

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Kaave Hosseiniمشاهده پروفایل

استادیار

University of RochesterUnited States

Kaave Hosseini is an Assistant Professor in the Department of Computer Science at the University of Rochester. He holds a PhD from UC San Diego and a BSc from Sharif University of Technology. His research focuses on theoretical computer science and additive combinatorics, emphasizing approximate algebraic structures and pseudorandomness. Education: PhD in Computer Science, UC San Diego (advisor: Shachar Lovett) BSc in Mathematics and Computer Science, Sharif University of Technology Research Interests: His work bridges theoretical computer science and mathematics, particularly in: Computational complexity Combinatorial structures Discrepancy theory Algebraic methods in computer science Key Publications: Recent works include advancements in communication complexity, pseudorandomness, and lower bounds. Notable achievements include a Best Paper Award at ICALP 2023. Awards: Best Paper Award at ICALP 2023. Teaching: He has taught courses such as Advanced Algorithms (CSC 484/284) and Analytic Methods in Computer Science (CSC 488/288) at the University of Rochester, and combinatorics and probability courses at Carnegie Mellon University. Professional Activities: Organized the Eastern Great Lakes (EaGL) workshop in Theory of Computation.

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Eshan Chattopadhyayمشاهده پروفایل

استاد

University of RochesterUnited States

Eshan Chattopadhyay is a prominent researcher in theoretical computer science, focusing on computational complexity, pseudorandomness, and cryptography. His work centers on the explicit construction of randomness extractors, condensers, pseudorandom generators, and non-malleable codes, often improving entropy requirements and error bounds. He has made significant contributions to derandomization, space-bounded computation, and tamper-resilient cryptography. His research is published extensively in the Electronic Colloquium on Computational Complexity (ECCC), indicating deep engagement with foundational aspects of computer science. Research Interests: Eshan's research spans randomness extraction from weak sources, including sumset sources, polynomial sources, and adversarial models. He investigates pseudorandomness for branching programs, linear threshold functions, and Fourier-based constructions. His work in cryptography includes non-malleable codes, leakage resilience, and secret sharing under bounded collusion. He also contributes to combinatorics through extremal hypergraphs and designs, and to complexity theory via lower bounds and derandomization techniques. The recent articles (2021–2025) show a continued focus on improving extractor and condenser constructions under challenging models such as number-on-forehead protocols, online adversaries, and interleaved or adversarial sources. There is a strong trend toward handling sources with very low entropy, achieving near-optimal parameters, and extending results to two-sided and unbalanced settings in expander graphs. His collaborations with leading researchers like Xin Li, David Zuckerman, and Jesse Goodman reflect his central role in the community. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no formal students or grants are listed, the volume and depth of publications suggest active mentorship and likely grant funding in theoretical computer science. His work often involves junior collaborators, indicating a role in guiding emerging researchers. Labs and Teams: No specific lab or team affiliations are mentioned in the scraped content. However, his frequent co-authorship with researchers from institutions like UT Austin, CMU, and others implies participation in collaborative research networks focused on complexity and cryptography.

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David Zuckermanمشاهده پروفایل

استاد

University of RochesterUnited States

David Zuckerman is a prominent theoretical computer scientist known for his foundational contributions to computational complexity, pseudorandomness, and randomness extraction. His research spans over two decades, with consistent publication in top-tier venues under the Electronic Colloquium on Computational Complexity (ECCC). Although his current institutional affiliation is not specified in the text, his work is widely recognized and frequently collaborative with leading figures in the field. His research interests include: Randomness extraction and derandomization Computational complexity and circuit lower bounds Pseudorandom generators and hitting set constructions Error-correcting codes and combinatorial constructions Communication complexity and Boolean function analysis Applications in cryptography and distributed protocols Analysis of his recent publications reveals a sustained focus on improving the efficiency and scope of randomness extractors, especially for weak or structured sources such as Chor-Goldreich sources, interleaved sources, and algebraic sources. His work often bridges hardness and randomness, leveraging lower bounds to construct pseudorandom objects. A recurring theme is the derandomization of space-bounded and distributed computation, with implications for cryptography and coding theory. David Zuckerman has received significant recognition in the theoretical computer science community, though specific awards are not listed in the provided text. His collaborations with researchers like Salil Vadhan, Raghu Meka, and Eshan Chattopadhyay suggest leadership in major research initiatives. He has also contributed to foundational results in derandomization, such as optimal pseudorandomness from hardness assumptions and improved bounds for coin-flipping protocols. There is no mention of advising students or managing labs in the provided data, but his long-standing research output and mentorship through collaboration imply an academic leadership role. His continued publication into 2025 indicates active engagement in research.

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Jad Silbakمشاهده پروفایل

پژوهشگر ارشد

Northeastern UniversityUnited States

Jad Silbak is a Distinguished Research Fellow in the Department of Computer Science at Khoury College of Computer Sciences, Northeastern University, where he is funded by the Khoury College Distinguished Postdoctoral Fellowship and collaborates with Professor Daniel Wichs. Previously, he held postdoctoral positions at the Simons Institute for the Theory of Computing (UC Berkeley) for the 2025 summer crypto program and at Tel Aviv University hosted by Professor Benny Applebaum. His academic background includes a PhD in Computer Science from Tel Aviv University under advisors Iftach Haitner and Ronen Shaltiel, and B.Sc./M.Sc. degrees from the University of Haifa supervised by Ronen Shaltiel. Educational milestones are: PhD: Tel Aviv University (Computer Science) M.Sc.: University of Haifa (Computer Science) B.Sc.: University of Haifa (Computer Science) Dr. Silbak's research centers on Cryptography , Complexity Theory , and Derandomization , with significant contributions to randomness extraction, error-correcting codes against computationally bounded adversaries, differential privacy, and non-malleable codes. His work bridges theoretical computer science and cryptographic applications, emphasizing security against resource-constrained attackers. Key methodologies include constructing efficient protocols under minimal assumptions and analyzing entropy in samplable distributions. Analysis of his 15 publications (2016-2025) reveals dominant themes in cryptographic foundations and coding theory. Over 70% focus on error-correcting codes for bounded adversaries, while differential privacy and secure computation constitute 20%. His recent work (2024-2025) shows increased emphasis on seedless condensers and optimal-rate non-malleable codes, reflecting evolving trends toward practical cryptographic constructions with theoretical guarantees. Award highlights: Khoury College Distinguished Postdoctoral Fellowship He also serves on program committees for CSCML 2025, Crypto 2025, and RANDOM 2023. Dr. Silbak has mentored students extensively as a Teaching Assistant: six semesters teaching Algorithms at Tel Aviv University (2019-2022) and five semesters teaching Computational Models at the University of Haifa (2015-2017). His research is supported by the Khoury College fellowship, Simons Institute affiliation, and prior Tel Aviv University funding. Current collaborations span Northeastern, Tel Aviv University, and the Simons Institute, with future work expected to advance cryptographic protocols for space-bounded channels and differential privacy frameworks.

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Xin Liمشاهده پروفایل

دانشیار

Johns Hopkins UniversityUnited States

Xin Li is an Associate Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University. He is a member of the theory group and conducts research in the theory of computation, with a focus on randomness in computation, complexity theory, coding theory, and cryptography. He has advised several Ph.D. students and is actively involved in organizing seminars and serving on program committees of major theoretical computer science conferences. Ph.D., University of Texas at Austin, 2011 B.S. and M.S., Tsinghua University, Beijing, China His research interests lie broadly in theoretical computer science, particularly in pseudorandomness , randomness extractors , and explicit combinatorial constructions . He has made significant contributions to the construction of two-source extractors and non-malleable codes. His earlier work includes research in quantum computing and human-computer interaction. The most recent publications show a strong trend in coding theory (especially insertion-deletion codes), extractors (two-source, affine, non-malleable), and streaming algorithms. His work combines deep combinatorial insights with applications in cryptography and complexity theory. Scientific Awards and Honors: Simons Postdoctoral Fellowship NSF CAREER Award CCF-1845349 Invited to Theory of Computing Special Issue (RANDOM 2018) Invited to SICOMP Special Issue (FOCS 2013) SICOMP Special Issue (FOCS 2011) Advising and Grants: Xin Li has advised multiple Ph.D. students including Kuan Cheng, Zhengzhong Jin, Yu Zheng, Songtao Mao, and Yan Zhong. He has served as a postdoctoral mentor and research assistant supervisor. He is supported by several grants including NSF Award CCF-1617713, NSF CAREER Award CCF-1845349, and the Johns Hopkins Catalyst Award. He co-organizes the theory seminar at CS@JHU and has served on the program committees of STOC, RANDOM, and other top conferences. Labs and Teams: Xin Li is a member of the theory group at the Johns Hopkins Department of Computer Science, which focuses on foundational aspects of computation, algorithms, and complexity.

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Zeyu Guoمشاهده پروفایل

استادیار

Ohio State UniversityUnited States

Zeyu Guo is an Assistant Professor in the Department of Computer Science and Engineering at The Ohio State University , based in Dreese Laboratories, Columbus, Ohio. He earned his Ph.D. in Computer Science from the California Institute of Technology in 2017 under the supervision of Chris Umans, followed by postdoctoral appointments at the University of Texas at Austin, the University of Haifa (Israel), and the Indian Institute of Technology Kanpur (India). Research Interests Theoretical Computer Science Computational Complexity Pseudorandomness and Derandomization Coding Theory Algebraic Complexity Theory Algebraic Algorithms His work explores deep interplay between algebra and computation, designing efficient algorithms, constructing pseudorandom objects, and establishing fundamental limits in error-correcting codes. Recent Publication Landscape Across 2021-2025, Guo’s papers predominantly target list decoding capacity for Reed–Solomon and Gabidulin codes, polynomial identity testing for restricted circuit classes, and fast algebraic algorithms such as multivariate multipoint evaluation. A recurring theme is leveraging algebraic geometry and additive combinatorics to derandomize constructions and achieve optimal parameters. Awards & Funding NSF CAREER Award (current support) Advising & Mentoring PhD student: Zihan Zhang Postdoc mentee: Ashish Dwivedi (2023–2024) Teaching & Course Development Guo regularly teaches core graduate and undergraduate courses including Algorithms, Computability and Complexity, and specialized topics in algebraic complexity theory and error-correcting codes.

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David Zuckermanمشاهده پروفایل

استاد

University of Texas at AustinUnited States

David Zuckerman is a Professor in the Department of Computer Science at the University of Texas at Austin, holding an Endowed Professorship. He earned an A.B. in Mathematics from Harvard University (1987) and a Ph.D. in Computer Science from UC Berkeley (1991). His research focuses on pseudorandomness, computational complexity, and their applications, particularly randomness extractors. He has held postdoctoral positions at MIT, Hebrew University, and visiting roles at institutions like the Institute for Advanced Study. His major awards include the 2025 Gödel Prize and the 2024 National Academy of Sciences Michael and Sheila Held Prize for his groundbreaking work on two-source extractors. He has advised numerous students, including Eshan Chattopadhyay, Raghu Meka, and Abhishek Bhowmick, who have achieved notable academic and industry roles. Zuckerman’s research explores the role of randomness in computing, with contributions to coding theory, cryptography, and distributed computing. His work on two-source extractors solved a long-standing open problem, enhancing both theoretical computer science and Ramsey Theory. He has also contributed to practical applications like pseudorandom generators and robust randomized algorithms. Current students include Gautam Chandrasekaran, Michael Jaber, and Vinayak Kumar. His career includes organizing major workshops like DavidFest (2025) and lecturing globally on topics like spectral graph theory and pseudorandomness. Key contributions span over 30 years, with impactful papers in STOC, FOCS, and the Annals of Mathematics.

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Chris Umansمشاهده پروفایل

استاد

California Institute of Technology (Caltech)United States

Chris Umans is a Professor of Computer Science in the Computing and Mathematical Sciences department at the California Institute of Technology (Caltech), affiliated with the Theory Group. He earned his Ph.D. from UC Berkeley in 2000 and joined Caltech in 2002 after a postdoc at Microsoft Research. His research focuses on theoretical computer science, particularly computational complexity, including derandomization, algebraic complexity, and matrix multiplication algorithms. Education: Ph.D. in Computer Science, UC Berkeley (2000); Postdoc, Microsoft Research (2000-2002). Research interests span computational complexity, explicit constructions, and hardness of approximation. His work often intersects algebraic methods and group theory to advance algorithm design, such as group-theoretic approaches to matrix multiplication. Professional Activities: Program committee member for FOCS 2024, STOC, SODA, and others. Vice-Chair of SIGACT (2021-24). Editor for Theory of Computing (ToC), ACM Transactions on Computation Theory (TOCT), and Computational Complexity (CC). Member of the ECCC scientific board. Research Trends: Recent articles explore fast matrix multiplication via matrix groups, algebraic problems over finite fields, and generalized DFTs for finite groups. His work bridges theoretical foundations with algorithmic innovations in algebraic structures. Grants & Labs: His research is supported by NSF grants focused on algebraic methods in complexity theory. He advises students in theoretical computer science and has contributed to collaborative projects on computational algebra and combinatorics.

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Salil Vadhanمشاهده پروفایل

استاد

University of California, BerkeleyUnited States

Salil Vadhan is a Professor at Harvard University and a member of Harvard's Theory of Computation research group. He leads the Privacy Tools Project and co-leads the open-source OpenDP differential privacy software project. His research spans computational complexity, cryptography, randomness in computation, and data privacy, with significant contributions to pseudorandomness theory. He has taught courses such as CS 1200: Introduction to Algorithms and Their Limitations and CS 225: Pseudorandomness , focusing on topics like expander graphs, randomness extractors, and error-correcting codes. His office hours are offered both in-person at Harvard's Science and Engineering Complex and via Zoom. Current professional activities include serving as Editor-in-Chief for Foundations and Trends in Theoretical Computer Science , steering committee roles for the Symposium on the Foundations of Responsible Computing (FORC) and Theory of Cryptography Conference (TCC) , and membership on the Electronic Colloquium on Computational Complexity scientific board.

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Divesh Aggarwalمشاهده پروفایل

دانشیار

University of California, BerkeleyUnited States

Divesh Aggarwal is an Associate Professor at the Department of Computer Science , National University of Singapore , and a Principal Investigator at the Centre for Quantum Technologies . He received his PhD from ETH Zurich under Prof. Ueli Maurer , focusing on theoretical cryptography. His research spans lattices, pseudorandomness, computational complexity, cryptography, and coding theory , with a focus on quantum-safe cryptographic systems. Research Themes: Lattice-based cryptography, quantum algorithms, computational complexity, non-malleable codes, and randomness extraction. Advising: Actively mentors graduate students in theoretical computer science and quantum computing. Professional Service: Serves on program committees for top conferences (CRYPTO, STOC, TCC, etc.) and editorial boards. Group Activities: Organizes a weekly research seminar covering diverse topics in theoretical computer science, including lattice algorithms, quantum computing, and cryptographic protocols.

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