جستجوی استاد راهنمای دانشگاهی

• Operations Research
• Supply Chain Management
• Inventory Theory
• +۴ مورد دیگر

Teo Chung Piaw is the Stephen Riady Professor and Executive Director of the Institute of Operations Research and Analytics (IORA) at the National University of Singapore (NUS). He holds a PhD in Operations Research from MIT (1996) and has held academic positions including Head of Department and Acting Deputy Dean at NUS Business School. His research focuses on optimization under uncertainty, supply chain management, and combinatorial optimization. He serves as a department editor for Management Science and has led strategic initiatives in Singapore's Smart Nation Program. Teo's educational journey includes a Bachelor of Science (Honors) in Mathematics from NUS (1990). His corporate experience spans roles at Unilever, Hewlett Packard, and PSA International. He has received prestigious awards including the NUS Faculty Outstanding Researcher Award (2003, 2006) and has been a Fellow of the Singapore-MIT Alliance Program. His research addresses operational challenges in smart cities, healthcare scheduling, and supply chain resilience. Notable contributions include work on appointment scheduling under patient no-show behavior, disruption risk mitigation in supply chains, and flexible production network design. He has authored over 100 publications and serves on editorial boards of leading journals like Operations Research and Management Science .

Mohsen Ghaffariمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Distributed Algorithms
• Parallel Algorithms
• +۳ مورد دیگر

Mohsen Ghaffari is an Associate Professor at MIT's Department of Electrical Engineering and Computer Science (EECS), holding the Steven and Renee Finn Chair. His research focuses on theoretical computer science, particularly distributed and parallel algorithms, graph theory, and network optimization. Formerly, he was a tenured CS faculty member at ETH Zurich until 2022. PhD in Computer Science from MIT (2016) His research interests include distributed algorithms, parallel computing, graph decomposition, and network congestion management. His recent work addresses coreness decomposition, spanner construction, and Euclidean k-center optimization in massive parallel computation frameworks. Notable scientific awards include the ACM Doctoral Dissertation Award (Honorable Mention), ACM-EATCS Doctoral Dissertation Award, and multiple best paper awards at FOCS, PODC, and SODA. He has advised numerous PhD and Master's students, many of whom have transitioned to academic and industry roles. He has taught courses at MIT and ETH Zurich on distributed algorithms, advanced algorithms, and massively parallel computation. His professional activities include serving on program committees for SODA, FOCS, STOC, and organizing workshops like Highlights of Algorithms (HALG) and Workshop on Local Algorithms (WOLA).

Jan Dreierمشاهده پروفایل

پژوهشگر ارشد

• Structural Graph Theory
• Algorithmic Meta-theorems
• Computational Complexity
• +۱ مورد دیگر

Jan Dreier is a Research Fellow at the Institute of Logic and Computation at Vienna University of Technology. His research centers on structural graph theory and algorithmic meta-theorems, particularly exploring the boundaries of tractability for model checking problems. Dreier's work bridges theoretical computer science and discrete mathematics, focusing on graph decompositions, parameterized complexity, and logical expressiveness. Key research themes include monadic stability in graph classes, applications of model theory to computer science, and efficient algorithms for logical queries on structured graphs. His publication record shows consistent focus on graph sparsity concepts and algorithmic applications of logic, with recent work expanding into approximation methods for counting queries. Research demonstrates sophisticated applications of combinatorial methods to fundamental problems in computational complexity.

• Artificial Intelligence
• Computer Vision
• Deep Learning
• +۱۳ مورد دیگر

Noorbakhsh Amiri Golilarz is an Assistant Professor in the Department of Computer Science at The University of Alabama, College of Engineering. He has established himself as a prominent researcher in artificial intelligence, particularly in computer vision, deep learning, and image processing. His educational background includes: Postdoctoral Research Fellow, Computer Science, Boston College (2023) Ph.D., Electrical and Computer Engineering, Southern Illinois University Carbondale (2023) D. Eng., Computer Science and Technology, University of Electronic Science and Technology of China (2021) M.S., Electrical and Electronic Engineering, Eastern Mediterranean University (2017) B.S., Electrical Engineering, University of Guilan (2012) Dr. Golilarz's research spans multiple domains of artificial intelligence with a particular focus on computer vision, deep learning, and image processing applications. His work addresses challenges in medical imaging, satellite imagery, and cognitive neuroscience. He has made significant contributions to image denoising techniques, control chart pattern recognition, and AI applications in healthcare. His recent work has expanded into generative AI, large language models, and secure machine learning operations. His publication portfolio demonstrates consistent productivity with over 2500 citations and an h-index of 25. His most impactful work includes applications of blockchain and federated learning for COVID-19 detection, optimized support vector machines for medical diagnosis, and innovative image denoising techniques using metaheuristic optimization algorithms. Among his professional achievements: Co-founded AI Letters journal in 2024, serving as Associate Editor-in-Chief Served as Lead Guest Editor and Topic Editor for several SCI-indexed journals Held the role of Conference Program Chair Dr. Golilarz has supervised numerous graduate students and research projects, with his work spanning theoretical advancements in AI algorithms to practical applications in healthcare, energy systems, and cybersecurity. His research group has established collaborations with institutions including Boston College and Mississippi State University.

Chandra Chekuriمشاهده پروفایل

استاد

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete and Combinatorial Optimization
• +۶ مورد دیگر

Chandra Chekuri is the Paul and Cynthia Saylor Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign, situated within the Grainger College of Engineering. He has been actively contributing to theoretical computer science for over two decades, with significant leadership roles including serving as Editor-in-Chief of the prestigious SIAM Journal on Computing since May 2025. His academic journey began with a B.Tech in Computer Science from the Indian Institute of Technology, Madras in 1993, followed by a Ph.D. in Computer Science from Stanford University in 1998. Prior to joining UIUC, he spent eight years as a Member of Technical Staff at Bell Labs, Lucent Technologies. Chekuri's research focuses on theoretical computer science with particular emphasis on the design and analysis of algorithms, discrete and combinatorial optimization, approximation algorithms, mathematical programming, and graph theory. His work explores fundamental connections between discrete structures and optimization problems, with applications spanning network design, data analysis, and computational complexity. His recent publications demonstrate a continued focus on hypergraph algorithms, submodular function optimization, and graph partitioning problems, showing how theoretical insights can yield practical algorithmic improvements. His approach often combines continuous relaxations with discrete rounding techniques to develop approximation algorithms for NP-hard problems. As Editor-in-Chief of SIAM Journal on Computing, Chekuri leads one of theoretical computer science's most respected publications, which covers analysis and design of algorithms, algorithmic game theory, computational complexity, and other mathematical aspects of computer science. His editorial leadership follows previous service as Associate Editor for several major journals including SIAM Journal on Computing, Mathematics of Operations Research, and Mathematical Programming. ACM Fellow (January 2024) Scott Fisher Teaching Award (for year 2022-23) from CS Department Chekuri has advised numerous PhD students to completion, including Kent Quanrud, Vivek Madan, Shalmoli Gupta, and Chao Xu, with several currently in progress such as Tanvi Bajpai, ElFarouk Harb, Rhea Jain, and Weihao Zhu. His teaching portfolio includes graduate courses on Randomized Algorithms, Approximation Algorithms, Algorithms for Big Data, and Combinatorial Optimization. He has served as Director of the Graduate Program in the Department of Computer Science from May 2014 to August 2017, demonstrating significant administrative leadership within the department.

Asaf Ferberمشاهده پروفایل

استادیار

• Combinatorics
• Random Graphs
• Probabilistic Methods
• +۱ مورد دیگر

Asaf Ferber is Associate Professor in Mathematics at University of California, Irvine, School of Physical Sciences. His research spans discrete mathematics including combinatorial games, random graphs, extremal hypergraph theory, and quantum computation. Research explores Hamiltonian cycles in random graphs, structural properties of pseudorandom graphs, and quantum algorithms for combinatorial problems. Recent work develops quantum approaches to graph learning and sparse recovery in random matrices. Awards: NSF CAREER Award Sloan Fellowship Distinguished Early Career Faculty Award for Research Air Force Research Grant NSF-BSF Grant Organizes conferences including SoCalDM Symposium and Desert Discrete Math Workshop, mentoring graduate students through UCI's Probability and Combinatorics Seminar.

Daniel A. Spielmanمشاهده پروفایل

استاد

• Spectral Graph Theory
• Algebraic Graph Theory
• Laplacian Matrices
• +۷ مورد دیگر

Daniel A. Spielman is a Sterling Professor of Computer Science, Statistics & Data Science, and Mathematics at Yale University. He serves as the inaugural James A. Attwood Director of the Institute for Foundations of Data Science (FDS) and was previously co-Director of the Yale Institute for Network Science (YINS). He is also a member of TILOS, the NSF Institute for Learning-Enabled Optimization at Scale. His research interests span Spectral Graph Theory, Algebraic Graph Theory, Laplacian Matrices, Expander Graphs, and Random Walks on Graphs. Spielman has made fundamental contributions to understanding the mathematical foundations of data science, including work on smoothed analysis of algorithms, spectral sparsification, and solutions to the Kadison-Singer problem. Spielman's publications demonstrate a consistent focus on developing efficient algorithms with strong theoretical foundations. His work bridges pure mathematics, theoretical computer science, and practical applications in network analysis and machine learning. His research has evolved from foundational work on smoothed analysis to recent contributions in experimental design using discrepancy theory. His scientific honors include: Nevanlinna Prize for contributions to mathematical aspects of computer science Two Gödel Prizes (2008 and 2015) for outstanding papers in theoretical computer science MacArthur Fellowship ('Genius Grant') Simons Investigator award Membership in the National Academy of Sciences and American Academy of Arts and Sciences Spielman has advised numerous PhD students who have gone on to prominent positions in academia and industry. His teaching includes advanced courses in Spectral Graph Theory and Computation and Optimization. He has developed important software packages like Laplacians.jl for solving Laplacian linear equations and related problems.

Imogen Forbes-Macphailمشاهده پروفایل

استادیار

• Nineteenth-Century Poetry
• Mathematics and Literature
• Victorian Studies
• +۳ مورد دیگر

Imogen Forbes-Macphail is an Assistant Professor at the University of California, Davis, specializing in the interdisciplinary intersections of nineteenth-century British poetry and mathematical thought. Her current book project, Line and Number: Formal Problems in Nineteenth-Century Poetry and Mathematics , examines how Victorian poets and mathematicians engaged with analogous formal challenges. Victorian Poetry Caucus Representative, North American Victorian Studies Association Co-Editor (with Anna Henchman), Special Issue of Nineteenth-Century Gender Studies on women’s writing and scientific knowledge production (“Longing to Know”) Research Focus: Forbes-Macphail’s work bridges literary formalism and historical scientific methodologies, particularly exploring topics like computational proof, topological poetics, and the mysticism inherent in Victorian-era mathematical and poetic discourse. Her interdisciplinary approach highlights how mathematical concepts influenced poetic structures and vice versa. Scientific Contributions: Her publications span analyses of the Four-Color Theorem, Ada Lovelace’s literary-scientific legacy, and the gendered dynamics of 19th-century knowledge production. Key trends include the aestheticization of mathematical rigor, the role of formalism in shaping Victorian intellectual paradigms, and crossdisciplinary epistemological inquiries. Honorable Mention, “Expanding the Field” Essay Prize, Northeast Victorian Studies Association (2022) Susan Morgan Graduate Student Essay Prize, Interdisciplinary Nineteenth-Century Studies (2019) Sally Mitchell Prize, North American Victorian Studies Association (2018) Honorable Mention, Susan Morgan Graduate Student Essay Prize (2018) Sussex-Samuel Prize, Australasian Universities Language and Literature Association (2013) Forbes-Macphail’s teaching includes courses such as ENL 164: Writing Science Publications , emphasizing the synthesis of scientific and literary communication. She previously held a Junior Fellowship at the Harvard Society of Fellows (2022–25), underscoring her prominence in Victorian studies.

Daniel Varroمشاهده پروفایل

استاد

• Model-Based Systems Engineering
• Cyber-Physical Systems
• Software Engineering
• +۱۲ مورد دیگر

Daniel Varro is a Professor affiliated with McGill University (Faculty of Engineering, School of Computer Science), with strong ties to Budapest University of Technology and Economics and Linköping University. He is a leading researcher in model-driven engineering, cyber-physical systems, and software engineering, actively contributing to top-tier conferences such as MODELS, ICSE, and ASE. His research focuses on model-based systems engineering (MBSE) , automated model generation , model transformations , and constraint-based consistency checking . Recently, his work has expanded into integrating large language models (LLMs) and machine learning into modeling workflows, including model querying, domain modeling, and bug detection. The recent publications reveal a strong trend toward AI-augmented modeling, logic-based solvers (e.g., Refinery), and safety assurance of autonomous systems (e.g., COLREGs compliance). His work bridges formal methods with practical software engineering challenges in industrial and safety-critical domains. Scientific Awards: No specific awards mentioned in the text. Advising and Grants: While no explicit list of students or grants is provided, his mentorship in the Doctoral Symposium and repeated leadership roles suggest active supervision and likely grant funding. He has led projects on automated model generation, model quality, and AI integration in modeling. Labs and Teams: Daniel Varro is associated with research groups focused on model-driven engineering and software evolution, likely leading or co-leading teams working on the VIATRA and Refinery frameworks for model transformation and solving.

Jason Liمشاهده پروفایل

استادیار

• Fast Graph Algorithms
• Algorithm Design
• Minimum Cut Problems
• +۶ مورد دیگر

Jason Li is an Assistant Professor in the Department of Computer Science at Carnegie Mellon University's School of Computer Science. He teaches advanced algorithms courses including 15-754 Spectral Graph Theory (Spring 2025), 15-451 Design and Analysis of Algorithms (Fall 2024), and 15-850 Advanced Algorithms (Spring 2024). His research focuses on fast graph algorithms , particularly solving longstanding open problems through modern algorithmic techniques. Key research themes include preconditioning and locality , which serve as reductions from worst-case to well-behaved and local instances respectively. His work has produced breakthroughs in deterministic global minimum cut algorithms, all-pairs minimum cut (Gomory-Hu trees), and near-optimal parallel shortest path algorithms. Analysis of his recent publications reveals a consistent trend toward almost-linear time algorithms for fundamental graph problems, with significant contributions to dynamic graph algorithms, minimum cut variants, and parallel computation. His work frequently appears in top venues including STOC, FOCS, and SODA, often with multiple best paper recognitions. EATCS Distinguished Dissertation Award (2021) Best Paper Award at SODA 2024 Invited to HALG 2024 Invited to TALG and JACM for SODA 2024 paper Machtey Best Student Paper at FOCS 2019 Professor Li actively advises graduate students including Henry Fleischmann and George Li. His research is supported by collaborations with leading institutions and frequent invitations to present at major conferences. He maintains an open-door policy for CMU students and collaborators, though notes the high volume of research inquiries he receives weekly.

• Cryptography
• Post-Quantum Cryptography
• Elliptic Curve Cryptography
• +۳ مورد دیگر

David Jao is a Professor in the Department of Combinatorics and Optimization at the University of Waterloo. His research focuses on post-quantum cryptography, particularly leveraging isogenies of supersingular elliptic curves for secure cryptographic protocols. He is renowned for co-developing the Supersingular Isogeny Key Encapsulation (SIKE) protocol, a leading candidate for post-quantum cryptography standards. His work spans theoretical foundations and practical implementations, including optimizing isogeny-based systems for embedded devices and ARM processors. Research interests include isogeny-based cryptosystems, elliptic curve cryptography, zero-knowledge proofs, and cryptographic security against quantum attacks. He explores applications of expander graphs and Ramanujan graphs in cryptography, alongside algorithmic improvements for cryptographic protocols such as SIDH (Supersingular Isogeny Diffie-Hellman). Key contributions include advancements in key compression techniques for SIKE, side-channel attack mitigation, and formalizing security models for post-quantum key exchange. His publications analyze cryptographic hardness assumptions, such as the discrete logarithm problem in finite groups and the semidirect product structure in isogeny-based systems. Jao’s work bridges theoretical mathematics and applied cryptography, with a focus on ensuring practical security in next-generation cryptographic systems. His research addresses challenges in quantum-resistant authentication, key establishment, and digital signatures, often emphasizing efficiency and resistance to both classical and quantum attacks.

Tim Van de Cruysمشاهده پروفایل

مدرس ارشد

• Computational Linguistics
• Natural Language Processing
• Computational Semantics
• +۵ مورد دیگر

Tim Van de Cruys is a Senior Lecturer at the Faculty of Arts, KU Leuven, serving as Head of the Centre for Computational Linguistics (CCL). He maintains significant affiliations with LECTIO (KU Leuven Institute for the Study of the Transmission of Texts, Ideas and Images), Leuven.AI (KU Leuven Institute for Artificial Intelligence), and LILI (KU Leuven Interdisciplinary Language Institute). His work bridges computational linguistics, artificial intelligence, and humanities research with practical applications across multiple disciplines. Dr. Van de Cruys specializes in computational semantics and creative language generation, with particular expertise in applying NLP techniques to historical and classical texts. His research spans multiple domains including: Natural Language Processing for ancient languages (Latin, Ancient Greek) Computational approaches to lexical and compositional semantics Large language models and their applications in humanities research Creative language generation and human-AI collaboration Named entity recognition and disambiguation in historical contexts Non-autoregressive modeling for sequential generation tasks His recent publications demonstrate a strong focus on applying cutting-edge NLP techniques to humanities challenges, particularly in processing ancient languages. He frequently employs transformer models to address named entity recognition, word sense discrimination, and semantic analysis in low-resource language contexts. His work consistently bridges formal linguistic theory with practical computational applications, creating valuable tools for digital humanities scholars. As promotor and co-promotor on numerous research projects extending through 2029, Dr. Van de Cruys supervises PhD students working at the AI-humanities intersection. His current major projects include "Living Corpora" (exploring human-AI collaboration in digital humanities), "Stochastic processes and non-autoregressive models for sequential generation," and "NIKAW" (exploring knowledge networks from classical antiquity). These projects demonstrate his commitment to advancing both theoretical understanding and practical applications of computational linguistics. He teaches various courses including Computational Linguistics, Scripting Languages, Programming for Humanities, Computational Creativity, and AI for Humanities, training students to work at this critical interdisciplinary crossroads. His leadership of the Centre for Computational Linguistics positions him at the forefront of computational linguistics research in Belgium, where he continues to expand the boundaries of what's possible at the intersection of language, computation, and humanistic inquiry.

Sanjay Jainمشاهده پروفایل

استاد

• Inductive Inference
• Recursion Theory
• Complexity Theory
• +۳ مورد دیگر

Sanjay Jain is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). His research focuses on theoretical computer science with particular emphasis on inductive inference, recursion theory, complexity theory, and computational learning theory. Education: B.Tech. in Computer Science from Indian Institute of Technology Kharagpur, India (1986) M.S. in Computer Science from University of Rochester, USA (1988) Ph.D. in Computer Science from University of Rochester, USA (1990) Professor Jain's research spans multiple areas of theoretical computer science. His primary contributions are in computational learning theory, where he has made significant advances in understanding the intrinsic complexity of language identification and the limits of inductive inference. His work on recursion theory explores fundamental questions about computability and complexity, while his research in complexity theory addresses structural aspects of computational problems. A notable achievement was his work on "Deciding Parity Games in Quasipolynomial Time," which won the prestigious STOC 2017 best paper award and later the EATCS-IPEC Nerode Prize. Professor Jain's publication record shows a consistent focus on theoretical foundations of computer science, particularly in learning theory and computational complexity. His recent work has expanded into automatic structures, semiautomatic models, and connections between computational learning and algebraic structures. There is a clear progression from foundational work on language identification to more complex models involving automatic functions, transducers, and connections to mathematical logic. Scientific Awards: STOC 2017 Best Paper Award for "Deciding Parity Games in Quasipolynomial Time" EATCS-IPEC Nerode Prize (2021) Professor Jain has served on the editorial board of Information and Computation and has been actively involved in the academic community through program committee memberships for major conferences including COLT, ALT, LATA, TAMC, and PRICAI. He has held leadership roles as program co-chair for ALT 2000 and ALT 2013, and conference chair for ALT 2005. His work has been supported by various research grants, though specific details are not provided in the available materials. Professor Jain leads research in theoretical computer science at NUS, where he has built a strong research group focused on computational learning theory and related areas. His work often involves collaborations with researchers from around the world, particularly with Frank Stephan, with whom he has co-authored numerous papers. His research group has made significant contributions to understanding the fundamental limits and possibilities of computational learning models.

• Fast graph algorithms in different computation models
• Robust algorithms against adaptive adversaries
• Continuous optimization for combinatorial problems
• +۳ مورد دیگر

Thatchaphol Saranurak is an Assistant Professor at the University of Michigan , specifically in the Computer Science and Engineering Division . Prior to this, he earned his PhD in Computer Science from KTH Royal Institute of Technology in 2018 under Danupon Nanongkai , followed by a postdoctoral research assistant professorship at Toyota Technological Institute at Chicago (2018-2020). Research Focus : His work bridges fundamental problems in graph theory, including Dynamic graph algorithms for max-flow and min-cut Expander graph decompositions and their applications Robust algorithms against adaptive adversaries Continuous optimization for combinatorial problems Scientific Contributions : He has made breakthroughs in deterministic graph algorithms, notably improving vertex connectivity bounds, developing near-linear time Gomory-Hu trees, and advancing dynamic matching algorithms. His research has been recognized by Sloan Research Fellowship NSF CAREER Award Presburger Award 2023 Teaching : He teaches courses like Expander and Graph Algorithms and Introduction to Algorithms (Winter 23, Winter 25). His lecture videos and notes are publicly available. Collaborations : He works with leading researchers including Sayan Bhattacharya , Joakim Blikstad , and Jason Li , with affiliations to institutions like TTIC , KTH , and SODA conferences.

Giorgis Petridisمشاهده پروفایل

دانشیار

• Arithmetic Combinatorics
• Combinatorial Geometry
• Number Theory
• +۳ مورد دیگر

Giorgis Petridis is an Associate Professor at the University of Georgia, specializing in arithmetic combinatorics, a field rooted in combinatorial number theory with modern extensions into discrete analysis and finite field geometry. Born in Athens, Greece, he earned his PhD from the University of Cambridge under Tim Gowers and held a Visiting Assistant Professor position at the University of Rochester. He serves as an editor for Combinatorial Theory and is affiliated with the Number Theory and Arithmetic Geometry group, particularly its additive combinatorics and discrete analysis subgroup. Doctor of Philosophy (2011), University of Cambridge Certificate of Advanced Studies in Mathematics (2002), St John’s College, Cambridge BA (Hons) in Mathematics (2001), St John’s College, Cambridge His research focuses on additive combinatorics, exploring sumset estimates, polynomial configurations in prime lattices, and geometric incidence problems over finite fields. He investigates combinatorial geometry, including pinned distance problems and bisector arrangements, while also contributing to exponential sum bounds and expander graph theory. His work bridges theoretical mathematics with applications in pseudorandomness and discrete geometry. Recent publications highlight trends in finite field analysis, with 6 of 15 articles addressing arithmetic structures in prime-order fields. Key keywords include Combinatorics , Number Theory , and Finite Fields , with sub-fields spanning polynomial configurations, energy bounds, and geometric combinatorics. Scientific awards include the Creative Research Medal (2024) from the University of Georgia for mid-career research impact. Grants from the Simons Foundation (MPS-TSM-00007816) and multiple NSF DMS Awards (2054214, 1723016, 1500984, 1804049) support his work on discrete analysis and conferences. He co-advises five PhD students and has supervised multiple Master’s theses on topics like point-plane incidences and additive energy. Outreach includes leading high school math teams, organizing discrete analysis sessions, and contributing to public science communication guides.