جست‌وجوی استاد و پژوهشگر

• Computational Complexity Theory
• Algorithms
• Cryptography
• +۳ مورد دیگر

Rahul Santhanam is a Professor of Computer Science at the University of Oxford and a Tutorial Fellow at Magdalen College. His research focuses on theoretical computer science, particularly computational complexity theory and its connections to learning , cryptography , logic , and game theory . PhD in Computer Science, University of Chicago (2005) Postdoctoral research: Simon Fraser University, University of Toronto Lecturer at University of Edinburgh (2008), promoted to Reader (2013) Joined University of Oxford in 2016 His research spans computational complexity , exact algorithms , fine-grained complexity , and circuit complexity . Key themes include bounded rationality and probabilistic computation . His publications from 2004–2010 reflect a long-term focus on lower bounds , probabilistic time hierarchies , satisfiability algorithms , and probabilistically checkable proofs (PCPs) . Trends include intersections between cryptographic complexity and theoretical foundations . Scientific awards include the ERC Consolidator Grant ALUnif (2013–2019), supporting work on algorithms and lower bounds . Current student: Matthew Gray Past students: Levente Bodnar Thomas Orton Ninad Rajgopal

• Computational Biology
• Bioinformatics
• RNA Sequencing (RNA-seq)
• +۳ مورد دیگر

Mingfu Shao is an Associate Professor at the Department of Computer Science and Engineering, Pennsylvania State University, and affiliated with the Huck Institutes of the Life Sciences. His research focuses on computational biology and bioinformatics, specifically on RNA-seq data analysis, transcriptome assembly, and genome rearrangement algorithms. Research interests include developing exact and heuristic algorithms for genomic problems such as breakpoint distance computation, double-cut-and-join (DCJ) operations, and accurate assembly of circular RNAs and synthetic long reads. His work integrates machine learning techniques with traditional algorithmic approaches to enhance sequence analysis efficiency. Recent publications highlight advancements in RNA-seq data processing (e.g., Aletsch, TERRACE, Anchorage) and theoretical contributions to edit distance and k-mer analysis. His projects, funded by the National Science Foundation and the National Human Genome Research Institute, aim to improve isoform-level regulatory network inference and allele-specific transcript assembly.

Renato Bruniمشاهده پروفایل

دانشیار

• Optimization
• Machine Learning
• Bioinformatics
• +۱۰ مورد دیگر

Renato Bruni is Associate Professor at the Department of Computer, Control and Management Engineering of Sapienza University of Rome , Italy. He teaches in the Management Engineering and Bioinformatics study programs. His research focuses on Optimization, Machine Learning, and Bioinformatics , with applications spanning spacecraft control, biomedical engineering, and financial portfolio management. Research Interests His scientific activity is centered on: Combinatorial Optimization Data Mining and Classification Derivative-free Optimization Computational Molecular Biology Information Reconstruction Recent Research Trends The analysis of his publications reveals a strong focus on: Power distribution network optimization Spacecraft attitude control via mathematical programming Higher education data quality and institutional heterogeneity Robust classification with limited training data Stochastic dominance in portfolio selection Physician scheduling optimization Grants and Collaborations Principal Investigator in Sapienza-funded projects (2013–2019) Member of EU H2020 RISIS 2 project (2019–2022) Collaboration with international experts: Peter L. Hammer (Rutgers), Fabio Tardella (Sapienza), and Istat (Italian National Statistical Institute)

Ashutosh Raiمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Parameterized Algorithms
• Fixed-Parameter Tractability
• +۷ مورد دیگر

Ashutosh Rai is an Assistant Professor in the Department of Mathematics at the Indian Institute of Technology Delhi (IIT Delhi). He previously served as an Assistant Professor in the Computer Science Department at IIIT Delhi. His academic journey includes postdoctoral research at Charles University in Prague and the Hong Kong Polytechnic University. He completed his PhD and Master’s at the Institute of Mathematical Sciences (IMSc), Chennai, under the supervision of Prof. Saket Saurabh and Prof. Venkatesh Raman. His research focuses on Theoretical Computer Science, especially parameterized algorithms, fixed-parameter tractability, kernelization, and the complexity of NP-complete problems. His work bridges classical and parameterized complexity, exploring hardness and algorithmic solutions. The 15 most recent publications highlight consistent contributions to parameterized complexity, graph editing, coloring, and optimization problems. His research spans journals like Algorithmica , SIAM Journal on Discrete Mathematics , and Theoretical Computer Science , and top conferences including ICALP, IPEC, ESA, and MFCS. Key themes include kernelization, approximation in parameterized settings, and structural graph problems. He has taught courses such as Analysis and Design of Algorithms, Theory of Computation, Parameterized Algorithms, Operating Systems, and Combinatorics at IIT Delhi, IIIT Delhi, and Charles University. He has also mentored students and collaborated extensively with leading researchers in the field. Email: ashutosh.rai@maths.iitd.ac.in

• Theoretical Computer Science
• Computational Complexity
• Approximation Algorithms
• +۶ مورد دیگر

Per Austrin is a Lecturer at the Royal Institute of Technology (KTH) in the Department of Theoretical Computer Science. He has been actively involved in teaching courses such as Algorithms and Complexity (DD2352) , Advanced Algorithms (DD2440) , and Problem Solving and Programming Under Pressure (DD2458) , serving as examiner and course coordinator for several programs. His research focuses on the foundations of computational complexity, approximation algorithms, and cryptographic barriers. Key areas include hardness of approximation for constraint satisfaction problems (CSPs), combinatorial optimization, and theoretical limits in cryptography and coding theory. His work often intersects with probabilistic methods and quantum computing challenges. Recent publications highlight his contributions to understanding lower bounds in optimization problems, inapproximability thresholds, and complexity in structured combinatorial problems. Detailed information about his work can be found on his personal website: Per Austrin's Website .

Cayden Codelمشاهده پروفایل

پژوهشگر

• Programming Languages
• Formal Verification
• Satisfiability (SAT) Solvers
• +۳ مورد دیگر

Cayden Codel is a Researcher at Carnegie Mellon University's Computer Science Department , focusing on programming languages and formal verification. His work bridges theoretical logic with practical applications in automated reasoning and constraint solving. Research Interests: Programming Languages, Formal Verification, Satisfiability (SAT) Solvers, Satisfiability Modulo Theories (SMT), Automated Theorem Proving, Machine Learning Institution: Carnegie Mellon University (CMU) His publications emphasize formal verification for logical systems, SMT/SAT solvers , and reinforcement learning applications. Articles from 2024-2019 reveal a trajectory from foundational logic to real-world dataset design (e.g., Minecraft-based AI research). Thesis Advisors: Marijn Heule, Jeremy Avigad Contact: ccodel@andrew.cmu.edu

• Algorithm Engineering
• Health IT
• Information Systems
• +۸ مورد دیگر

Umberto Nanni is a full Professor of Information Management Systems at the University of Rome "La Sapienza" since November 2005. He has held significant leadership roles including Director of the Research Center for Distance Learning and Technologies for Learning at Telematic University Unitelma Sapienza (2015-2022) and President of the Area Council in Information Engineering at the Latina location of University of Rome "La Sapienza" (2014-2020). Professor Nanni's research spans multiple domains with primary focus on Algorithm Engineering (particularly path algorithms and combinatorial problems), Health IT, Information Systems (with applications in Transport and Logistics, Cultural Heritage), and Technology Enhanced Learning. His work integrates Big Data, Graph and Text mining, Incremental Algorithms, Dynamic Data Structures, and Internet of Things technologies to address complex challenges in these areas. His recent publications demonstrate a strong trend toward biomedical applications, particularly in biospecimen management and digital twins for precision medicine, while maintaining his foundational work in algorithm design and educational technology. The research shows increasing interdisciplinary collaboration, especially between computer science and healthcare domains, with notable publications in Cancer Genomics & Proteomics and other high-impact journals. He has advised over 400 undergraduate and master's theses along with 2 PhD students He has led numerous significant research projects including "Artificial Intelligence algorithms to track and detect Covid-19 vaccine-related infodemic on social media" (2023-2025) He coordinated the "ADCATER - Advanced Digital Solutions for Professional Food and Nutrition Catering Service" project (2021-2023) He served as Principal Investigator for the eLF-eLearning Fitness project (2011-2014) with 19 partners and 42 associated partners Professor Nanni co-founded and was instrumental in developing SPRECware, software tools for Standard PREanalytical Code labeling to improve biospecimen management. His work has resulted in over 100 scientific papers with an h-index of 27, demonstrating substantial impact across computer science, healthcare informatics, and educational technology domains.

Richard Changمشاهده پروفایل

دانشیار

• Computational Complexity Theory
• NP-optimization Problems
• Approximation Algorithms
• +۷ مورد دیگر

Richard Chang is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a Ph.D. from Cornell University (1991) and has been affiliated with UMBC since 1991, serving in various roles including tenure-track positions and joint appointments at the University of Maryland Institute for Advanced Computer Studies (1994–2004). His research focuses on computational complexity theory, particularly bounded query classes, NP-optimization problems, approximation algorithms, and relativized complexity. He has authored numerous papers on topics such as query complexity, Boolean hierarchies, and space-bounded computations. Chang's academic contributions include significant work on the theoretical foundations of computational complexity, including studies on the Boolean hierarchy, randomized reductions, and the structure of NP computations. He has secured multiple research grants, including from the National Science Foundation and the National Security Agency. His teaching spans a wide range of computer science courses, from introductory programming to advanced topics like compiler design and automata theory. He actively participates in academic service, serving on departmental, college, and university committees, as well as organizing conferences and reviewing for top journals. His work emphasizes bridging theoretical computer science with practical algorithmic challenges, contributing to both academic discourse and educational excellence.

Stephen Watsonمشاهده پروفایل

استاد

• Mathematical Economics
• Choice Functions
• Preference Modeling
• +۳ مورد دیگر

Dr. Stephen Watson is Full Professor and Chair of Mathematics and Statistics at York University. His research integrates topology, logic, and game theory to model economic decisions, with emphasis on rational choice functions and preference structures. Research develops mathematical frameworks for choice rationalization, bounded rationality, and social decision mechanisms. Recent contributions include axiomatic analyses of indecisive behavior, Nash equilibrium proofs, and semantic models of salience-based decisions. Work addresses UN Sustainable Development Goals including Reduced Inequalities and Economic Growth. Dr. Watson's theoretical innovations advance understanding of voting systems, behavioral anomalies, and collective decision-making. Publications reconstruct fundamental economic concepts through combinatorial and topological approaches.

• Constraint Programming
• Boolean Satisfiability
• Artificial Intelligence
• +۵ مورد دیگر

Steve Prestwich is a Lecturer at the School of Computer Science and Information Technology, University College Cork. He specializes in Artificial Intelligence, Data Analytics, and Algorithmics, with research interests spanning constraint programming, Boolean satisfiability, and hybrid search methods. Education: BA (Hons) Mathematics from University of Oxford, MSc and PhD in Computer Science from University of Manchester. Research Focus: His work integrates constraint programming, SAT solving, and metaheuristics for optimization under uncertainty, with applications in inventory control, protein design, and stochastic modeling. Awards: Runner-up, Constraint Modelling Challenge Bronze medal, SAT'05 Solver Competition

Markus Bläserمشاهده پروفایل

استاد

• Computational Complexity
• Theoretical Computer Science
• Algebraic Complexity
• +۵ مورد دیگر

Markus Bläser is a Professor in the Department of Computer Science at Saarland University, located on the Saarland Informatics Campus. He is an active researcher in theoretical computer science, with a focus on computational complexity, approximation algorithms, and algebraic complexity. He serves as the Editor-in-Chief of the Springer journal computational complexity . His research interests lie primarily in computational complexity , algebraic complexity , and approximation algorithms . He investigates fundamental problems such as the complexity of matrix multiplication, the design of approximation algorithms for NP-hard problems like the Traveling Salesman Problem (TSP), and the structural properties of algebras in relation to computational efficiency. His work bridges deep mathematical theory with algorithmic applications. The recent publications highlight a strong trend in combinatorial optimization , particularly approximation algorithms for asymmetric TSP and cycle cover problems , often achieving improved performance ratios. Another major theme is algebraic complexity , especially lower bounds for bilinear forms and the rank of algebras. A smaller but notable stream involves algorithmic game theory , such as budget-balanced mechanisms for multicast pricing. Scientific Awards: No awards or fellowships mentioned in the provided text. Markus Bläser has advised PhD and other graduate students, though specific names are not listed. He has led research projects likely supported by German funding agencies, though explicit grants are not detailed. As Editor-in-Chief of a major journal, he plays a significant role in the dissemination of high-quality research in computational complexity. Labs and Research Groups: He leads or is a key member of a research group at Saarland University whose webpage hosts publications from 2006 onward. The group is part of the Saarland Informatics Campus, a collaborative environment including institutions like the Max Planck Institute for Informatics.

Zoltan Kocsisمشاهده پروفایل

مدرس

• Mathematical Logic
• Set Theory
• Lattices
• +۲۸ مورد دیگر

Dr. Zoltan Kocsis is a mathematical logician and educator based at the University of New South Wales (UNSW), where he currently holds the position of Adjunct Lecturer. His research spans multiple areas including proof theory, nonstandard analysis, category theory, and computational logic, with a focus on logical verification, degree of satisfiability, and structured decompositions. PhD in Mathematics from the University of Manchester (2019) Adjunct Lecturer at UNSW Work with interactive theorem proving software like Agda Dr. Kocsis' work on degree of satisfiability explores the probability of logical formulas holding in algebraic structures, revealing gaps in equations from Heyting algebras to group theory. His research on structured decompositions and spined categories provides categorical frameworks for fixed-parameter tractability and tree-width generalizations. In formal verification, he contributed to the seL4 kernel on RISC-V architecture. Recent publications include Proof-theoretic methods in quantifier-free definability (2025), Apartness relations between propositions (2024), and Degree of satisfiability in Heyting algebras (2024). Earlier works cover pseudo-random sequences, homology, and nonstandard analysis in group theory. He has received the CSIRO SCS Engineering and Technology award (2021) and the IBM Prize (2018) for his contributions to logical satisfiability. His collaborations include work with Ben Bumpus on spined categories and Jade Master on structured decompositions, alongside teams at CSIRO and Tallinn University of Technology.

Sumit Kumar Jhaمشاهده پروفایل

استاد

• Artificial Intelligence
• Quantum Computing
• Formal Methods
• +۵ مورد دیگر

Prof. Sumit Kumar Jha is a Professor in the Department of Computer Science at Florida International University (FIU), specializing in artificial intelligence, formal methods, and computer architecture. His research focuses on AI-driven system design, in-memory computing, and robust machine learning systems. He leads over $17 million in active research projects from agencies like DARPA, AFRL, NSF, and DOE. Research interests include: Adversarial machine learning and model robustness Neuro-symbolic systems and program synthesis Analog/digital in-memory computing architectures Formal verification and safety-critical systems Explainable AI and model interpretability Recent work emphasizes secure LLM code generation, quantum computing applications, and fault-tolerant in-memory systems. His publications span top venues like ICML, ICLR, and DAC. Awarded FIU's Top Scholar Award (2024-25) and multiple best paper nominations. Active in NSF-funded initiatives including SPX (extreme-scale computing) and FMitF (formal methods in in-memory systems).

Kazuo Iwamaمشاهده پروفایل

استاد

• Stable Matchings
• Boolean Satisfiability
• Auction algorithms
• +۱۳ مورد دیگر

Kazuo Iwama is a Professor at the School of Informatics, Kyoto University, where he has been employed since 1997. He previously served as a Professor at Kyushu University's Department of Information Science (1992–1997) and held various academic positions, including Associate Professor and Visiting Associate Professor, at institutions such as Kyoto Sangyo University and UC Berkeley's Computer Science Division. Education Ph.D., Electrical Engineering, Kyoto University (1980) M.E., Electrical Engineering, Kyoto University (1975) B.E., Electrical Engineering, Kyoto University (1980) His research spans theoretical computer science, with a focus on algorithms, computational complexity, and quantum computing. Key areas include stable matchings, approximation algorithms, Boolean satisfiability, and quantum network coding. Scientific Awards 2008 Honorary Doctorate from University of Latvia 2005 Member, Science Council of Japan

• Algorithms
• Constraint Programming
• SAT Solving
• +۲ مورد دیگر

Florentina Voboril is a Research Fellow in the Algorithms and Complexity group at Technische Universität Wien. Her research explores how Large Language Models can solve Constraint Programming instances efficiently, with additional focus on SAT-solving and algorithm design. She investigates applications of AI in combinatorial optimization problems and develops innovative approaches to algorithmic challenges. Voboril has developed methods for SAT-based local improvement in string problems and generates streamlining constraints using LLMs. Her work bridges theoretical computer science with practical applications in computational biology and AI-assisted programming.