جست‌وجوی استاد و پژوهشگر

• Mixed-Integer Optimization
• Combinatorial Optimization
• Discrete Mathematics
• +۳ مورد دیگر

Timm Oertel is a Professor in the Department of Data Science at Friedrich Alexander University Erlangen-Nuremberg (FAU), holding the Chair of Analytics & Mixed-Integer Optimization. His office is located in Room 03.344 at Cauerstraße 11, Erlangen, and he can be contacted via email at timm.oertel@fau.de or phone at +49 9131 85-67313. His research focuses on mixed-integer optimization, combinatorial optimization, and discrete mathematics, with significant contributions to sparse solutions in lattices and semigroups, integer Carathéodory rank, knapsack polyhedra, and parametric integer optimization. His work bridges theoretical computer science, operations research, and discrete geometry, emphasizing structural properties of integer solutions and algorithmic efficiency. Professor Oertel's publication record (2013-2025) reveals consistent trends in theoretical integer programming, with recent work (2020-2025) concentrating on sparsity patterns, approximation in algebraic structures, and complexity bounds. He frequently collaborates with leading researchers including Iskander Aliev, Robert Weismantel, and Joseph Paat, publishing in top venues like Mathematical Programming and SIAM Journal on Optimization. His research demonstrates deep connections between combinatorial geometry and optimization theory.

• Optimization
• Mixed-Integer Programming
• Lattice Theory
• +۵ مورد دیگر

Professor Timm Oertel is a leading academic at the Department of Data Science (DDS) at Friedrich Alexander University Erlangen-Nuremberg, where he holds the Chair of Analytics & Mixed-Integer Optimization. His research has established him as a significant contributor to the field of mathematical optimization, with a particular focus on integer programming and its applications. Professor Oertel's research interests center on mathematical optimization , specifically mixed-integer programming , lattice theory , semigroups , and combinatorial optimization . His work explores fundamental questions about sparsity in integer solutions, properties of lattice points in polyhedra, and the theoretical foundations of optimization algorithms. His research bridges pure mathematics with practical applications in operations research and computer science. An analysis of Professor Oertel's publication record reveals a strong thematic consistency with evolving depth. His work consistently addresses sparsity phenomena in integer programming, structural properties of lattices and semigroups, and computational complexity aspects of optimization problems. The publications demonstrate increasing sophistication in handling block-structured problems and parametric optimization scenarios, with recent work extending to colorful variants of classical geometric lemmas applied to integer programming. Professor Oertel has established productive collaborations with leading researchers including Iskander Aliev, Robert Weismantel, and Joseph Paat. His research has been consistently published in top-tier venues including Mathematical Programming , SIAM Journal on Optimization , and the prestigious IPCO (Integer Programming and Combinatorial Optimization) conference series. These publications reflect rigorous theoretical contributions with potential applications across operations research, computer science, and discrete mathematics.

• Algebraic Complexity Theory
• Computational Algebra
• Geometric Complexity Theory
• +۴ مورد دیگر

Prof. Dr. Peter Bürgisser is a Professor at the Technical University of Berlin, affiliated with the Institute of Mathematics and the Algorithmic Algebra research group within Faculty II - Mathematics and Natural Sciences. His research focuses on algebraic complexity theory, computational algebra, and geometric methods in computer science. Bürgisser has made significant contributions to topics including invariant theory, numerical analysis of algorithms, and the computational complexity of algebraic problems. He has authored influential books such as *Algebraic Complexity Theory* and has published extensively in top-tier journals like the Journal of the ACM and SIAM Journal on Computing. His work includes developing polynomial-time algorithms for problems in invariant theory, analyzing the condition numbers of algebraic varieties, and studying the computational aspects of semialgebraic sets. Bürgisser's research also intersects with probability theory, particularly in understanding the statistical properties of zeros of random polynomials and the geometry of random algebraic varieties. Recent trends in his publications emphasize geometric complexity theory, non-commutative optimization, and the application of numerical methods to algebraic problems. He has collaborated with researchers such as Felipe Cucker, Michael Walter, and Avi Wigderson on foundational topics in computational mathematics and theoretical computer science. Bürgisser's office is located in room EB 116, and his contact information includes the email pbuerg@math.tu-berlin.de. His research has been supported through grants and collaborations, though specific grant details are not explicitly mentioned in the provided texts.

Shuichi Hiraharaمشاهده پروفایل

دانشیار

• Computational Complexity Theory
• Meta-complexity
• Average-case Complexity
• +۴ مورد دیگر

Shuichi Hirahara is an Associate Professor at the National Institute of Informatics (NII), Japan, within the Principles of Informatics Research Division. He holds a Ph.D. from the University of Tokyo and has held research positions at the University of Warwick and Nagoya University. His work lies at the intersection of theoretical computer science and cryptography, focusing on foundational questions in computational complexity. Educational Background: Ph.D. in Computer Science, Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo (2016–2019) His research centers on meta-complexity , a field probing the complexity of problems about computational complexity itself, such as the Minimum Circuit Size Problem (MCSP). He investigates average-case complexity , Kolmogorov complexity , and circuit minimization , aiming to understand the limits of efficient computation and to establish secure cryptographic foundations. His work often reveals unexpected hardness results and bridges worst-case and average-case complexity. The recent publications highlight a strong trend toward using meta-complexity to understand cryptographic primitives such as one-way functions and to unify hardness conjectures like the Planted Clique problem. His results have significant implications for proving the security of cryptography based on average-case hardness. Scientific Awards: Young Scientists' Award from MEXT (2024) Yamato Scientific Award (2024) Microsoft Informatics Research Award (2024) Complexity Result of the Year 2022 Funai Research Encouragement Award (2022) Machtey Award (FOCS 2018) Academic Encouragement Award (IEICE, 2019) Hirahara has been actively involved in research funding and academic service. He is the principal investigator of a JSPS Challenging Research (Pioneering) grant on average-time NP-completeness and has participated in several JST and JSPS projects on complexity theory and quantum algorithms. He serves on the program committees of major conferences including STOC, FOCS, and CCC. He is a frequent invited speaker at international workshops and seminars, contributing to the global discourse on computational complexity and cryptography. While no formal advisees are listed, his leadership in research projects suggests an active mentoring role. Labs and Research Teams: He is affiliated with the Informatics Principles Research Division at NII, a leading center for theoretical informatics in Japan. His work is highly collaborative, involving researchers from institutions like JST, University of Tokyo, and international partners.

Louisa Seelbach Benknerمشاهده پروفایل

پژوهشگر

• Data Compression
• Grammar-based Compression
• Succinct Data Structures
• +۳ مورد دیگر

Louisa Seelbach Benkner is a postdoctoral researcher at the University of Siegen , affiliated with the Faculty of Electrical Engineering and Computer Science. Her research focuses on data compression, particularly grammar-based compression, succinct data structures, universal source coding, and analytic combinatorics. She has contributed to theoretical advancements in tree compression and entropy analysis. Education: PhD in Computer Science from University of Siegen (2023). Research interests center on optimizing data compression techniques for tree structures, analyzing entropy bounds, and applying combinatorial methods to algorithm design. Her work bridges theoretical computer science and practical data encoding solutions. Selected publications highlight her expertise in hypersuccinct tree compression, empirical entropy comparisons, and fringe subtree analysis. Key collaborations include researchers like Markus Lohrey, Stephan Wagner, and Travis Gagie. Scientific awards: Capocelli Prize at DCC 2019 Best Student Paper Award at SPIRE 2020 Teaching roles include formal languages, complexity theory, logic, and algorithmics courses. She has also contributed to mathematics instruction in analysis and linear algebra.

Yann Strozeckiمشاهده پروفایل

دانشیار

• Enumeration Complexity
• Algorithmic Game Theory
• Simple Stochastic Games
• +۷ مورد دیگر

Yann Strozecki is an Associate Professor (Maître de Conférences HDR) at the University of Versailles Saint-Quentin, where he is based in the DAVID Laboratory and leads the ALMOST research team focused on algorithms and stochastic models. He is currently on a part-time assignment at LIGM, Gustave Eiffel University, and has previously held positions at LIP6 (RO team), Paris-Sud University (ALGO team), and completed a postdoctoral fellowship at the University of Toronto's Theory Group. He earned his PhD from Paris Diderot (Paris 7) under Arnaud Durand. His research lies at the intersection of theoretical computer science and discrete mathematics, with core interests in: Enumeration complexity, especially delay and space constraints Algorithmic game theory, particularly simple stochastic games (SSGs) Graph and matroid algorithms Cheminformatics and molecular structure generation Sparse polynomials and algebraic complexity Analysis of his recent publications reveals a strong trend in developing efficient enumeration algorithms with provable delay and space bounds, advancing the theoretical foundations of output-sensitive computation. He also contributes to practical algorithms for Cloud RAN scheduling and cheminformatics, often combining theoretical rigor with real-world applications. His work on geometric amortization and strategy improvement in SSGs demonstrates innovation in algorithm design. Notable scientific contributions include: Generic strategy improvement methods for SSGs Polynomial-delay enumeration via closure operations Efficient deterministic scheduling for low-latency networks Tools for molecular cage generation in chemistry Yann Strozecki actively supervises PhD and master’s students, including Noé Demange, Maël Guiraud, and Xavier Badin de Montjoye. He co-organizes the ALMOST team seminar and has advised numerous interns in algorithmics and game theory. His research has been supported through collaborations with Nokia Bell Labs (CIFRE thesis) and interdisciplinary projects in cheminformatics and networking.

• Algorithmic Algebra
• Computational Complexity
• Invariant Theory
• +۴ مورد دیگر

Prof. Peter Bürgisser is a Professor in the Institute of Mathematics at Technische Universität Berlin, leading the Research Group on Algorithmic Algebra. His work focuses on computational complexity, invariant theory, algebraic geometry, and probabilistic methods in mathematics. He holds a prominent role in advancing theoretical computer science and algorithmic algebra through his research and publications. Research interests include Algorithmic Algebra, Computational Complexity, Invariant Theory, Optimization, and Probability Theory. His contributions span foundational work in geometric complexity theory, probabilistic algebraic geometry, and efficient algorithms for algebraic problems. Publications highlight his expertise in topics like random fewnomials, nonarchimedean geometry, and polynomial time algorithms for invariant theory. His work is published in top journals such as Journal für die reine und angewandte Mathematik and Foundations of Computational Mathematics . Prof. Bürgisser is actively involved in academic activities, including teaching and advising, though specific student names are not listed in the provided texts. His research has been supported by grants and collaborations with institutions worldwide.

• Analysis of Algorithms
• Data Analysis
• Massive Data Sets
• +۱۵ مورد دیگر

Robert Krauthgamer is the Harry Weinrebe Professor of Computer Science and currently serves as Department Head in the Department of Computer Science & Applied Mathematics at the Weizmann Institute of Science , within the Faculty of Mathematics and Computer Science . He is a leading researcher in theoretical computer science, particularly in the analysis of algorithms. Research Interests: His research focuses on Analysis of Algorithms , with deep expertise in Data Analysis and Massive Data Sets , Combinatorial Optimization , Approximation Algorithms , Hardness of Approximation , Embeddings of Finite Metrics , and Routing and Peer to Peer Networks . He also maintains a broad interest in Discrete Mathematics and High-Dimensional Geometry . His recent publications highlight work in graph algorithms, parameterized complexity, streaming algorithms, and metric embeddings. Publication Trends: His most recent work, including papers from SODA 2016, demonstrates a strong trend in the design and analysis of efficient algorithms for fundamental problems in graph theory, optimization, and data streams. Key themes include kernelization and sampling techniques for dynamic graph streams, subexponential parameterized algorithms, deterministic derandomization of the polynomial method, and structural results for graph modification problems. His research often bridges theoretical insights with applications in computational biology and network science. Service and Recognition: Journal Editorial: Editor-in-Chief of SIAM Journal on Computing (2019–2025), Associate Editor (2012–2017); Managing Editor of Theory of Computing (2007–2018), and current Editorial Board Member. Conference Leadership: Program Committee Chair for SODA 2016 and HALG 2018; Steering Committee member for SODA, ESA, and HALG; and committee member for the Gödel Prize (2019–2021). Workshops: Organizer of numerous workshops on sublinear algorithms, fine-grained complexity, and high-dimensional data. Teaching and Mentorship: He regularly teaches advanced courses such as Randomized Algorithms and Sublinear Time and Space Algorithms . He advises a large group of MSc and PhD students and hosts postdoctoral researchers, demonstrating a strong commitment to training the next generation of computer scientists. His former students have gone on to successful academic and research careers. Laboratories and Research Groups: He is a key member of the Foundations of Computer Science (theory) seminar at Weizmann and has organized the TheoryLunch and Reading Group in Algorithms, fostering a vibrant research community within the department.

Matteo Camilliمشاهده پروفایل

دانشیار

• Software Engineering
• Software verification
• Automated testing
• +۴ مورد دیگر

Matteo Camilli is an Associate Professor in the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano, Italy, where he leads research in software engineering and verification. His academic journey includes positions as Assistant Professor at Free University of Bozen-Bolzano and postdoctoral research at the University of Milan and University of Bergamo. His educational background includes a PhD in Computer Science (2015), MSc in Computer Science (2012), and BSc in Computer Science (2009), all from the University of Milan. His doctoral research focused on combining advanced abstraction techniques and big data approaches to address state explosion problems in formal verification. Camilli's research primarily centers on software verification, testing, and methods to improve dependability of autonomous, cyber-physical, service-based, and ML-enabled critical systems. His work spans formal methods, model-based testing, uncertainty quantification, and design-time/runtime verification with applications to complex distributed systems. His recent publications reflect a growing focus on explainable self-adaptation, quality assurance for LLM-based systems, and managing uncertainty in adaptive systems. His publication record includes papers in top journals (TOSEM, TAAS, JSS, EMSE) and conferences (ICSE, ISSRE, ICST, ICSA). He serves on program committees for prestigious conferences including ICSE, ICSA, ICST, and ECSA, and is on the steering committee for the International Workshop on Formal Approaches for Advanced Computing Systems (FAACS). Camilli actively contributes to the academic community through conference organization, including serving as Program Committee Member for numerous conferences and as Program Co-Chair for the Software Architecture track at ACM SAC. He also serves as guest editor for special issues on automated testing and dependable AI systems. His teaching portfolio at Politecnico di Milano includes Software Engineering 2, Software Engineering for Automation, and Distributed Software Development. Previously at Free University of Bozen-Bolzano, he taught Systems Engineering and Verification and Reliability for Dependable Systems.

• Quantum Information
• Quantum Computing
• Many-body Physics
• +۵ مورد دیگر

Dr. Rahul Trivedi is a tenured Research Group Leader in the Theory Division at the Max Planck Institute of Quantum Optics in Garching, Germany. His research focuses on theoretical quantum information and quantum science, particularly addressing challenges in noisy quantum systems and simulators. Dr. Trivedi received his undergraduate degree in Electrical Engineering from the Indian Institute of Technology Delhi, followed by MS and PhD in Electrical Engineering from Stanford University (2021). After a postdoctoral fellowship at the Max Planck Harvard Research Center for Quantum Optics, he served as an Assistant Professor of Electrical and Computer Engineering at the University of Washington before returning to MPQ as a tenured researcher in 2024. His research program spans multiple areas at the intersection of quantum information theory, many-body physics, and quantum device engineering. Key research directions include: Theory of open quantum systems and non-Markovian dynamics Quantum simulation with noisy intermediate-scale quantum (NISQ) devices Quantum error correction and fault tolerance Quantum optics theory with applications to quantum simulation and metrology Dr. Trivedi has secured significant research funding including an ERC Starting Grant for his ToNQS project (Theory of Noisy Quantum Simulation of Many-body Physics), as well as previous awards from the National Science Foundation and Department of Energy in the United States. His scientific awards and recognitions include: ERC Starting Grant: ToNQS - Theory of Noisy Quantum Simulation of Many-body Physics National Science Foundation (NSF) research funding Department of Energy (DOE) research funding Dr. Trivedi currently leads a research group consisting of three PhD students, one Master's student, and several co-advised students. His group maintains extensive collaborations with partners both within Europe and the US. With the ERC grant, additional positions for PhD students and postdoctoral researchers are becoming available. The Theory of Open Systems research group is housed in the Theory Division at the Max Planck Institute of Quantum Optics. The group actively collaborates with experimental teams to bridge theoretical frameworks with practical quantum device implementations, particularly focusing on how noise affects quantum simulation capabilities.