جست‌وجوی استاد و پژوهشگر

Irène Marcoviciمشاهده پروفایل

استاد

• Probability Theory
• Dynamical Systems
• Cellular Automata
• +۴ مورد دیگر

Irène Marcovici is a Professor in the Department of Mathematics at the University of Rouen Normandy, affiliated with the Raphaël Salem Mathematics Laboratory (LMRS). She leads the Probability and Dynamical Systems team within LMRS and participates in the ALEA and SDA2 working groups of the GDR Informatique Fondamentale et ses Mathématiques. PhD in Mathematics (2013, University of Paris Diderot) Habilitation à Diriger des Recherches (2021, University of Lorraine) Her research focuses on probability theory , dynamical systems , and cellular automata , with significant contributions to percolation theory, self-organization phenomena, and combinatorics on words. She investigates how randomness influences complex systems, particularly through probabilistic cellular automata and their ergodic properties. Analysis of her recent publications (2021-2025) reveals a strong emphasis on percolation dynamics (e.g., corner percolation with directional bias), self-stabilization mechanisms in cellular systems, and combinatorial structures like Kolakoski sequences. Her work bridges theoretical computer science and pure mathematics, often employing stochastic methods to solve problems in symbolic dynamics and discrete geometry. Supervision & Collaborations: Currently supervising Maxence Poutrel (with Jérôme Casse) Previously supervised Pierrick Siest (2021-2024), Jocelyn Begeot (now Associate Professor), and Pierre-Adrien Tahay (now PRAG at Telecom Nancy) Regular collaborations with Régine Marchand, Nazim Fatès, and Pascal Moyal Laboratory Context: As leader of the Probability and Dynamical Systems team at LMRS, she contributes to France's national research infrastructure in fundamental mathematics, with connections to CNRS and international working groups focused on automata theory and discrete probability.

• Combinatorial Optimization
• Approximation Algorithms
• Online Algorithms
• +۳ مورد دیگر

Prof. Dr. Sven Oliver Krumke is a Full Professor of Mathematics and currently serves as Dean of the Faculty of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU). His research focuses on Combinatorial Optimization, Approximation Algorithms, Online Algorithms, Complexity, Algorithmic Game Theory, and Graph Theory with Applications. He leads the Optimization Group (AG Optimierung) within the Department of Mathematics. Education and Academic Path: PhD (Dr. rer. nat.) in Mathematics, University of Würzburg (1997) Habilitation in Mathematics, Technische Universität Berlin (2002), Thesis: 'Online Optimization: Competitive Analysis and Beyond' Professor at RPTU since 2004 Research Projects: Principal investigator in the Research Training Group (GRK 2982) 'MIMO: Mathematics of Interdisciplinary Multiobjective Optimization' Project lead for 'ONE PLAN: Optimization in Emergency Medical Services in Rhineland-Palatinate' Teaching includes courses on Analysis, Mathematical Modeling in Economics, and Reading Courses. He supervises Bachelor's and Master's theses in Optimization-related topics. He has held roles such as Scientific Researcher at the Konrad-Zuse-Zentrum Berlin (1998–2004), and has extensive international collaborations, including a Fulbright-funded stay at SUNY Albany (1992–1993). His work emphasizes practical applications in healthcare logistics, emergency services optimization, and algorithmic solutions for real-world problems.

Kai Salomaaمشاهده پروفایل

استاد

• Theory of Computation
• Automata Theory
• Formal Languages
• +۵ مورد دیگر

Kai Salomaa is a Professor and Graduate Chair in the School of Computing at Queen’s University, Canada. He holds a Ph.D. from the University of Turku (1989). His research focuses on theoretical computer science, particularly automata theory, formal languages, and their applications. Key areas include descriptional complexity, cellular automata, and quantum computing innovations. Affiliations: Queen’s University, School of Computing. Education: Ph.D. in Computer Science from the University of Turku (1989). Research Interests: Prof. Salomaa explores foundational topics like automata state complexity, nondeterminism measures, and computational models. His work bridges classical theory with modern applications in quantum computing, vehicular networks, and algorithmic resource optimization. Notable contributions include studies on input-driven pushdown automata and the integration of quantum algorithms into practical systems. Publications: His recent work spans quantum-enhanced optimization (e.g., vehicle platooning), fair matching algorithms, and complexity analysis of automata. These studies emphasize innovative solutions for computational challenges in dynamic systems and distributed networks. Grants & Labs: Leads the Formal Languages and Automata Theory Research Group, actively organizing conferences like CIAA and DCFS. His work often addresses practical applications of theoretical computer science in areas like sensor networks and metaverse resource management.

• Strategic Leadership
• Corporate Governance
• Organizational Search
• +۳ مورد دیگر

Wei Shen is the Dean’s Council Distinguished Professor and Chair of the Department of Management and Entrepreneurship at Arizona State University’s W. P. Carey School of Business. He previously served as Associate Dean for W. P. Carey China Programs and Faculty Director of the China Executive MBA Program. His research focuses on CEOs, boards of directors, and organizational impacts, with publications in top-tier journals like Administrative Science Quarterly and Strategic Management Journal. Educated at Peking University (B.S. in Psychology) and Texas A&M University (Ph.D. in Business Administration), Shen has received awards including the Robert J. Litschert Best Doctoral Student Paper Award and the Mays Outstanding Ph.D. Alumni Award. He currently serves as President-Elect of the International Association for Chinese Management Research (IACMR). His research interests include strategic leadership, corporate governance, organizational search mechanisms, and research methodology. Key themes in his work address CEO accountability, board dynamics, and the interplay between organizational performance and governance structures. Shen’s publications span over two decades, consistently exploring governance mechanisms, strategic decision-making, and leadership succession. Recent work examines tiered status hierarchies in competitive actions, gender bias in CEO roles, and compliance with governmental mandates. His books include Empirical Methods in Organization and Management Research (4th ed.) and Organizational Management: A Perspective of Chinese Enterprises in the Age of Digital Intelligence . He has advised numerous academic programs and holds leadership roles in advancing Chinese management research. His courses include doctoral seminars, strategic management, and global corporate strategy, reflecting his commitment to educating future business leaders.

Marina Knittelمشاهده پروفایل

استادیار

• Graph Algorithms
• Fair Machine Learning
• Mechanism Design
• +۳ مورد دیگر

Marina Knittel is an Assistant Professor of Computer Science at Reed College in the Division of Mathematical and Natural Sciences, starting Spring 2025. She currently serves as a postdoctoral researcher at UC San Diego working with Profs. Barna Saha and Sanjoy Dasgupta on graph algorithms. She holds a PhD from the University of Maryland (2023) and a BS in Mathematics and Computer Science from Harvey Mudd College. Her research focuses on graph algorithm theory with applications spanning fairness in machine learning, mechanism design, and massively parallel computation. She explores interdisciplinary connections between computer science, economics, and biology, particularly how computational problems increasingly require cross-domain expertise. Knittel's publication portfolio demonstrates consistent focus on scalable algorithms for massive datasets, with recent work emphasizing fairness in clustering and hierarchical methods. Her articles frequently appear in top theoretical computer science venues and show sophisticated mathematical approaches to practical computational problems.

• Computer Architecture
• High-Performance Computing
• Multicore and Manycore Systems
• +۷ مورد دیگر

Miquel Moreto Planas is a Senior Lecturer in the Department of Computer Architecture at the Barcelona School of Informatics, Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading institution in high-performance computing. His academic profile is deeply rooted in computer architecture and high-performance computing, with a strong emphasis on practical and theoretical advancements in multicore systems, memory management, and hardware acceleration. His research interests span a wide range of topics including computer architecture, high-performance computing, multicore and manycore systems, cache and memory management, hardware acceleration for genomics and AI, RISC-V processor design, processing-in-memory, interconnection networks, and real-time systems. These interests are reflected in his extensive publication record and collaborative projects. The most recent articles highlight a significant trend toward interdisciplinary research, particularly the application of advanced computer architecture techniques to bioinformatics and healthcare. Key themes include the acceleration of genomic sequence alignment using novel hardware such as processing-in-memory, the development of benchmarks for ARM-based HPC systems in genomics, and the creation of AI-based 3D decision support tools for neurosurgical applications. His work also continues to advance core computer architecture topics like cache management, power-aware resource allocation in heterogeneous systems, and the design of secure, post-quantum cryptographic hardware based on RISC-V. Fulbright Award 2011 HiPEAC Paper Award HiPEAC Paper Award 2024 HiPEAC Paper Award Moreto has been a principal investigator or key contributor to multiple competitive R&D+i projects, such as the STRATUM project for neurosurgical tools, REDIOH for open hardware, and the Laboratorio Zettaescala de Barcelona. He has advised several doctoral students, including López, G., Kostalampros, I., and Haghi, A., and is a core member of the CAP (High Performance Computing) research group at UPC. His work is characterized by strong collaborations with leading researchers like Mateo Valero, Eduard Ayguadé, and Jesús Labarta, often bridging the gap between UPC and BSC-CNS. His laboratory and team affiliations are centered around the CAP group and the Barcelona Supercomputing Center, where he contributes to cutting-edge research in high-performance and embedded computer architectures. His recent work on the BIMSA accelerator and the STRATUM project demonstrates a clear future direction toward applying high-performance computing solutions to critical problems in genomics and medicine.

Christopher Hojnyمشاهده پروفایل

استادیار

• Mixed-Integer Programming
• Symmetry Handling in Optimization
• Combinatorial Optimization
• +۳ مورد دیگر

Christopher Hojny is an Assistant Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology , specializing in combinatorial optimization. He contributes to the EAISI Foundational group and co-develops the academic solver SCIP . His research focuses on symmetry handling in mixed-integer programming , theoretical properties of integer programs, and algorithm development for combinatorial optimization. Recent work explores applications in graph neural network verification , clustering problems, and network coding through mixed-integer programming frameworks. Key publication trends show expertise in Symmetry detection and mitigation techniques Relaxation complexity theory Applications to machine learning robustness Decision diagram-based scheduling Scientific contributions include Proof systems for symmetry certification Topological bounds tightening in GNNs Stable set problem symmetry handling SCIP solver extensions He supervises PhD students Cédric Roy (NWO project on Local Symmetries) and Sten Wessel (co-supervised with Frits Spieksma), while Jasper van Doornmalen (2019-2023) investigated symmetry propagation algorithms.

• Supply Chain Coordination
• Spreadsheet Modeling
• Decision Making & Optimization
• +۳ مورد دیگر

Professor Michelle Cheong Lee Fong is a full-time faculty member at the School of Information Systems, Singapore Management University. She holds leadership roles as Associate Dean for Post-Graduate Professional Education and Director of the Doctor of Engineering program, and is actively involved in designing educational frameworks for technology-driven learning. Current affiliations: Singapore Management University (School of Information Systems) Research focus: Supply chain coordination, spreadsheet modeling, and educational technology Key courses taught: Computer as an Analysis Tool, Financial Modeling, Process Modeling Her research interests in supply chain coordination span strategic hub location optimization, tactical supplier coordination, and operational transportation planning. She also specializes in spreadsheet modeling for business decision-making, having developed textbook resources and case studies for logistics networks and financial planning. Recent work explores AI's role in digital education, including ChatGPT's impact on assessment design and ethical considerations in AI-driven pedagogy. The articles she has written or co-authored demonstrate expertise in operations research, educational technology, and AI applications. Topics include optimization theory, heuristic algorithms for scheduling, and digital assessment frameworks that integrate learning analytics. Her work bridges spreadsheet modeling's pedagogical value with modern challenges like ChatGPT's influence on student learning. Her teaching portfolio includes courses such as IS102 (Computer as an Analysis Tool), IS304 (Process Modeling), and FNCE645 (Financial Modeling). These courses emphasize practical skills in translating business requirements into technology solutions through spreadsheet-based analytical frameworks.

• Algorithmic Game Theory
• Fair Division
• Computational Economics
• +۳ مورد دیگر

Dr. Georgios Birmpas is a researcher specializing in algorithmic game theory, computational economics, and fair division. He currently serves as Module Co-ordinator for Algorithmic Game Theory (COMP559) and Computational Game Theory and Mechanism Design (COMP326) at an institution not explicitly named. His research focuses on fairness and efficiency in resource allocation problems, often intersecting computer science, economics, and multiagent systems. Key research areas: Algorithmic Fairness Submodular Optimization Strategic Agent Modeling Distortion in Voting Systems Recent contributions include: Fair multiobjective submodular function maximization Existence of approximate equilibria in resource allocation Two-query distortion analysis in matching problems Interdependent value models in fair division His work has appeared in venues such as the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS) and journals like Mathematics of Operations Research and SIAM Journal on Discrete Mathematics . Collaborators include researchers from institutions across Europe, focusing on theoretical and applied aspects of algorithmic fairness.

• Operations Research
• Combinatorial Optimization
• Game Theory
• +۳ مورد دیگر

Tom Demeulemeester is a Research Fellow at the Operations Research and Statistics Research Group (ORSTAT) of KU Leuven , with a future appointment as Assistant Professor in Operations Research at Maastricht University starting August 2025. His work bridges operations research, combinatorial optimization, and computational social choice, focusing on fair resource allocation and algorithmic game theory. His research emphasizes fairness in integer programming, hedonic games, and one-sided matching. Recent work examines Rawlsian assignments and strategyproofness in multiwinner elections. Publications span journals like the European Journal of Operational Research and conferences such as MFCS and AAAI, with a focus on both theoretical and applied optimization. Key trends in his publications include randomization for fairness, stability in coalition formation, and axiomatic approaches to matching problems. All works are publicly accessible via repositories, with code available on GitHub. This aligns with his commitment to open science and reproducibility. Tom actively engages with academic communities through conference participation (EURO, MFCS, AAAI) and workshops on school choice. He will soon transition to Maastricht University after completing his PhD defense at KU Leuven in May 2024, titled Fairness through randomization: An operations research perspective .

Francisco Castroمشاهده پروفایل

استادیار

• Auctions
• Market Design
• Online Display Advertising
• +۳ مورد دیگر

Francisco Castro is an Assistant Professor at the UCLA Anderson School of Management since 2020. His research bridges operations management and market design , focusing on spatial and incentive dynamics in digital marketplaces. Prior to UCLA, he served as a Postdoctoral Research Scientist at Uber , where he developed models for ride-hailing platforms and supply chain resilience during crises. Ph.D., Decision, Risk and Operations (2020, Columbia Business School) M.S., Mathematical Engineering (2014, University of Chile) B.S., Engineering Sciences (2013, University of Chile) Castro’s research explores optimal pricing policies and incentive-compatible contracts in platforms like Uber. His work on surge pricing frameworks (Management Science, 2021) and spatial capacity planning (Operations Research, 2021) has implications for ride-hailing, delivery logistics, and high-dimensional market design challenges. Recent projects address autonomous vehicle integration and spatial inequality risks in platform economies. His publications span journals like Operations Research , Games and Economic Behavior , and Management Science , with working papers examining matching queues , two-sided marketplace dynamics , and AI-driven market design . Castro emphasizes translating these insights into MBA curriculum , preparing students for post-pandemic economic shifts through creative problem-solving and data-driven decision frameworks .

Artur Czumajمشاهده پروفایل

استاد

• Theoretical Computer Science
• Randomized Algorithms
• Parallel and Distributed Computing
• +۴ مورد دیگر

Artur Czumaj is a Professor of Computer Science and Director of the Center for Discrete Mathematics and its Applications (DIMAP) at the University of Warwick, United Kingdom. He is a member of the Global Faculty at the University of Cologne and serves as President of the European Association for Theoretical Computer Science (EATCS). PhD and Habilitation from University of Paderborn Recipient of the IBM Award and Fellow of EATCS His research focuses on theoretical computer science, particularly in the design of randomized algorithms, analysis of large data, and applications to parallel/distributed computing, property testing, sublinear algorithms, optimization algorithms, and algorithmic game theory. His work has been funded by major institutions including EPSRC, NSF, Royal Society, European Union, Simons Foundation, and IBM. The 15 most recent publications reflect expertise in graph algorithms, distributed systems, approximation techniques, and algorithmic complexity. His research spans foundational algorithm design to practical applications in large-scale data processing. Fellow of the European Association for Theoretical Computer Science (EATCS) IBM Award recipient Czumaj has held leadership roles in prominent conferences, including Program Committee Chair for STOC, ICALP, SODA, and HALG. His academic career is supported by grants from multiple international research councils and organizations.

• Operations Research
• Scheduling Algorithms
• Integer Linear Programming
• +۳ مورد دیگر

Gerhard F. Post is an Assistant Professor specializing in Mathematics of Operations Research. His work focuses on algorithmic solutions for scheduling and optimization problems, particularly in healthcare and educational contexts. He contributes to the UN Sustainable Development Goals through research addressing complex operational challenges. Research interests include personnel scheduling, integer linear programming, and timetabling systems. His work bridges theoretical models with real-world applications, such as nurse rostering and compliance with labor regulations. Recent studies involve service planning processes and shift design optimization using advanced mathematical frameworks. Key contributions include a unified nurse rostering model and analyses of Dutch labor law inconsistencies. His research has been disseminated through peer-reviewed journals like Annals of Operations Research and conference proceedings such as PATAT. Active in academic discourse, he has presented on topics ranging from sports tournament scheduling to harmonious personnel scheduling strategies.

• Distributed Computing
• Theoretical Computer Science
• Parallel Algorithms
• +۴ مورد دیگر

Hsin-Hao Su is an Assistant Professor in the Department of Computer Science at Boston College. His research focuses on distributed computing through the lens of theoretical computer science, emphasizing parallelism, locality, communication, combinatorial optimization, symmetry breaking problems, and gossip-based algorithms. He completed his Ph.D. at the University of Michigan (2010–2015), advised by Seth Pettie, followed by a postdoctoral fellowship in Nancy Lynch's group at MIT (2015–2017). **Education:** Ph.D. in Computer Science, University of Michigan (2010–2015) Postdoctoral Associate, MIT (2015–2017) His work addresses foundational challenges in distributed systems, including efficient algorithms for shortest paths, graph decomposition, and task allocation. Notable contributions include advancing parallel and distributed approaches to clustering, matching, and quantile computations. Su has served on program committees for major conferences like ISAAC, ESA, and DISC, and held roles such as Workshop Chair (PODC 2021) and Student Travel Awards Organizer (PODC 2018). **Research Trends:** His articles emphasize algorithm design under distributed and parallel constraints, with recent focus on optimizing communication, reducing computational rounds, and bridging theoretical guarantees with practical efficiency. Topics span graph algorithms, approximation techniques, and bio-inspired methods.

Orhan Kaplanمشاهده پروفایل

مدرس

• Mathematics Education
• Algebra Teaching
• STEAM Education
• +۴ مورد دیگر

Dr. Orhan Kaplan serves as a Lecturer at Gaziantep University's Nizip Vocational School in the Marketing and Advertising Department since 2019, with prior appointment in the Mathematics Education Department at Nizip Faculty of Education (2021). Holding a doctorate in Curriculum and Instruction (Mathematics Education) from the University of Florida, he maintains active research in mathematics education with particular focus on algebra pedagogy, STEAM integration, and educational technology. His research interests encompass Mathematics Education , Algebra Teaching Methodologies , STEAM Curriculum Development , Educational Technology Integration , and Critical Thinking Development . Current projects include TÜBİTAK-funded research on 'Artificial Intelligence Applications in Mathematics Education' and comparative analyses of mathematics curricula across Türkiye and the United States. Recent publications reveal a strong emphasis on digital technology's impact on creative thinking (2025), ChatGPT integration in teacher education (2024), and critical analysis of algebra curricula (2025). His scholarly work spans quantitative studies using PISA data, qualitative analyses of teacher reflections, and historical examinations of NCTM's evolution regarding equity and assessment. Certificate of Appreciation for Master's Education (Turkish Consulate General, New York) Certificate of Appreciation for Upward Bound Program Services (University of Florida) Measurement and Evaluation Certificate (Gaziantep) As an educator, Kaplan teaches courses including Primary School Mathematics Teaching, Problem Solving in Mathematics, and Communication in Mathematics Classrooms. He has served on organizing committees for international symposia including BİLTEK-IV (2021) and NCTM Annual Meeting Exposition (2018), demonstrating active engagement in global mathematics education communities through his National Council of Teachers of Mathematics membership since 2012.