جست‌وجوی استاد و پژوهشگر

Jorge Cobbمشاهده پروفایل

دانشیار

• Network Protocols
• Quality of Service in Networks
• Mobile Computing
• +۶ مورد دیگر

Jorge Cobb is an Associate Professor in the Department of Computer Science at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. His research focuses on network protocols, quality of service (QoS), mobile computing, and distributed systems. He holds a Ph.D. from the University of Texas at Austin (1996), an M.A. (1989), and a B.S. (1987) from the University of Texas at El Paso. His research interests include design and implementation of network protocols, QoS in high-speed networks, mobile computing, and distributed systems. He has published extensively on topics like sensor networks, routing algorithms, and network stabilization. Recent work emphasizes fault-tolerant systems, barrier coverage in sensor networks, and SDN-based traffic engineering. Key awards include AT&T scholarships and fellowships from UT Austin. He has led projects such as CHAMPS (National Science Foundation) and contributed to optical network research. His teaching spans computer networks, database systems, and distributed systems at both undergraduate and graduate levels.

Michiel Smidمشاهده پروفایل

استاد

• Computational Geometry
• Geometric Networks
• Graph Algorithms
• +۳ مورد دیگر

Michiel Smid is a Professor in the School of Computer Science at Carleton University. He earned his Ph.D. from the University of Amsterdam and M.Sc. from Eindhoven University of Technology. His research focuses on Computational Geometry, Geometric Networks, Graph Algorithms, and Data Structures, with applications in manufacturing. He joined Carleton in 2001 as an Associate Professor and was promoted to Professor in 2004. Education: Ph.D. in Computer Science, University of Amsterdam (1989) M.Sc. in Mathematics and Computer Science, Eindhoven University of Technology (1986) Research Interests: Design and analysis of algorithms Spanner networks and geometric routing Graph theory and combinatorial optimization Applications of computational geometry in manufacturing Affiliations: Computational Geometry Lab at Carleton University Former positions include the Max-Planck-Institute for Computer Science (1990–1996) and the University of Magdeburg (1996–2001) Teaching: Winter 2025: COMP/MATH 3804 (Design and Analysis of Algorithms I) Focus on algorithmic theory and practical implementations Labs/Teams: Active in the Computational Geometry Lab, collaborating on geometric algorithms and spanner networks.

Avery Millerمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Distributed Algorithms
• Graph Theory
• +۵ مورد دیگر

Avery Miller is an Associate Professor in the Department of Computer Science at the University of Manitoba. His research focuses on theoretical computer science, particularly distributed algorithms, graph theory, and algorithmic lower bounds. He holds a Ph.D. from the University of Toronto, supervised by Faith Ellen, and has held postdoctoral positions at Tel Aviv University and Université du Québec en Outaouais. Education: Ph.D. in Computer Science, University of Toronto (Supervisor: Faith Ellen) M.Sc. in Computer Science, University of Toronto (Supervisor: Faith Ellen) B.Math. in Computer Science and Combinatorics & Optimization, University of Waterloo Research interests include distributed computing in anonymous networks, wireless networks, and graph burning. His work explores deterministic protocols, fault-tolerant systems, and the role of information in distributed algorithms. Recent projects involve reconfiguration of multisets, fast rendezvous in labeled networks, and cop-and-robber games on planar graphs. Publications highlight contributions to distributed algorithms, radio networks, and graph theory, including a best paper award at SPAA 2019. His work often bridges theoretical foundations with practical network challenges. Awards: Best Paper Award at SPAA 2019 Academic service includes roles as Organizing Chair of PODC 2021, Treasurer of PODC 2020, and committee memberships in SPAA, DISC, and other conferences. He reviews for top journals like ACM Transactions on Algorithms and Theoretical Computer Science. Teaching includes courses on automata theory, algorithms analysis, and distributed computing. He is part of the Geometric, Approximation, and Distributed Algorithms Lab at the University of Manitoba.

• Operations Research
• Game Theory
• Decision Theory
• +۵ مورد دیگر

Evangelos F. Magirou is a Professor of Operations Research at the Department of Informatics of Athens University of Economics and Business (AUEB). He holds a BS in Electrical Engineering from Princeton University (1971), an MSc in Decision and Control Sciences from Harvard University (1972), and a Ph.D. in Decision and Control Sciences from Harvard (1976). His research focuses on theoretical and applied Operations Research, with specializations in Finance, Shipping, and Energy Policy. He has held significant administrative roles, including Deputy Chairman of the Department of Informatics at AUEB and Chairman of the Hellenic Procurement Institute (1994–1997). Education: BS in Electrical Engineering, Princeton University (1971) MSc in Decision and Control Sciences, Harvard University (1972) Ph.D. in Decision and Control Sciences, Harvard University (1976) Research Interests: Operations Research applications in Finance, Shipping, and Energy Policy Optimization, Game Theory, and Decision Theory Algorithm design and dynamic optimization Recent Publications Trends: Magirou’s work spans theoretical contributions to graph theory, kernel enumeration, and default logic, alongside applied research in shipping logistics, energy policy, and financial modeling. His 2000s publications emphasize computational finance and policy iteration methods, reflecting a shift toward quantitative finance and algorithmic innovation. Awards and Grants: No specific awards are listed, but his extensive involvement in energy policy research and industry partnerships (e.g., Public Power Corporation) highlights impactful applied work. Teaching and Advising: He teaches courses in mathematics of finance, operations research, and algorithms. His academic leadership includes directing the MSc Program in Business Mathematics (jointly with the University of Athens). Labs/Teams: Collaborates with the Center for Economic Research at AUEB and has contributed to shipping industry studies through collaborative projects with industry experts.

Justin Goodsonمشاهده پروفایل

استاد

• Operations Research
• Transportation and Logistics
• Decision Analysis under Uncertainty
• +۳ مورد دیگر

Justin Goodson, Ph.D., is the Father Davis Professor in the Department of Operations and IT Management at Saint Louis University's Richard A. Chaifetz School of Business. He also serves as Program Director for the M.S. in Supply Chain Management program. His research focuses on developing methods for sequential decision-making under uncertainty, particularly in transportation and logistics contexts. Dr. Goodson holds a Ph.D. in Business Analytics (University of Iowa), an MBA, and three degrees from the University of Missouri (M.S. and B.S. in Industrial and Systems Engineering, and an MBA). His research interests include dynamic programming, stochastic optimization, and vehicle routing problems. Notable publications address electric vehicle routing, pandemic resource allocation, and gamification in logistics. He has received numerous awards, including the Transportation Science Paper of the Year (2023), Emerson Excellence in Teaching Award (2022), and multiple Chaifetz School Research Awards. Dr. Goodson is actively involved in professional organizations such as INFORMS Transportation Science and Logistics Society and INFORMS Computing Society. His work bridges theoretical advancements with practical applications in transportation systems and business analytics.

• Computer Networking
• Internet Measurement
• Network Security
• +۵ مورد دیگر

Benoit Donnet is a Professor at the Research Unit in Networking (RUN) within the Faculty of Applied Sciences at the University of Liège, Belgium. He has held this position since September 2011 and holds a Doctorate in Computer Science from University Paris 6, France. Professor Donnet's research spans multiple areas of computer networking and computer science education. His primary research interests include: Internet Measurement and Network Topology Discovery Network Security and Blockchain Analysis Network Protocol Design and Implementation Computer Science Education, particularly in introductory programming courses His recent publication trends show a dual focus on advanced networking research and innovative computer science education techniques. In networking, his work continues to advance Internet measurement methodologies, with recent publications on Bitcoin network analysis, IPv6 extension headers, and MPLS tunnel discovery. In education research, he has developed frameworks like CAFÉ 2.0 for automatic feedback in programming education and approaches to teaching abstraction skills through diagrammatic reasoning. Professor Donnet has mentored numerous students who have co-authored publications with him across both networking and education domains. His research has been supported by various grants enabling work on network measurement infrastructure, protocol development, and educational innovations. He leads research within the Research Unit in Networking (RUN), which focuses on Internet architecture, network measurement, and computer science education. The group maintains strong connections with the international networking research community and contributes to open-source network measurement tools.

Claudio Contardoمشاهده پروفایل

دانشیار

• Operations Research
• Logistics Management
• Vehicle Routing
• +۳ مورد دیگر

Claudio Contardo is an Associate Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on Operations Research, Logistics Management, Vehicle Routing, Location Analysis, Integer and Combinatorial Optimization, and Artificial Intelligence. He holds an ORCID identifier (0000-0001-7595-3904) and maintains an active academic presence through publications and collaborations. His work emphasizes optimization algorithms for complex systems, including transportation networks, biomedical logistics, and automated systems. Recent contributions include iterative exact algorithms for biomedical sample transportation and counterfactual explanations for k-Nearest Neighbors models. His research bridges theoretical optimization with practical applications in urban mobility, healthcare logistics, and AI explainability. Contardo’s methodologies often involve decomposition techniques (e.g., Dantzig-Wolfe, column generation) and integration of mathematical programming with data-driven approaches. Despite prolific output, no explicit awards or grants are listed in the provided materials. His CV and full publication list are accessible via the provided link.

• Theoretical Computer Science
• Algorithms
• Approximation Algorithms
• +۳ مورد دیگر

Kolliopoulos Stavros is a Professor in the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens. His work focuses on theoretical computer science, algorithms, and combinatorial optimization. He has contributed to scheduling theory, network optimization, and approximation algorithms. His research addresses problems like resource allocation, disjoint paths in graphs, and facility location. Key research interests include the design and analysis of algorithms for NP-hard problems, with applications to scheduling, network flow, and operations research. He explores techniques such as linear programming relaxations and greedy algorithms to achieve approximation guarantees. His recent publications (2023–2025) emphasize time-sharing scheduling, linear-time graph algorithms, and IoT resource management. Earlier work (1997–2013) includes foundational contributions to unsplittable flow, facility location, and selfish routing in networks. His work bridges theoretical insights with practical algorithmic solutions. Notably, he has developed FPTAS algorithms for tardiness minimization and established tight bounds for Lovász-Schrijver rank in facility location problems. His research often combines graph theory with optimization principles to solve real-world network and scheduling challenges.

Veronika Leschمشاهده پروفایل

استاد

• Self-aware Computing Systems
• Cyber-physical Systems
• Industry 4.0
• +۳ مورد دیگر

Veronika Lesch is a Professor and Head of the Applied Computer Science program at DHBW Mosbach. Previously, she served as a post-doctoral research group leader and doctoral researcher at the University of Würzburg's Chair of Computer Science II (Software Engineering Group). Her research focuses on self-aware computing systems, cyber-physical systems, and intelligent transportation logistics. She has supervised numerous theses on topics like platooning coordination and warehouse optimization. Notable awards include being a nominee for the 'Ingenieurinnen Preis Bayern' and recipient of the 'Würzburg Software Engineering Award'. Education: She holds a Bachelor's (2015) and Master's (2017) in Computer Science from the University of Würzburg, followed by a PhD and postdoc at the same institution. Professional roles include teaching coordination of MINT courses and supervision of software projects. Research interests span IoT, Industry 4.0 logistics, and autonomous systems optimization. Over 20 peer-reviewed publications since 2017 address challenges in adaptive systems, vehicle routing, and meta-optimization strategies. Active in reviewing for top journals/conferences like IEEE Transactions on ITS and ICPE. Supervised 15+ student theses (2018-2021) Developed FADE framework for adaptive distance estimation Contributed to Combench communication protocol benchmarking Labs/Teams: Previously part of the Software Engineering Group at Würzburg, now leading applied CS initiatives at DHBW Mosbach.

Balaji Raghavachariمشاهده پروفایل

استاد

• Design and analysis of algorithms
• Database design
• Approximation algorithms
• +۶ مورد دیگر

Balaji Raghavachari is a Professor in the Department of Computer Science at The University of Texas at Dallas (UTD), serving as Director of Graduate Studies. His primary affiliation is with the Erik Jonsson School of Engineering and Computer Science. His research focuses on algorithm design, database systems, combinatorial optimization, and network design. Specific areas include approximation algorithms for NP-hard problems, telecommunication networks, vehicle routing challenges, and bioinformatics applications like protein domain interaction analysis through the DOMINE database. Recent work includes path survivability in mesh networks, degree-constrained spanning trees, and buy-at-bulk network optimization. His publications span algorithmic theory (e.g., edge-connectivity approximations) to applied domains like telecommunication infrastructure and computational biology. He has held leadership roles in academic administration, including graduate program direction. No scientific awards are explicitly listed in the provided information. His advising activities and grant history are not detailed in this text, though his research indicates sustained involvement in algorithmic research and interdisciplinary projects.

Zhenhua Liuمشاهده پروفایل

استادیار

• Online Algorithm Design
• Convex Optimization
• Game Theory
• +۷ مورد دیگر

Zhenhua Liu is an Assistant Professor in the Department of Applied Mathematics and Statistics at Stony Brook University, with affiliations to the Department of Computer Science and the Smart Energy Technology Cluster. He joined Stony Brook in 2014 and was on leave in 2014-2015 for the ITRI-Rosenfeld Fellowship at Lawrence Berkeley National Laboratory. His research focuses on sustainable computing systems, cloud platforms for big data, energy management, and renewable energy integration. He holds a Ph.D. in Computer Science from the California Institute of Technology (Caltech), advised by Prof. Adam Wierman and Prof. Steven Low, and prior degrees from Tsinghua University and Peking University. His research interests span distributed algorithms, convex optimization, game theory, quantum networks, and energy-efficient computing. He develops theoretical frameworks and practical systems to address challenges in data centers, edge computing, and renewable energy integration. Notably, his work emphasizes rigorous analysis combined with system design to achieve real-world impact. His publications from 2023-2024 highlight advancements in distributed deep learning optimization, quantum entanglement routing, energy-aware edge computing, and sustainability metrics for data centers. These contributions reflect his interdisciplinary approach to solving complex problems at the intersection of computing, networking, and energy systems. Awards & Honors : Computerworld Honors Laureate, Best Paper Awards in International Green Computing Conference and ACM GreenMetrics, ITRI-Rosenfeld Fellowship, and multiple academic recognitions. Education : Ph.D. in Computer Science, Caltech (2014) M.S. in Computer Science & Technology, Tsinghua University (2009) B.E. in Measurement & Control, Tsinghua University (2006) B.S. in Economics, Peking University (2009)

Sanghyeok Choiمشاهده پروفایل

پژوهشگر

• Deep Learning
• Generative Models
• Probabilistic Inference
• +۶ مورد دیگر

Sanghyeok Choi is a PhD student in Informatics at the University of Edinburgh, supervised by Nikolay Malkin. His research focuses on deep learning, generative models, and probabilistic inference, with applications in AI Safety and AI for Science. His studies are funded by ARIA and CIFAR, supported by the Global Korea Scholarship. Education: PhD in Informatics (University of Edinburgh, 2025–current), MS in Industrial & Systems Engineering (KAIST, 2023–2025), BBA and BS in Industrial Engineering (Seoul National University, 2017–2023). Experience: Research Intern at Mila (2024–current), Undergraduate Researcher at KAIST and Seoul National University labs, and Machine Learning Research Engineer at MakinaRocks. Research Interests: Generative Flow Networks, structure learning, and reinforcement learning with applications in biological sequence design, molecular optimization, and HVAC systems. His work combines deep learning with combinatorial optimization to solve NP-hard problems using AI-driven frameworks. Scientific Trends: Recent publications emphasize GFlowNets for combinatorial/molecular optimization, transformer-based routing solutions, and reinforcement learning in energy systems. Key themes include AI for science, equity-aware algorithms, and genetic-guided neural architectures. Scientific Awards: Global Korea Scholarship (2025) Bang Il-Young Scholarship (2018–2021) 1st Place in DACON AI Competitions (2020) Open Source Contributions: TorchGFn (2024–current) RL4CO benchmark (2023–2025)

• Mathematics
• Optimization
• Problem Solving

Bradley W. Jackson is a Professor in the Department of Mathematics at San José State University. He holds a PhD from the University of Maryland College Park (1977). His research focuses on mathematical optimization and problem-solving, with publications addressing complex puzzles like Ringel's earth-moon problem and Gale's jeep problem. These works explore resource allocation and efficiency in theoretical scenarios. Research Focus: Optimization algorithms, transportation logistics, and combinatorial mathematics. Key Publications: Analyzes spatial resource distribution challenges through mathematical modeling.

Edward F Schmeichelمشاهده پروفایل

استاد

• Graph Theory
• Complexity of Algorithms
• Computational Mathematics
• +۳ مورد دیگر

Edward F. Schmeichel is a Professor in the Mathematics Department at San José State University. His research focuses on Graph Theory and Complexity of Algorithms, with a strong emphasis on algorithm design, network optimization, and computational complexity. He holds a Ph.D. from Northwestern University (1974), an M.A. from Northwestern (1968), and a B.A. from Grinnell College (1967). His work spans theoretical and applied mathematics, including topics like NP-hard problem analysis, graph orientation, and time-varying network optimization. Notable contributions include studies on dominating cycles, star arboricity, and approximation algorithms for facility allocation. His publications reflect interdisciplinary approaches to discrete mathematics and computational challenges. Dr. Schmeichel’s articles explore themes such as polynomial algorithms for NP-hard hypotheses, Voronoi partitions in network location theory, and the Jeep problem’s optimization. His research bridges pure mathematics with practical applications in operations research and distributed systems. He currently serves at SJSU with office hours on TTH 10:00-10:30, 1:30-2:00, and 5:00-5:30. No scientific awards are explicitly listed in the provided materials.

Kenan Zhangمشاهده پروفایل

استادیار

• Urban Transportation Systems
• Operations Research
• Transportation Engineering
• +۶ مورد دیگر

Dr. Kenan Zhang is a Tenure Track Assistant Professor at EPFL's School of Architecture, Civil and Environmental Engineering, leading the Laboratory for Human-Oriented Mobility Eco-system (HOMES). She holds dual roles in teaching Civil Engineering and contributes to the EDCE and SGC programs. Her research focuses on mathematical modeling, optimization, and operations management of urban transportation systems, with emphasis on emerging mobility services and technologies. Education: BSc in Civil Engineering, Tsinghua University MSc in Architecture-Engineering-Construction Management (AECM), Carnegie Mellon University PhD in Civil Engineering (Transportation System Analysis & Planning) and second MSc in Statistics, Northwestern University Postdoctoral Researcher at ETH Zurich Research Interests: Urban transportation systems, optimization algorithms, sustainable mobility, traffic flow theory, and emerging technologies like autonomous vehicles and MaaS platforms. Her work integrates data-driven approaches with theoretical models to address real-world challenges in urban mobility. Awards & Recognition: CEE Rising Star Award COTA Best Dissertation Award TRB Committee Membership (ACP 50) Editorial Advisory Board, Transportation Research Part C Teaching & Advising: Supervises PhD students Liu Xuhang & Ma Xinyu. Teaches courses on urban transport systems, transportation network modeling, and seminars in civil/environmental engineering. Active in curriculum development for interdisciplinary mobility studies. Labs & Collaborations: Directs HOMES Lab exploring human-centric mobility ecosystems. Engages in international collaborations and policy analysis for sustainable transport solutions.