جست‌وجوی استاد و پژوهشگر

Adam Elmachtoubمشاهده پروفایل

دانشیار

• Operations Research
• Machine Learning
• Revenue Management
• +۵ مورد دیگر

Adam Elmachtoub is an Associate Professor in the Department of Industrial Engineering and Operations Research at Columbia University, where he holds affiliations with the Data Science Institute and serves as an Amazon Visiting Academic. He earned his B.S. in Operations Research from Cornell University and his Ph.D. in Operations Research from the Massachusetts Institute of Technology (MIT), followed by a postdoctoral position at IBM's T.J. Watson Research Center focusing on Smarter Commerce technologies. His research bridges machine learning, analytics, and operations, with dual specializations: (1) developing ML-driven personalization methods for retail, logistics, and travel industries; and (2) creating novel models for revenue and supply chain optimization in e-commerce and service systems. His work emphasizes practical applications of optimization under uncertainty, data-driven decision-making, and algorithmic fairness. Elmachtoub's publication record demonstrates consistent focus on pricing analytics, revenue management, and operational efficiency, with recent work exploring fairness constraints, reusable resources, and pandemic-responsive systems. His research integrates stochastic modeling, statistical learning, and economic theory to solve complex industrial problems. Notable scientific recognitions include: NSF CAREER Award for foundational contributions to data-driven optimization IBM Faculty Award for industry-relevant research 1st place in INFORMS JFIG Paper Competition Great Teacher Award from the Society of Columbia Graduates Forbes 30 Under 30 in Science honor He maintains active research funding through NSF and IBM collaborations. While specific student advisees are unnamed in available sources, his teaching recognition suggests significant mentoring activities. No explicit details regarding dedicated labs or research teams are documented.

John Doyleمشاهده پروفایل

استاد

• Control Theory
• Systems Biology
• Neural Networks
• +۳ مورد دیگر

John Doyle is a Professor at the California Institute of Technology, affiliated with the Division of Engineering and Applied Science and the Control and Dynamical Systems department. His research focuses on theoretical foundations of complex networks across technology, biology, neuroscience, ecology, and social systems, integrating control theory, computing, communications, and multiscale physics. He emphasizes layered architectures that balance efficiency, adaptability, and robustness in systems like the brain and engineered networks. Doyle teaches advanced courses such as CDS 131 (Linear Systems Theory) and CDS 231 (Robust Control Theory), reflecting his expertise in control systems. His work has received recognition through awards like the Axelby Outstanding Paper Award and the Test of Time Paper Award. Notable students include Ray Sun, Ethan Pronovost, and Louise Schul, who have received Henry Ford II Scholar Awards. His research explores how biological and technological systems achieve performance despite constraints like limited resources and noisy communication. Key areas include sensorimotor control, immune system dynamics, and distributed control architectures. Collaborations span fields from synthetic biology to cybersecurity, emphasizing interdisciplinary problem-solving.

Kevin Riehlمشاهده پروفایل

مدرس

• Multi agent systems
• Resource allocation in networks
• Game theory & control
• +۴ مورد دیگر

Kevin Riehl is a Lecturer at the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich, specializing in transportation systems and fairness mechanisms. He is affiliated with the Gruppe Strassenverkehrstechnik and holds a Master's degree in Genetics and Bioinformatics from the University of Cambridge and degrees in Industrial Engineering from Darmstadt University of Technology. Education: 2020–2021: Master's in Genetics and Bioinformatics, University of Cambridge 2018–2020: MSc Industrial Engineering with IT, Darmstadt University of Technology 2014–2017: BSc Industrial Engineering with IT, Darmstadt University of Technology His research focuses on multi-agent systems, resource allocation fairness, and karma-based mechanisms for equitable traffic management. Notable contributions include work on reproducibility in transportation simulations and karma economies for sustainable urban mobility. He has published extensively in journals like European Transport Research Review and npj Sustainable Mobility and Transport . Recent projects include BikeZ for cycling service modeling and microscopic traffic simulation courses. His work bridges computer science, economics, and transportation engineering to address systemic fairness in infrastructure.

Éva Tardosمشاهده پروفایل

استاد

• Algorithmic Game Theory
• Algorithm Design
• Applied Mathematics
• +۳ مورد دیگر

Éva Tardos is the Jacob Gould Schurman Professor at Cornell University, affiliated with the Department of Mathematics and multiple colleges including the Cornell Ann S. Bowers College of Computing and Information Science, College of Arts and Sciences, and College of Engineering. Her research focuses on algorithm design, particularly in algorithmic game theory, networks, and combinatorial optimization. She explores mechanisms for selfish users, network efficiency, and distributed systems. Her work bridges theoretical computer science and economics, addressing challenges like congestion games, mechanism design, and social network influence. Key contributions include analyzing selfish routing's inefficiency, bounding equilibrium inefficiencies, and designing approximation algorithms for facility location and network design problems. Tardos collaborates extensively with top researchers in computer science and mathematics, contributing foundational insights into modern algorithmic theory. Research interests include algorithmic game theory , network optimization , mechanism design , and approximation algorithms . Recent publications emphasize social network dynamics, collusion effects in congestion games, and fair resource allocation strategies. Her work has practical applications in traffic routing, telecommunications, and distributed computing systems. While no specific awards are listed, her sustained contributions to theoretical computer science have established her as a leading figure in the field. Advising and mentoring are integral to her role, though specific advisee names are not documented here. She is actively involved in Cornell’s academic and research initiatives across multiple interdisciplinary domains.

Ramesh Johariمشاهده پروفایل

استاد

• Online Platforms Design
• Economic Analysis
• Machine Learning
• +۳ مورد دیگر

Ramesh Johari is a Professor of Management Science and Engineering and Professor (by courtesy) of Electrical Engineering at Stanford University. He holds affiliations with the Institute for Human-Centered Artificial Intelligence (HAI), Precourt Institute for Energy, and the Institute for Computational and Mathematical Engineering (ICME). As Associate Director of Stanford Data Science and Co-Director of the Stanford Causal Science Center, he leads initiatives in data-driven research and causal inference. His research focuses on online platforms, statistical/machine learning, and healthcare technology, with contributions to diabetes care optimization and algorithmic decision-making. Education: PhD in Electrical Engineering and Computer Science from MIT (2004). His work integrates economics, operations research, and computer science to address challenges in platform design and healthcare systems. Notable achievements include developing the Timely Interventions for Diabetes Excellence (TIDE) platform, improving outcomes for type 1 diabetes patients through remote monitoring and algorithmic prioritization. Key research areas include: design of digital health platforms, economic analysis of online markets, and scalable healthcare solutions. His recent studies emphasize equitable access to CGM technology and precision medicine in diabetes care. Scientific Awards: Over 11 honors, including the George E. Nicholson Student Paper Competition (2003), ACM Doctoral Dissertation Award (2004), and NSF CAREER Award (2007). Advising: Mentors doctoral and master’s students in healthcare technology, data science, and operations research. Serves on editorial boards and program committees for top conferences in his field. Current roles include partial leave from January 2025 to June 2025. Labs/Teams: Active in the Society and Algorithms Lab (SOAL) and collaborates with Stanford’s interdisciplinary healthcare initiatives. His work bridges academic research and real-world applications in technology and medicine.

Balaji Prabhakarمشاهده پروفایل

استاد

• Computer Networks
• Data Center Networks
• Societal Networks
• +۵ مورد دیگر

Balaji Prabhakar is a Professor of Electrical Engineering and Computer Science at Stanford University. He holds the VMware Founders Professorship in Computer Science and is affiliated with the School of Engineering. His research focuses on computer networks, including data center networks, societal networks (transportation, energy, recycling), and network algorithms. He has pioneered congestion control mechanisms like QCN and DCTCP, and developed incentive systems to reduce traffic congestion through behavioral 'nudges.' Prabhakar's work integrates principles from computer networks with societal infrastructure challenges. Key areas include energy-efficient transmission, randomized algorithms for scheduling, and network measurement architectures like Counter Braids. He has received numerous accolades, including the IEEE Innovation in Societal Infrastructure Award and the Rollo Davidson Prize. His teaching includes courses on probabilistic systems analysis, network algorithms, and incentive mechanisms. Current and former students have contributed to foundational work in data center networking and societal infrastructure optimization. His lab collaborates with industry partners like VMware and Infosys, applying theoretical insights to real-world systems.

Will Evansمشاهده پروفایل

استاد

• Computational Geometry
• Graph Drawing
• Information Theory
• +۳ مورد دیگر

Will Evans is a Professor in the Department of Computer Science at the University of British Columbia (UBC). He specializes in computational geometry, graph drawing, information theory, data compression, and algorithms. His research focuses on geometric algorithms, graph visualization, and theoretical computer science applications. Recent work emphasizes optimization of algorithms for moving objects, congestion control, and geometric representations. His publications span topics from scheduling strategies to visualization techniques for complex data structures. While no formal awards or grants are listed, his extensive list of peer-reviewed publications underscores his contributions to the field. Advising details and lab affiliations are not explicitly mentioned in the provided materials.

Mehrdad Asadiمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Robotics
• Intelligent Transportation Systems
• +۷ مورد دیگر

Mehrdad Asadi is a Research Fellow at the Vrije Universiteit Brussel (VUB), affiliated with the Department of AI and Robotics within the School of Informatics and Applied Informatics. His research focuses on advancing AI and robotics with an emphasis on safety, explainability, and real-world applications in transportation systems. He holds post-doctoral scholarships at Federated Labs AI and Robotics and the Informatics and Applied Informatics unit. Research Interests: - Development of trustworthy AI systems resistant to adversarial attacks - Optimization algorithms for multi-agent robotics and transportation networks - Explainable AI methodologies for ethical and transparent decision-making - Heuristic approaches for real-time system coordination - Integration of human preferences in automated systems Collaborations: - Active participation in international conferences like GECCO and eXplainable AI workshops - Co-organized events including 'Interactive eXplainable AI - Theory and Practice' (2025) - Cross-disciplinary projects with institutions like IEEE and academic consortia Key Contributions: - Developed the SPATIAL architecture for monitoring AI inference capabilities - Pioneered heuristic methods for intelligent transportation systems - Published 9 peer-reviewed works between 2021-2025 with a focus on safety-critical applications

Majid Norooziمشاهده پروفایل

استادیار

• Statistical Network Models
• Statistical Machine Learning
• Stochastic Block Models
• +۳ مورد دیگر

Majid Noroozi is an Assistant Professor in the Department of Mathematical Sciences at the University of Memphis since August 2021. Previously, he served as a William Chauvenet Postdoctoral Lecturer at Washington University in St. Louis (2020–2021) and held roles as a Graduate Research Assistant and Teaching Assistant at the University of Central Florida (2014–2020). He also taught at Azad University, Karaj Branch, Iran (2010–2014). Education includes a Ph.D. in Applied Mathematics from the University of Central Florida (2020), an M.S. from the same institution (2016), and an M.S. from K. N. Toosi University of Technology (2009). His research focuses on Statistical Network Models and Statistical Machine Learning , with specialties in stochastic block models, subspace clustering, and network analysis. Recent work includes advancements in diverse multiplex network models and sparse subspace clustering techniques. Key publications span journals like the Journal of the Royal Statistical Society Series B , Journal of Machine Learning Research , and Journal of Multivariate Analysis . He has also contributed to conferences such as the ERCIM International Conference on Computational and Methodological Statistics. Awards: Multiple teaching awards from the University of Central Florida (2018–2019). Advising: Supervised two Master’s students, including Sasi Kumar Jaggarapu (2023) and Pravallika Pasala (2022). Service: Roles include Local Arrangements Chair for the Mid-South Data Science Conference (2024) and committee memberships in curriculum development and academic advising. He is actively involved in the academic community, presenting at institutions like St. Jude Children’s Research Hospital and the University of California, San Diego.

Srinivasan Seshanمشاهده پروفایل

استاد

• Distributed Systems
• Mobile Computing
• Networking
• +۱ مورد دیگر

Srinivasan Seshan is Joseph Traub Professor of Computer Science and Department Head of the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research focuses on network protocols, distributed network applications, and next-generation network architectures. His primary research explores next-generation network architectures like the eXpressive Internet Architecture (XIA) for robust internet evolution and video content delivery optimization. A secondary focus examines systems challenges in mobile computing, including power-efficient data collection, scalable infrastructure design, and privacy management for smartphone-based environmental observations. As a prominent researcher in distributed systems, Seshan has made significant contributions to transport protocols, sensor networking, and firewall design. His publications demonstrate consistent focus on network architecture innovation and mobile systems optimization.

David Clarkمشاهده پروفایل

پژوهشگر

• Internet Architecture
• Cybersecurity
• Network Policy
• +۳ مورد دیگر

David Clark is a Senior Research Scientist at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Lab (CSAIL) , where he has been instrumental in shaping internet architecture since the 1970s. He served as Chief Protocol Architect (1981-1989) and chaired the Internet Activities Board, focusing on the intersection of technology, economics, and policy. Research Interests : His work spans internet security, large-scale network measurement, architectural redesign, and policy analysis for mitigating malicious applications. Recent projects include Trust Zones, data-driven routing security, and congestion inference frameworks like Jitterbug. Scientific Contributions : Coined foundational principles for internet architecture Developed tussle framework for network protocol design Advocated for policy-aware network research Scientific Recognition : Fellow of the National Academy of Engineering Fellow of the American Academy of Arts and Sciences Student Mentorship : Supervised 25+ graduate theses on topics ranging from routing security to network economics and quantum computing, including advisors for key studies on BGP hijacking and broadband policy. Leadership Roles : Leads MIT's Internet Policy Research Initiative and has chaired the Computer Science and Telecommunications Board of the National Academies, influencing national and international standards for internet governance.

Fanyin Zhengمشاهده پروفایل

استادیار

• Empirical Operations Management
• Business Analytics
• Applied Econometrics
• +۴ مورد دیگر

Fanyin Zheng is an Assistant Professor at Imperial College Business School, specializing in Management Science and Business Analytics. She previously held an Assistant Professor position at Columbia Business School. Her research focuses on empirical operations management, business analytics, and applied econometrics, with an emphasis on decision-making in complex service systems like healthcare operations and platform markets. She earned her PhD from Harvard University, Cambridge, United States. Her research explores how individuals and firms leverage data-driven strategies in dynamic environments, particularly in healthcare systems and two-sided platforms. She serves as an Associate Editor for Management Science and Manufacturing & Service Operations Management . Her work addresses challenges such as resource allocation in hospitals, congestion management in transportation networks, and optimal design of marketplaces. Key themes in her publications include healthcare resource optimization, customer preference modeling in transportation systems, and structural estimation of intertemporal externalities in ICU admissions. She actively contributes to advancing methodologies in causal inference and network analysis for complex operational systems.

Jean-Baptiste Jeanninمشاهده پروفایل

استادیار

• Verification of cyber-physical systems
• Logics and semantics of programming languages
• Programming with coinductive types
• +۳ مورد دیگر

Jean-Baptiste Jeannin is an Assistant Professor in the Department of Aerospace Engineering at the University of Michigan — Ann Arbor, leading the MARVL group. He is also affiliated with the departments of Computer Science and Engineering and Robotics. His research focuses on formal verification of cyber-physical systems, logics and semantics of programming languages, and coinductive programming types. He holds a Ph.D. in Computer Science from Cornell University (2013) and a Diplôme d'Ingénieur from École polytechnique (2007), with prior roles at Samsung Research America and Carnegie Mellon University. His research interests include verification of aerospace applications, program logics, and formal methods applied to robotics and distributed systems. Notable work includes formally verified algorithms for collision avoidance, network consensus protocols, and numerical methods. He teaches courses such as AERO 552 (Aerospace Information Systems) and EECS 590 (Advanced Programming Languages). Jeannin's recent publications emphasize formal verification in hybrid systems, rounding error analysis, and hardware-software co-design. His work bridges theoretical foundations with practical applications in autonomous systems, cybersecurity, and computational physics. Collaborations include projects on certified approximations of mathematical functions and verified distributed system protocols.

• Distributed Algorithms
• Blockchain Technology
• Transactional Memory
• +۵ مورد دیگر

Costas Busch is a Professor and Department Chair in the Department of Computer Science at Georgia State University's School of Computer and Cyber Sciences. He holds a Ph.D. (2000) and M.S. (1998) in Computer Science from Brown University. His research focuses on distributed algorithms, blockchain technology, transactional memory, and sensor networks. He has authored numerous publications in top-tier conferences and journals. Education: Ph.D., Computer Science, Brown University (2000) M.S., Computer Science, Brown University (1998) Research interests include distributed systems, consensus protocols, and algorithmic optimization. He serves as an editor for Forensic Science International: Digital Investigation and MDPI Algorithms . Active in governance roles, he chairs the Faculty Search Committee and Faculty Affairs Committee, and participates in promotion committees. His work bridges theoretical computer science with practical applications in distributed computing and blockchain scalability. Notable contributions include advancements in blockchain sharding, transactional memory scheduling, and fault-tolerant distributed systems. His recent work explores poly-logarithmic universal Steiner trees and adversarial transaction generation resilience in blockchain architectures. Service & Leadership: Editorial roles at 2 leading journals Committee leadership in faculty governance Active participation in international conferences like IEEE Blockchain

Rolf H. Möhringمشاهده پروفایل

استاد

• Combinatorial Optimization
• Graph and Network Algorithms
• Operations Research
• +۶ مورد دیگر

Prof. Rolf H. Möhring is a Professor at the Department of Mathematics, Faculty II – Mathematics and Natural Sciences, Technical University of Berlin. He specializes in Combinatorial Optimization, Graph and Network Algorithms, and Operations Research with applications in industrial and transportation systems. His research bridges theoretical foundations and practical implementations, addressing challenges in scheduling, distributed computing, and algorithmic game theory. Key research interests include graph algorithms, project scheduling optimization, and robust optimization methodologies. Notable contributions span network flow analysis, traffic equilibrium design, and logistics optimization in container terminals and shipping routes. Awards: 2025 Research.com Mathematics in Germany Leader Award, 2010 EURO Gold Medal. Publications: Over 127 papers with 16,279 citations in Computer Science and 113 papers with 15,733 citations in Mathematics. His work frequently explores combinatorial structures, invariant theory, and practical applications in distributed systems. His advising focuses on PhD students in combinatorial optimization and algorithmic theory, with contributions to the Mathematics Genealogy Project. Collaborations include industrial projects like Kiel Canal ship traffic optimization and AGV routing in container terminals, emphasizing real-world problem-solving through mathematical frameworks.