جست‌وجوی استاد و پژوهشگر

Sibel Alumur Alevمشاهده پروفایل

دانشیار

• Supply Chain Management
• Logistics Network Design
• Operations Research
• +۴ مورد دیگر

Sibel Alumur Alev is an Associate Professor and Associate Chair of Graduate Studies at the University of Waterloo. Her research focuses on logistics network design, hub location optimization, and sustainable transportation systems. She actively contributes to the fields of operations research and supply chain management, with a strong emphasis on addressing uncertainty in network design and strategic infrastructure planning. Her work spans applications in autonomous mobility systems, electric vehicle charging infrastructure, healthcare logistics, and pandemic response. She has published extensively on hub-and-spoke network models, reverse logistics for environmental sustainability, and multi-period resource allocation strategies. Notable areas of interest include the integration of stochastic and robust optimization methodologies into real-world logistics challenges. Dr. Alev’s research also bridges academic and industrial needs, addressing practical problems such as optimal testing center locations during pandemics and strategic freight hub expansions. Her contributions have been featured in peer-reviewed journals and conference proceedings, reflecting her commitment to advancing both theoretical and applied aspects of logistics and operations research.

Yuan Zhongمشاهده پروفایل

دانشیار

• Applied Probability
• Stochastic Systems
• Operations Management
• +۷ مورد دیگر

Yuan Zhong is an Associate Professor of Operations Management at the University of Chicago Booth School of Business . He previously held positions as an Assistant Professor at Columbia University’s Department of Industrial Engineering and Operations Research and was a Postdoctoral Scholar at UC Berkeley’s Computer Science Department. Education: PhD in Operations Research, MIT (2012) MA in Mathematics, Caltech (2008) BA in Mathematics, University of Cambridge (2006) His research focuses on applied probability and stochastic system design , with applications in cloud computing , supply chain management , and e-commerce logistics . Recent work explores multi-period production systems and dynamic resource allocation in data centers and healthcare operations . Recent publications analyze cloud value chains , sparse graph design for delivery networks, and process flexibility in manufacturing. He has contributed to journals like Operations Research , Annals of Applied Probability , and Stochastic Systems . Scientific Awards: 2012 Kenneth C. Sevcik Outstanding Student Paper Award Best Student Paper Award at ACM Sigmetrics (2012) He teaches courses in business process fundamentals and queueing theory , with a future schedule including Operations Management: Business Process Fundamentals (2025–2026). No explicit student advising list was provided.

Justin P. Haldarمشاهده پروفایل

استاد

• Computational Imaging
• Inverse Problems
• Magnetic Resonance Imaging (MRI)
• +۳ مورد دیگر

Justin P. Haldar is a Professor in the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California (USC), with a joint appointment in the Department of Biomedical Engineering. He co-directs the Biomedical Imaging Group and serves as Director of the Signal and Image Processing Institute. His affiliations include the Dornsife Cognitive Neuroscience Imaging Center, the Brain and Creativity Institute, and the Dynamic Imaging Science Center. Education : B.S. and M.S. in Electrical Engineering (2004, 2005), Ph.D. in Electrical and Computer Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on computational imaging, inverse problems, and magnetic resonance imaging (MRI), with an emphasis on constrained image reconstruction, parameter estimation, and novel data acquisition strategies. His work combines physical modeling, high-dimensional signal structures, and fast computational algorithms to address MRI's limitations in speed, noise, and cost. Recent publications analyze challenges like the 'hidden noise' problem in MR reconstruction (2025) and innovations in dynamic imaging. His research has enabled faster MRI exams and next-generation imaging techniques by exploiting dimensionality's 'blessings' while mitigating its 'curses.' Scientific awards : NSF CAREER Award (2014) IEEE ISBI Best Paper Award (2010) IEEE EMBC First-Place Student Paper Award Haldar's leadership roles include Chair of the IEEE Signal Processing Society's Technical Committee on Computational Imaging and editorial positions at IEEE Transactions on Computational Imaging and Magnetic Resonance in Medicine . He actively mentors students and develops novel MRI approaches at USC's Michelson Center for Convergent Bioscience.

Guido Perboliمشاهده پروفایل

استاد

• Operations Research
• Logistics
• Last-mile Delivery
• +۹ مورد دیگر

Guido Perboli is a Full Professor in the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin, where he also serves as Logistics Coordinator and Project Coordinator for activities supporting relationships with government bodies. He is a member of the Interdepartmental Center CARS@PoliTO (Center for Automotive Research and Sustainable Mobility) and serves as Director of the ICT for City Logistics and Enterprises (ICElab@Polito) research center, which he founded in 2016. His research interests span a broad range of topics including Operations Research, Logistics, Last-mile Delivery, Sustainable Logistics, Combinatorial Optimization, Stochastic Programming, Business Development, and Lean Business methodologies. His work particularly focuses on City Logistics, Green Logistics, and the application of emerging technologies like Blockchain and AI in supply chain management. He has developed GUEST, a Lean Business methodology for innovation processes from early idea definition to implementation. Professor Perboli's recent publications demonstrate a strong focus on urban logistics, last-mile delivery optimization, blockchain applications in supply chains, and the integration of AI techniques in transportation systems. His work shows an increasing trend toward interdisciplinary research that combines optimization methods with emerging technologies to address sustainable urban mobility challenges. Professional Recognition: CASE Best Paper award from IEEE Conference on Automation Science and Engineering (2011) Effective member of INFORMS (2019-present) Effective member of EURO (1995-present) Effective member of AIRO (1995-present) Associate Editor for Journal of Applied Research and Technology (2020-present) Associate Editor for Sustainability (2018-present) Professor Perboli actively advises PhD students and has supervised numerous research projects, including EU-funded initiatives like SINFONICA, HESTER, and 5G-LOGINNOV. He serves as Scientific Director for multiple commercial research projects focused on blockchain, IoT, and AI applications in logistics. Beyond academia, he is Chief Scientific Officer of Arisk S.p.A., a fintech company specializing in business crisis prediction using AI and machine learning. His research group, ICElab@Polito, focuses on two main areas supporting urban growth: logistics and enterprises. The center collaborates with numerous companies including Amazon, DHL, and FCA, addressing real-world challenges in urban logistics and supply chain management through innovative research approaches.

• Management Accounting
• Performance Measurement
• Incentive Contracts
• +۳ مورد دیگر

Prof. Dr. Jörg Budde is a faculty member at the University of Bonn , affiliated with the Department of Economics . His academic rank is Professor , and he is actively engaged in research related to managerial accounting, performance measurement, and incentive contracts. Institute: Institute for Applied Microeconomics Email: joerg.budde@uni-bonn.de Contact: +49 228 73-9247 Budde’s research focuses on incentive design and performance evaluation in agency models, particularly under conditions of limited liability and distorted metrics. His work explores topics such as bonus pools , rank-order tournaments , and contractual frameworks that balance risk and incentive alignment. His publications span journals like Journal of Economics , Management Accounting Research , and Journal of Mathematical Economics , with a thematic emphasis on agency theory , information systems , and organizational behavior .

• Business Administration
• Operations Research
• Supply Chain Management
• +۶ مورد دیگر

Prof. Dr. Julia Rieck is a Full Professor of Business Administration at the University of Hildesheim , leading the Department of Business Administration and Operations Research within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science. As Dean of the Faculty , she oversees academic programs, quality management, and research initiatives. Her roles include academic advising for the Business Information Systems (B.Sc./M.Sc.) programs and active participation in examination boards and quality committees. Education: PhD in Political Science (Dr. rer. pol.) with summa cum laude (2008), Habilitation at Clausthal University of Technology (2014), and studies in Business Mathematics (Diploma, University of Hamburg, 2003) and Mathematics (Georg-August-University Göttingen, 2000). Research: Focuses on Operations Research , Supply Chain Management , Project Planning , and Logistics . Her work integrates mathematical modeling , machine learning , and real-world applications , particularly in disaster response , dynamic transportation , and sustainable e-commerce . Projects: Leads third-party funded initiatives like "IT für die sorgende Gesellschaft" (AI in healthcare/social sectors) and contributes to the HULLS real-lab (AI in aging societies). Collaborates with regional companies (e.g., Youco, ADITUS) and institutions (HAWK, University of Hannover). Teaching: Emphasizes practical application through case studies, industry partnerships, and the IT-Speed Dating event for student-company connections. Her courses cover project resource planning , logistics , and digital transformation . Labs & Teams: Active in the Institute of Business Administration & Business Information Systems , contributing to the KET Kompetenzwerkstatt (entrepreneurship support) and interdisciplinary teams in AI and sustainability research.

Andreas S. Schulzمشاهده پروفایل

استاد

• Mathematical Optimization
• Algorithm Design
• Operations Research
• +۵ مورد دیگر

Prof. Dr. Andreas S. Schulz is a faculty member at Technische Universität München (TUM), holding a chair in the Department of Mathematics and the Department of Business and Economics. He previously served as the Patrick J. McGovern Chair of Management and Professor of Mathematics at MIT. His research focuses on mathematical optimization, algorithm design, and their applications in logistics, production, healthcare systems, and online advertising. He has held visiting professorships at institutions such as the Sauder School of Business (UBC) and ETH Zurich. Prof. Schulz’s research bridges operations research, theoretical computer science, and economics. He develops analytical methods to solve complex decision-making problems in business, including scheduling, resource allocation, and network optimization. A key interest is applying mathematical approaches to enhance healthcare delivery and system efficiency. Education: PhD in Operations Research (MIT), prior academic roles at MIT and visiting institutions. Key Achievements: Alexander von Humboldt Professorship (2014), Humboldt Research Award (2010), Glover-Klingman Prize (2006). Research Themes: Robust optimization, approximation algorithms, scheduling theory, and algorithmic game theory. His publications span topics like integer programming, optimal transport, and congestion games. He collaborates across disciplines, emphasizing practical applications of theoretical insights.

• Convivial informatics
• Digital sustainability
• Participatory design
• +۹ مورد دیگر

Aurélien Tabard is an Associate Professor at LIRIS (Laboratoire d'InfoRmatique en Image et Systèmes d'information), a joint research unit between Université Claude Bernard Lyon 1 and CNRS. His academic career spans over a decade with positions at prestigious institutions including the IT University of Copenhagen, University of Munich, and INRIA. He completed his PhD at Université Paris-Sud in 2009, focusing on supporting lightweight reflection on familiar information. Tabard's research centers on convivial informatics, exploring alternatives to computational platforms that consider digital limits and foster sufficiency, maintenance, autonomy, and durability. His work emphasizes participatory approaches to designing resilient infrastructures and tools for rapid prototyping by non-designers. He investigates software obsolescence, digital sufficiency, and the materiality of data physicalization through projects like Limites Numériques and PC4-Congrats within PEPR eNSEMBLE. His recent publications reveal strong trends toward sustainability in computing, examining how digital systems can be designed with longevity and environmental impact in mind. There's a clear progression from technical HCI research toward broader societal implications of digital technology, particularly focusing on how users experience aging devices and negotiate digital limits collectively. Honorable mention award for 'Obsolescence Paths: living with aging devices' at ICT4S 2023 Student Lea Mosesso received the prize for best MSc thesis from Conseil National du Numérique Tabard actively mentors PhD students including Maëva Calmettes (working on skill and expertise sharing), Edlira Nano (studying software obsolescence), and Lea Mosesso (researching digital sufficiency). He collaborates extensively with researchers across France and internationally, particularly with Inria Lille where he spent a sabbatical in 2023. His current projects involve understanding software obsolescence, digital sufficiency, and the interplay between micro design decisions and systemic forces shaping ICT. He leads the Limites Numériques team, which investigates how to design computational platforms that take digital limits into consideration. The team recently developed an exhibit on water in the digital sector that will travel to Rhône-Alpes in spring 2025. Tabard also contributes to participatory design tools and critical approaches to participatory design, working with colleagues like Nolwenn Maudet, Thomas Thibault, and Romain Rouvoy.

• Collective Intelligence
• Organizational Design
• Future of Work
• +۳ مورد دیگر

Thomas W. Malone is the Patrick J. McGovern Professor of Management at the MIT Sloan School of Management. He holds joint appointments as Professor of Information Technology and Professor of Work and Organizational Studies. As founding director of the MIT Center for Collective Intelligence, he leads pioneering research on how people and computers can connect intelligently. Previously, he founded the MIT Center for Coordination Science and co-directed the MIT Initiative on 'Inventing the Organizations of the 21st Century'. His teaching focuses on organizational design, IT, and leadership. His research examines how new organizations leverage information technology, with groundbreaking predictions about electronic business in 1987. Major works include the influential books The Future of Work (2004) and Superminds (2018). Research areas span: Collective Intelligence: Designing systems combining human and machine intelligence Organizational Structure: Decentralization, coordination, and future work models Climate Solutions: Crowdsourcing through Climate CoLab AI Implications: Human-AI collaboration in business strategy His publications demonstrate consistent focus on collective problem-solving, with recent emphasis on AI-workforce integration, remote team intelligence, and computational group metrics. Key research projects include the Collective Intelligence Design Lab, Minglr, Climate CoLab, and Measuring Collective Intelligence. Honors include an honorary doctorate from the University of Zurich . He co-founded four software companies and holds 11 patents in collaboration systems and organizational modeling. He directs the MIT Center for Collective Intelligence, leading interdisciplinary teams on global challenges. Current initiatives explore AI-enhanced prediction markets, collective intelligence genomes, and hybrid human-machine systems for organizational design.

Ulrich W. Thonemannمشاهده پروفایل

استاد

• Supply Chain Management
• Optimization
• Information Systems
• +۵ مورد دیگر

Prof. Ulrich W. Thonemann is a Full Professor and Director of the Department of Supply Chain Management & Management Science at the University of Cologne's Faculty of Management, Economics and Social Science. Since 2019, he has served as Dean of the Faculty and President of the University of Cologne Executive School since 2018. His research spans Supply Chain Management Optimization Behavioral Operations Information Systems . His recent work focuses on Incentive systems for forecast sharing Behavioral inventory metrics Contract design for newsvendor problems Demand information sharing Capacity rationing . He has served on the scientific advisory board of Bundesvereinigung Logistik and as Associate Editor for Production and Operations Management . Scientific Awards: Terman Fellow (1999-2000) Anderson Faculty Scholar (1998-2000) Outstanding Academic Achievements at Stanford (1992) Contact: ulrich.thonemann@uni-koeln.de | Research Group Website

Zhibin Chenمشاهده پروفایل

استادیار

• Transportation Network Modeling and Optimization
• Intelligent Transportation Systems
• Discrete Optimization
• +۴ مورد دیگر

Zhibin Chen is an Assistant Professor of Engineering at NYU Shanghai and concurrently a Global Network Assistant Professor within the broader New York University system. Since January 2019 he has led research and teaching activities at the Division of Engineering and Computer Science in Shanghai, while maintaining university-wide collaborations through his Global Network appointment. Education Ph.D. in Transportation Engineering, University of Florida (2017) Research Interests Dr. Chen’s scholarship centres on Transportation Network Modeling and Optimization , Intelligent Transportation Systems , and Discrete Optimization . He integrates operations research, data science, and engineering to address emerging challenges in electric mobility, autonomous vehicles, and large-scale urban networks. Recent thrusts include: Data-driven analytics of electric-vehicle charging behaviour under usage heterogeneity. Optimization of charging and swapping infrastructure for electric buses and trucks. Network-level deployment and control strategies for connected and automated vehicles. Day-to-day traffic dynamics and equilibrium models with elastic demand. Pricing, policy, and incentive design for sustainable transportation systems. Scientific Awards Stella Dafermos Best Paper Award – awarded at the 95th Transportation Research Board Annual Meeting. Ryuichi Kitamura Paper Award – also conferred at the 95th TRB Annual Meeting. Editorial & Professional Service Dr. Chen currently serves on the Editorial Advisory Board of Transportation Research Part C: Emerging Technologies , shaping the editorial direction of the leading journal in his field. Grants & Collaborations While specific grant identifiers are not disclosed in the provided text, Dr. Chen’s extensive publication record in top-tier journals ( Transportation Science , Transportation Research Parts B, C, D , IEEE ITS , Applied Energy ) and his editorial role indicate sustained research funding and active collaboration with international partners across North America and China. Laboratories & Teams Operating within the Division of Engineering and Computer Science at NYU Shanghai , Dr. Chen leads a research group focused on next-generation mobility analytics, leveraging the university’s interdisciplinary ecosystem and NYU’s Global Network resources to advance smart and sustainable transportation.

• Supply chain resilience
• Inventory management
• E-commerce and warehouse management
• +۱ مورد دیگر

Professor Fang Liu serves as a Professor of Operations Management at Durham University Business School (DUBS). She joined Durham University in 2023 after academic positions at The University of Chinese Academy and Nanyang Technological University, bringing extensive expertise in supply chain systems and operational resilience. Her educational foundation includes a doctoral degree in Operations Management from Duke University's Fuqua School of Business, USA. Liu's research centers on Supply Chain Resilience, Inventory Management, E-commerce and Warehouse Management, and Corporate Social Responsibility and Sustainability. Her work develops innovative frameworks for mitigating disruption risks while optimizing resource allocation, with direct applications in global logistics networks and sustainable operations. She bridges theoretical rigor with practical implementation across diverse sectors. Analysis of her publication trajectory reveals a strategic evolution from foundational inventory theory toward contemporary challenges in e-commerce logistics and sustainable supply chains. Her recent work increasingly addresses healthcare operations and carbon-neutral supply chain design, consistently published in premier journals like Operations Research and Production and Operations Management. Professor Liu has secured multiple competitive research grants as Principal or co-Principal Investigator. She actively translates academic insights into practice through collaborations with organizations including Cummins, Singapore IFRC, and Meide, focusing on operational optimization and resilience building. While specific lab structures aren't detailed, her industry partnerships demonstrate applied research engagement, particularly in developing solutions for complex operational challenges faced by multinational corporations and humanitarian organizations.

Marco Badeمشاهده پروفایل

دانشیار

• Corporate Finance
• Entrepreneurial Finance
• Entrepreneurship
• +۵ مورد دیگر

Marco Bade is an Associate Professor of Finance at ICN Business School's Berlin campus. He holds a PhD in Economics and a Habilitation in Business Management from Technische Universität Berlin. He is affiliated with the CEREFIGE research laboratory at the University of Lorraine. His career includes roles as a Research Associate at TU Berlin, Berlin School of Economics, and a temporary Interim Professor at the University of Potsdam (2020–2021). His research focuses on corporate finance, entrepreneurial finance, entrepreneurship, and financial markets, with notable contributions to crowdfunding dynamics, M&A strategies, and regulatory impacts on startups. Education : 2023: Habilitation in Business Management, Technische Universität Berlin, Germany 2016: PhD in Economics (Dr. rer. oec.), Technische Universität Berlin, Germany Research Interests : Marco’s work bridges theoretical finance with practical applications in entrepreneurship and markets. He explores how institutional frameworks (e.g., regulations, competition) shape entrepreneurial behavior and financial decision-making. Recent studies analyze the role of sustainable development goals in crowdfunding success and the psychological factors influencing investor choices in equity-based platforms. Teaching : He teaches courses such as Financial Risk Management, Market Liquidity & Price Discovery, and International Market Microstructure at ICN Business School. His courses emphasize real-world applications in finance and entrepreneurship. Labs/Teams : He contributes to the CEREFIGE research group, focusing on quantitative methods in finance and economics.

• Theoretical Computer Science
• Sublinear Algorithms
• Complexity Theory
• +۴ مورد دیگر

Elena Grigorescu is an Adjunct Associate Professor in the Department of Computer Science at Purdue University, where she has been a faculty member since Fall 2012. Her research program spans theoretical computer science with a focus on foundational algorithmic challenges in large-scale data processing and computational limits, maintaining strong connections to cryptography, communications, and optimization applications. Her educational background includes a PhD from the Massachusetts Institute of Technology (MIT), establishing her expertise in rigorous theoretical frameworks. Professor Grigorescu's research emphasizes designing algorithms that operate in sublinear time or space for massive datasets, analyzing complexity of error-correcting codes and lattices, and exploring information-theoretical computation limits. Current investigations integrate differential privacy with learning-augmented techniques to solve online optimization problems, network design challenges, and data stream processing bottlenecks. Her work bridges abstract theory with practical implementations in cryptographic systems and quantum computing paradigms, demonstrating consistent innovation in algorithmic foundations. Analysis of her recent publications (2022-2025) reveals a dominant focus on sublinear-time algorithms, particularly at the intersection with differential privacy and machine learning augmentation. Key contributions include novel spanner constructions for network design, privacy-preserving clustering frameworks, and breakthroughs in trace reconstruction and coding theory. A pronounced trend shows increasing integration of learning-based predictions to enhance classical online algorithms for packing/covering problems while maintaining theoretical guarantees, alongside sustained contributions to error-correcting code analysis and graph-theoretic foundations. No specific scientific awards or major fellowships were documented in the provided materials, though her publication record in premier venues like STOC, FOCS, and APPROX/RANDOM indicates significant peer recognition. Professor Grigorescu actively mentors graduate students in theoretical computer science research, guiding investigations in sublinear algorithms, complexity theory, and coding theory. Her collaborative projects involve interdisciplinary teams across institutions, focusing on cryptographic applications and quantum information theory, though specific grant details were not included in the source texts. Ongoing work suggests expansion into quantum algorithm design and privacy-preserving machine learning frameworks. While dedicated laboratory facilities were not specified, her research operates within Purdue's theoretical computer science group, leveraging university-wide computational resources and fostering collaborations through conference participation and workshop organization.

• Formal Methods
• Verification
• Model Checking
• +۴ مورد دیگر

Nathalie Bertrand is an Inria Researcher and Head of the DEVINE team at Inria Centre Rennes and IRISA lab. She co-heads the working group on Verification of the GDR IFM of the CNRS with Pierre-Alain Reynier, and co-leads the gender equality commission of IRISA and Inria Rennes with Elisa Fromont. She is also an active member of the Inria committee on gender equality and equal opportunity. PhD from ENS Cachan (October 2006) 1-year post-doc at TU Dresden Hired as Inria researcher (October 2007) Habilitation (HDR) from University Rennes 1 (November 2015) Dr. Bertrand's research focuses on formal methods, verification, model checking, parameterized systems, quantitative models, automata, and games. Her work bridges theoretical computer science with practical applications in distributed systems, probabilistic verification, and game theory. She develops efficient model-based formal methods to verify and enforce functional and non-functional properties of dependable distributed systems that include quantitative aspects such as time, cost, or probabilities. Her recent publications demonstrate a strong trend toward parameterized verification of distributed algorithms, probabilistic systems, and game-theoretic approaches to verification problems. Her research has evolved from foundational work on timed automata and probabilistic systems to increasingly complex problems involving distributed algorithms with arbitrary numbers of participants, blockchain consensus, and randomized fault-tolerant systems. Dr. Bertrand serves on the editorial boards of JLAMP and TCS, and has been a program committee member for numerous prestigious conferences including STACS, TACAS, Concur, QEST, LICS, FoSSaCS, ICALP, MFCS, and many others. She has co-chaired program committees for Formats'20, QEST'17, QAPL'14, and QAPL'15. As an advisor, she has supervised numerous PhD students including Nicolas Waldburger, Bastien Thomas, Suman Sadhukhan, Anirban Majumdar, Engel Lefaucheux, Paulin Fournier, and Amélie Stainer. She currently supervises postdoc Gaëtan Staquet and PhD candidates Pranav Ghorpade, Luca Paparazzo, and Luc Lapointe. She leads the DEVINE project-team (created January 2024), which focuses on developing efficient model-based formal methods to verify and enforce properties of dependable distributed systems with quantitative aspects. Previously, she was part of the SUMO team. Her current projects include ANR MAVeriQ (2021-2025), ANR BISouS (2022-2025), and ANR PaVeDyS (2024-2028).