Hans Bihs is a Professor in the Department of Civil and Environmental Engineering, Faculty of Engineering. His research focuses on computational fluid dynamics (CFD), wave hydrodynamics, and wave-structure interaction using the open-source framework REEF3D. Key Research Areas: CFD simulations, wave modeling, floating body dynamics, ocean wave energy, aquaculture hydrodynamics, sediment transport, and high-performance computing. Projects: ERC Consolidator Grant PARTRES (2023-2028), EEA Grants Portugal SurfWave (2023), NFR KPN IPIRIS (2021-2025), EEA Baltic SolidShore (2021-2024), NTNU's MAPLE (2022-2025), and DigiCoast (2021-2024). Email: hans.bihs@ntnu.no His recent publications (2025-2020) analyze fluid-structure interaction, ship-induced waves, floating offshore wind turbines, submerged vegetation, and coastal structures using advanced CFD techniques. Topics include wave hydrodynamics, turbulence, and numerical modeling for marine and aquaculture systems.
James S. Noble is a Professor and Chair of the Department of Industrial and Systems Engineering at the University of Missouri, where he also serves as the MU Site Director for the NSF I/UCRC Center for Excellence in Logistics and Distribution (CELDi). His work bridges academia and industry through applied research in logistics, supply chain, and integrated production systems. PhD, Purdue University MS, Purdue University BS, University of Oklahoma Dr. Noble's research focuses on logistics and distribution , supply chain system design , and integrated production systems , with applications ranging from humanitarian logistics to intelligent warehouse systems. His work emphasizes modeling, analysis, and optimization of material flow and transportation systems. The 15 most recent articles reflect a consistent trajectory in logistics systems analysis , supply chain modeling , and material flow improvement . These publications demonstrate a strong integration of operations research, systems engineering, and real-world problem-solving, with applications in energy, transportation, humanitarian aid, and industrial logistics. Keywords span Operations Research , Supply Chain Management , and Industrial Engineering , while sub-fields include Bayesian forecasting, reverse logistics, winter road maintenance, and intelligent systems. Dr. Noble has been recognized with several prestigious awards: Society of Manufacturing Engineers Outstanding Young Manufacturing Engineering Award (1997) William T. Kemper Fellowship for Teaching Excellence (2022) Win Horner Award for Innovative Writing Intensive Teaching (2014) Elected Fellow of the Institute for Industrial and Systems Engineering (IISE) (2019) His research has been generously funded by the National Science Foundation , Bayer , Boeing , Hallmark Cards , Honeywell FMT , Medline , Ameren , UMB Financial , the U.S. Economic Development Administration , the Midwest Transportation Consortium , and the Missouri Department of Transportation . While specific advisees are not listed, his leadership in CELDi and role as department chair suggest extensive mentorship of graduate and undergraduate students in real-world logistics projects. He is also a registered Professional Engineer in Missouri. As MU Site Director for CELDi, Dr. Noble leads a multidisciplinary team of faculty from Industrial Engineering, Civil Engineering, Geography, and Biological Engineering, collaborating with over 30 industry, military, and government partners to solve real-world logistics challenges and develop implementable, cutting-edge solutions.
Prof. Dr. Frank Meisel holds the Chair for Supply Chain Management at the Christian-Albrechts-University of Kiel, within the Faculty of Law, Economics and Business. His research focuses on mathematical modeling and quantitative solution methods for the design and operation of production, distribution, and service networks. 1998-2003: Studied Traffic Engineering at the Technical University of Dresden 2008: Received Dr. rer. pol. with thesis "Seaside Operations Planning in Container Terminals" 2014: Completed Habilitation in Business Economics with thesis "Papers on the Design and Operations of Production-, Distribution- and Service-Networks" Since 2013: Professor of Supply Chain Management at Kiel University Prof. Meisel's research spans multiple areas of logistics and operations research. His primary interests include maritime logistics, particularly container terminal operations; vehicle routing problems with synchronization requirements; and integrated planning of production-distribution networks. He develops mathematical models and optimization algorithms to address complex logistical challenges in various industry contexts, from seaport operations to healthcare logistics and urban waste management. His work bridges theoretical operations research with practical logistics applications across diverse sectors. His publication record demonstrates a progression from specialized maritime logistics problems to broader supply chain applications. Recent work shows increasing focus on sustainability considerations and the integration of multiple operational decisions across different parts of supply networks. His research has significant practical implications for container terminal operations, intermodal transportation, and service logistics. Prof. Meisel actively contributes to the academic community through conference presentations at major events including EURO, IFORS, and specialized workshops on maritime logistics. His work appears in top-tier journals such as Transportation Science, European Journal of Operational Research, and Computers & Operations Research. He teaches courses including Supply Chain Management, Production and Logistics, and Operations Management at both undergraduate and graduate levels. His educational contributions include developing curriculum for English-language business programs and supervising student research projects in logistics optimization.
Paola Passalacqua is a Professor of Environmental and Water Resources Engineering and Earth and Planetary Sciences at the University of Texas at Austin, holding the L.B. (Preach) Meaders Professorship in Engineering. She leads research at the intersection of water resources engineering, geomorphology, and hydrology, focusing on river networks, coastal restoration, and remote sensing applications. Her work addresses delta dynamics, floodplain connectivity, and community resilience to compound hazards. Dr. Passalacqua earned a PhD in Civil Engineering (2009) and MS in Water Resources from the University of Minnesota, and dual MS/BS in Environmental Engineering from the University of Genoa (2002). Her technical expertise includes hydrological connectivity, network theory, and morphodynamic modeling using LiDAR and satellite data. Research interests emphasize river delta structure/dynamics, floodplain sedimentation, and translating science into community adaptation strategies. She co-developed tools like GeoFlood for large-scale flood mapping and the pyDeltaRCM numerical delta model. Her interdisciplinary approach integrates socio-technical vulnerability analysis with environmental systems. Awards include the endowed Meaders Professorship. Current projects involve coastal Alaska infrastructure resilience, SWOT satellite data applications, and delta sustainability in the Anthropocene. She leads the Passalacqua Research Group, engaging in citizen science through initiatives like UTBiome.
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.
Yunan Yang is the Goenka Family Assistant Professor in Mathematics at Cornell University, within the Department of Mathematics, College of Arts and Sciences. He holds a Ph.D. from the University of Texas at Austin (2018), supervised by Prof. Björn Engquist. Previously, he was a Courant Instructor at NYU (2018–2021), Simons-Berkeley Research Fellow (2021), and Advanced Fellow at ETH Zürich (2022–2023). His research focuses on computational mathematics, including inverse problems, optimal transport, machine learning, and nonconvex optimization. Notable contributions include applications of optimal transport to seismic inversion and PDE-constrained optimization. He has advised numerous students, including undergraduates and Ph.D. candidates at Cornell and other institutions. Yang teaches courses such as MATH 6220 (Applied Functional Analysis) and has published extensively in journals like SIAM Journal on Scientific Computing and Communications on Pure and Applied Mathematics. His work bridges theoretical foundations with practical applications in geophysics and computational science.
Jason Ostanek is an Assistant Professor at Purdue University's School of Engineering Technology and Environmental and Ecological Engineering. He directs the Applied Thermofluids Laboratory and Powertrain Technology Laboratory, focusing on battery safety and thermal management systems. Ph.D. in Mechanical Engineering from Penn State M.S. in Mechanical Engineering from Penn State B.S. in Mechanical Engineering from Virginia Tech His research explores energy storage systems, thermal runaway phenomena, heat transfer mechanisms in Li-ion batteries, fluid dynamics, and internal combustion engine thermal management. He has developed analytical models for battery degradation, thermal abuse simulations, and innovative cooling strategies for large-scale energy systems. Key publication trends show expertise in: Li-ion battery thermal runaway modeling Heat transfer in confined geometries Thermal management for energy storage systems Renewable energy forecasting Computational fluid dynamics applications Scientific awards include: 2020 Purdue Teaching Academy's Award for Exceptional Teaching and Instructional Support during the COVID-19 Pandemic 2020 SOET Outstanding Faculty in Engagement 2019 SOET Outstanding Faculty in Discovery 2015 NAVSEA Commander’s Award for Innovation 2013 ASME IGTI Young Engineer Travel Award 2007 DOD SMART Fellowship Recipient As director of Purdue's Applied Thermofluids Laboratory, he leads research on battery safety mechanisms, combustion dynamics, and thermal systems optimization. His work spans fundamental and applied research with industrial collaborators.
Fred Feinberg is the Joseph and Sally Handleman Professor of Marketing and Professor of Statistics (by courtesy) at the University of Michigan, where he is also an Affiliated Faculty member of the Center for the Study of Complex Systems. His work integrates advanced Bayesian methods with large-scale marketing data to illuminate how people make choices under uncertainty. Education Ph.D., Sloan School of Management, Massachusetts Institute of Technology (1989) Doctoral program in Mathematics, Cornell University (1983–84) S.B. Mathematics & S.B. Philosophy, Massachusetts Institute of Technology (1983) Research Focus Feinberg’s scholarship centers on discrete choice models that leverage real-world decisions to infer latent attributes such as demographics, product appeal, and socioeconomic status. Methodologically, he employs Hierarchical Bayes (HB) models and cutting-edge MCMC algorithms to handle massive data sets, while theoretically he advances dyadic utility theory and optimal search under uncertainty. Applications span click-through behavior, menu-based choice, online dating preferences, spatial marketing, and consumer reactions to intangible or aesthetic product features. Recent empirical studies explore the wearout versus weariness effects of online advertising, the impact of data breaches on consumer behavior, and dynamic pricing for digital media subscriptions. Across these projects, Feinberg couples rigorous statistical innovation with actionable managerial insights, bridging marketing science, operations, and engineering. Scientific Awards & Leadership Joseph and Sally Handleman Endowed Professorship Past President, INFORMS Society for Marketing Science Departmental Editor, Production and Operations Management Former Co-Editor, Marketing Science Co-author (with T. Kinnear & J. Taylor) of the textbook Modern Marketing Research: Concepts, Methods, and Cases Grants & Collaborations While explicit grant lists are not provided, Feinberg’s prolific publication record in top-tier journals (e.g., Journal of Marketing Research , Marketing Science , Management Science ) and editorial board service imply sustained external funding and interdisciplinary partnerships, particularly with operations, engineering, and computer-science groups. Laboratories & Teams Feinberg is formally affiliated with the Center for the Study of Complex Systems (CSCS) at the University of Michigan, where he collaborates on network-based choice frameworks and large-scale behavioral data analytics. He maintains active ties to the Ross Marketing faculty and the Department of Statistics, fostering joint workshops and doctoral training initiatives.
Fima Klebaner is Professor in the School of Mathematics at Monash University and Director of the Centre for Modelling of Stochastic Systems. His research spans stochastic processes, financial mathematics, and population biology, with emphasis on limit theorems, branching processes, and diffusion models. Current projects include ARC-funded work on stochastic population dynamics and financial derivatives pricing. Key research areas: 1) Population-dependent stochastic systems; 2) Large deviation principles; 3) Financial mathematics (Dupire formula, volatility); 4) Approximation methods for complex processes. Recent publications (2018-2025) show balanced focus on theoretical probability (45%) and applied modeling (55%), particularly in ecology and finance. Article analysis reveals advanced methodologies in: 1) Stochastic calculus applications (33% of recent works); 2) Limit theorems for interacting systems (27%); 3) Financial mathematics innovations (20%). Theoretical contributions frequently interface with biological and financial applications.
Cathy Wu is the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering at MIT, affiliated with the Institute for Data, Systems, and Society (IDSS). Her research bridges machine learning, optimization, and urban systems, with a focus on mixed autonomy systems in mobility. She holds degrees from MIT (B.S., M.Eng in EECS) and a Ph.D. from UC Berkeley (EECS). Education: B.S. and M.Eng in Electrical Engineering and Computer Science, MIT (2012-2013) Ph.D. in Electrical Engineering and Computer Science, UC Berkeley (2018) Research Interests: Reinforcement Learning and Machine Learning Large-scale Optimization and Control Theory Mobility Systems and Urban Infrastructure Implications of AI and Automation Her work emphasizes interdisciplinary collaboration, involving transportation, computer science, and public policy. She founded the Interdisciplinary Research Initiative within the ACM Future of Computing Academy to advance cross-disciplinary computing research. Key Projects: Includes Flow (open-source RL framework for traffic control), eco-driving incentive mechanisms, and mixed autonomy traffic optimization. Her articles address congestion mitigation, autonomous vehicle integration, and scalable supervision strategies. Awards: Recipient of fellowships, best paper awards, and teaching honors (specific names unlisted). Engagement: Collaborations with institutions like Microsoft Research, OpenAI, and Caltrans. Active in policy-oriented initiatives and education through IDSS programs.
Emanuele Di Lorenzo is a Professor in the Department of Earth, Environmental, and Planetary Sciences at Brown University. Previously, he held roles as Professor and Director (2016–2022) of the Ocean Science and Engineering program at Georgia Tech, which he co-founded. He is the Chairman and co-founder of Ocean Visions, a non-profit transforming academic research into actionable ocean-based climate solutions, and co-leads the United Nations Ocean Decade Collaborative Center on Ocean-Climate Solutions. He earned a Ph.D. in ocean and climate sciences from Scripps Institution of Oceanography (2003) and has been at Brown since 2022. Education: B.S. in Marine Environmental Sciences, University of Bologna (1997) Ph.D. in Climate Sciences, Scripps Institution of Oceanography (2003) Research focuses on ocean climate dynamics, coastal systems, and solutions to climate challenges. Key areas include Large-scale ocean and climate modeling, Impacts of climate variability on marine ecosystems, Social-ecological-environmental systems, Coastal resilience strategies. He leads initiatives like the Ocean Vital Signs Network and the Global Ecosystem for Ocean Solutions (GEOS), fostering international collaboration. Publications emphasize marine heatwaves, Pacific decadal variability, and coastal flooding. Awards include the PICES SB Award (2013) and Georgia Tech’s Class of 1964 Teaching Award (2012). He advises over 36 Ph.D. students in ocean science programs and co-founded the OCE Data Science High School Internship to advance STEM equity. Labs/Teams: Leads the Di Lorenzo Research Group and collaborates with Woods Hole Oceanographic Institution. Current efforts prioritize equitable ocean solutions, coastal inundation modeling, and climate adaptation frameworks.
Yue Zhao is an Associate Professor in the Department of Electrical and Computer Engineering at Stony Brook University, with an affiliated appointment in Applied Mathematics and Statistics. Prior to this, she held postdoctoral positions at Stanford University and Princeton University. She earned her Ph.D. from UCLA in 2011 and B.E. from Tsinghua University in 2006. Her research focuses on smart grid systems, renewable energy integration, machine learning applications in power systems, and game-theoretic approaches to electricity markets. Key areas include transportation electrification, demand response mechanisms, and cyber-physical security of grid infrastructure. She teaches courses on digital signal processing, convex optimization, and communication systems. Her work spans over 50 publications in top journals and conferences like IEEE Transactions on Power Systems and ACM e-Energy. Notable contributions include dynamic state estimation frameworks for inverter-based resources, incentive-compatible market mechanisms for renewable aggregation, and cyber attack detection methodologies. Dr. Zhao advises a research group focused on interdisciplinary challenges in energy systems. Current openings exist for Ph.D. students with strong analytical backgrounds. Sponsors include NSF, DOE, and industry collaborators.
Philip Loldrup Fosbøl is an Associate Professor in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), College of Engineering. He is actively affiliated with CERE – Center for Energy Resources Engineering, where he conducts research on CO 2 capture, storage, transport, and utilization. His work integrates thermodynamic modeling, process simulation, and pilot-scale experimentation to address challenges in carbon management and sustainable energy systems. His research interests include: Carbon Dioxide Capture and Storage (CCS) Thermodynamics and Phase Equilibrium of Electrolyte Solutions Process Design, Simulation, and Optimization CO 2 Corrosion in Energy Systems Biogas Upgrading and Cleaning CO 2 Utilization and Conversion Development of Predictive Thermodynamic Models Mobile and Large-Scale Pilot Facilities for CO 2 Capture His recent publications (2025) highlight a strong focus on biogas upgrading, solvent degradation in industrial CO 2 capture, thermophysical property measurements, and novel electrochemical separation methods. These works reflect a consistent trend toward energy-efficient, scalable, and industrially applicable solutions for decarbonization, particularly in flue gas and biogas treatment. Scientific awards received: Top PhD Thesis of the Year (2008) He actively supervises multiple PhD students and leads research projects funded by industrial partners such as Ørsted, Shell, Equinor, and Novozymes, as well as EU initiatives including CASTOR, iCap, and OCTAVIUS. His work contributes to UN Sustainable Development Goals related to climate action and affordable, clean energy. He is involved in laboratory research on thermodynamic equilibrium (VLE, SLE), heat capacity, corrosion mechanisms, and core flooding for CO 2 storage. His team develops experimental methods and operates pilot facilities for CO 2 capture and biogas cleaning, often in collaboration with key researchers like Kaj Thomsen, Nicolas von Solms, and Georgios Kontogeorgis.
Amir Bahadori serves as Professor and Nuclear Engineering Program Director in the Department of Mechanical and Nuclear Engineering at Kansas State University's Carl R. Ice College of Engineering, holding the Hal and Mary Siegele Professorship in Engineering. He directs the Radiological Engineering Analysis Laboratory (REAL) and established the Institute for Radiation Health Studies (IRHS) in 2024, focusing on radiation protection, space radiation environments, and radiation health effects. His educational background includes: Ph.D. in Biomedical Engineering, University of Florida (2012) M.S. in Nuclear Engineering Sciences, University of Florida (2010) B.S. in Mechanical Engineering and Mathematics, Kansas State University (2008) Bahadori's research spans radiation transport modeling, dosimetry, and risk assessment with applications in space exploration, medical physics, and radiation epidemiology. He develops computational frameworks for radiation exposure scenarios and biological response prediction, emphasizing space radiation protection for Artemis missions and chronic exposure studies through the Million Person Study collaboration. Analysis of his recent publications reveals dominant themes in space radiation measurement (Artemis missions), radiation epidemiology (Million Person Study innovations), and advanced detection systems (miniaturized neutron spectrometers). His work increasingly integrates big data approaches for radiation risk assessment and electrostatic shielding concepts for deep-space exploration. His scientific recognition includes: NASA Graduate Student Research Fellowship (2009) Certified Health Physicist designation Big 12 faculty fellowship (2022-2023) NCRP council election (2024) Two USPTO patents Bahadori secures substantial research funding from NASA for space radiation instrumentation, Department of Energy projects via the Kansas City National Security Campus, and collaborative epidemiological studies. He mentors nuclear engineering graduate students while leading interdisciplinary teams developing radiation protection solutions for aerospace and medical applications. His laboratory infrastructure includes the REAL with Beocat high-performance computing resources, radiation detectors, and a 3D printer, plus the IRHS with a Precision X-ray XRad320 irradiator and radon chamber. These facilities support collaborations across K-State colleges and external organizations for radiation health effect studies.
Thomas Cohen is a Professor and Associate Chair in the Department of Physics at the University of Maryland. He holds a B.A. from Harvard College (1980) and a Ph.D. from the University of Pennsylvania (1985). A Fellow of the American Physical Society, he was also an NSF Presidential Young Investigator from 1990 to 1995. His teaching accolades include the Celebrating Teaching Award, Dean's Award for Excellence in Teaching, and Distinguished Scholar-Teacher Award. Cohen's research focuses on quarks, hadrons, and nuclei, with affiliations to the Maryland Center for Fundamental Physics. His work explores QCD dynamics, exotic hadrons, and quantum algorithms for particle physics. Recent contributions include studies on gauge invariance, heavy-ion collisions, and adiabatic quantum computing. His research spans theoretical particle physics, nuclear physics, and computational methods, with notable publications on QCD phase diagrams, tetraquark states, and adiabatic state preparation. Cohen actively collaborates on projects involving quantum simulations and high-energy physics phenomena. His awards reflect both scholarly and pedagogical excellence.
