Find Academic Supervisors

• Applied Mathematics
• Mathematical Physics
• Computational Science
• +3 more

Ben Goddard is a Professor in the School of Mathematics at the University of Edinburgh. His work bridges applied mathematics with real-world scientific challenges, emphasizing interdisciplinary collaboration across engineering, biology, chemistry, and physics. He earned his PhD at the University of Warwick, later completing his final year at TU Munich following his advisor. His research focuses on mathematical modeling, numerical methods, and asymptotic analysis applied to problems such as quantum chemistry, fluid dynamics, and biological systems. Education: Bachelor’s degree in Mathematics (undergraduate details unspecified) PhD in Mathematical Quantum Chemistry (University of Warwick/TU Munich) Research interests include: Dynamic density functional theory (DFT) for complex fluids and nanoparticles Interfacial phenomena and contact line dynamics Numerical optimization and pseudospectral methods Biological systems modeling (e.g., RNA transcription mechanics) Recent work explores applications like ouzo phase behavior, aerosol droplet stability, and opinion dynamics in social networks. His collaborations span diverse fields, including experimental biology at the Welcome Centre for Cell Biology. He advocates for mathematicians’ role in interdisciplinary problem-solving, emphasizing clear communication and adaptability. Advising and grants: While specific grant details are not listed, his projects reflect significant funding and team-based research. He actively promotes STEM engagement through activities like designing math-themed escape rooms with his spouse, a statistician. Labs/Teams: Collaborates extensively with Edinburgh’s Schools of Engineering, Biology, and Informatics, though no specific lab names are mentioned.

• Humanitarian Operations
• Air Traffic Management
• Logistics Optimization
• +7 more

Dr. Jose Escribano is a Lecturer in Aviation & Logistics at the Department of Civil and Environmental Engineering within the Faculty of Engineering at Imperial College London. His research focuses on humanitarian logistics optimization, AI-driven airspace management, and urban resilience strategies. He holds a First Class Honours bachelor’s degree (2015) and a PhD (2021) from Imperial College London. Dr. Escribano is affiliated with the Centre for Transport Engineering and Modelling and the Transport Systems and Logistics Project D-Risk SHIFT. His academic qualifications include a BEng in Engineering and a PhD in Civil Engineering, both from Imperial College London. His professional affiliations include the Institution of Civil Engineers, Chartered Institute of Logistics and Transport, and the American Institute of Aeronautics and Astronautics. He has received the 2023 Transportation Research Board Best Paper Award and a JSPS Fellowship for urban evacuation modelling. Dr. Escribano’s research integrates stochastic modelling, machine learning, and simulation to address challenges in humanitarian response, UAV coordination for disaster relief, and airspace safety. His work emphasizes endogenous value-of-information analysis and the application of cutting-edge technologies to enhance societal resilience. He has collaborated with the United Nations World Food Programme on UAV deployment models for humanitarian contexts. His recent publications span topics like air traffic network resilience, autonomous vehicle optimization, and last-mile delivery mechanisms. He advises doctoral candidates in transportation systems, logistics, and air traffic management, offering opportunities for PhD research in these domains.

Philipp ReissView profile

Professor

• Lunar Exploration
• Planetary Resources
• Space Instrumentation
• +3 more

Prof. Philipp Reiss is a Professor of Lunar and Planetary Exploration Technologies at the Technical University of Munich (TUM), part of the TUM School of Engineering and Design. His academic journey includes a doctorate in lunar exploration (2018) and postdoctoral leadership of a research group, followed by ESA work on lunar mission instruments. He was appointed to his current role in 2022. Education: Bachelor's/Master's in Aerospace Engineering from Bremen University of Applied Sciences and TUM Doctorate in Lunar Exploration (TUM, 2018) Research Focus: Development of instruments for in-situ resource characterization (e.g., water detection on the Moon) Simulation of heat/mass transport in extraterrestrial environments Technologies for extreme environment exploration Legal and ethical frameworks for space resource utilization Recent Article Trends: Recent work emphasizes lunar water cycle analysis, space resource extraction technologies, and ESA mission instrument development. Key projects include PROSPECT payload design and thermal extraction of volatiles from regolith. Awards and Roles: ERC Grant Awardee (2024), Honorary Fellow at TUM Institute for Advanced Study Principal Investigator at ORIGINS Excellence Cluster (2022–present) Member of ESA’s PROSPECT science team (2019–present) Contributions to UN space resource legal discussions Advising & Grants: Supervises research projects on lunar rover systems and resource utilization. Secured funding through ERC grants and ESA collaborations. Advises on international space policy initiatives. Labs/Teams: Leads the Lunar and Planetary Exploration Professorship group at TUM, collaborating with ESA, JAXA, and the European Lunar Symposium. Active in developing planetary exploration tools like the PROSPECT permittivity sensor and MULE instrumentation.

• Transportation Engineering
• Intelligent Transportation Systems (ITS)
• Wrong-Way Driving Countermeasures
• +15 more

Haitham Al-Deek is a Professor in the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida's College of Engineering and Computer Science. He leads the Intelligent Transportation Systems and Data Analytics Lab and has over 32 years of experience in transportation engineering, planning, and operations. His work is nationally recognized, particularly in freeway operations and intelligent transportation systems (ITS). Ph.D., Civil Engineering-Transportation Engineering, University of California, Berkeley (1991) M.S., Civil Engineering-Transportation Engineering, University of California, Berkeley (1987) B.S., Civil Engineering (with Honors), University of California, Berkeley (1985) Dr. Al-Deek's research focuses on wrong-way driving countermeasures, connected and automated vehicles, traffic safety, and data analytics. He pioneered innovative ITS solutions for detecting and preventing wrong-way driving, including the development of a high-success-rate detection system in partnership with the Central Florida Expressway Authority (CFX). His work extends to freight transportation, electronic toll collection, and sustainable transportation systems. He has also contributed to safety performance functions and driver behavior modeling. His recent publications highlight advanced methodologies in network screening for crash modeling, the use of crowdsourced data (e.g., Waze) for incident detection, optimization of wrong-way driving countermeasures, and benefit-cost analyses of safety technologies. These works reflect a strong trend toward data-driven, real-time, and cost-effective solutions in transportation safety and operations. Scientific awards and recognitions include: TRB Chairman Award (2018, 2012) Multiple TRB Best Paper Awards (Freeway Operations and Regional TSM&O, 2023–2003) TRB Best Student Paper Awards (2022, 2019, 2018, 2017) UCF Excellence in Research Award (2018) UCF Researcher of the Year (1999) Distinguished Researcher, UCF College of Engineering (2003) Dr. Al-Deek has supervised 15 Ph.D. students and 29 M.S. theses and has secured over $10.3 million in research funding from agencies including FDOT, TRB, USDOT, and CFX. He serves as a technical editor for TRR and associate editor for the Journal of Intelligent Transportation Systems. He also chaired key TRB paper review subcommittees and is an active professional engineer in Florida. He leads the Intelligent Transportation Systems and Data Analytics Lab, which focuses on real-world applications of ITS, data warehousing, and advanced analytics for transportation safety and efficiency.

• Hydroinformatics
• Urban Hydrology
• Flood Modeling
• +3 more

Jonathan L. Goodall is a Professor of Civil and Environmental Engineering and Director of the Link Lab at the University of Virginia. His research focuses on hydroinformatics, urban hydrology, and flood modeling, leveraging data science and cyber-physical systems to enhance resilience in coastal urban environments. He leads efforts in reproducible environmental modeling through integration of platforms like HydroShare, emphasizing open science and computational workflows. His work includes advancing machine learning techniques for real-time flood forecasting, integrating IoT and sensor networks for smart city applications, and assessing climate change impacts on coastal communities. Notable contributions involve developing surrogate models for flood prediction in Norfolk, VA, and studying compound flooding effects using hydrodynamic modeling paired with crowdsourced data. Collaborations span universities, national labs, and agencies like CUAHSI, focusing on environmental data interoperability and infrastructure resilience. Goodall’s research often addresses socio-technical challenges in urban flood management, combining engineering solutions with community engagement strategies. His lab explores reinforcement learning for real-time stormwater control, IoT education initiatives, and geospatial tools for flood vulnerability analysis. Projects frequently involve interdisciplinary teams and emphasize reproducibility through containerized environments and metadata standards.

Ian AbelView profile

Researcher

• Fusion Energy
• Plasma Physics
• Magnetic Confinement Systems
• +3 more

Dr. Ian Abel is an Associate Research Scientist at the Institute for Research in Electronics & Applied Physics (IREAP) at the University of Maryland, where he has been since 2018. His expertise spans fusion energy, plasma physics, and computational modeling. Abel holds a B.A. in Mathematics (2006) and M.S. in Applied Mathematics (2007) from the University of Cambridge, followed by a Ph.D. in Theoretical Physics from the University of Oxford (2012). His research focuses on magnetically confined fusion systems, particularly edge dynamics in tokamaks and innovative centrifugal mirror concepts. He has contributed to the development of gyrokinetic simulation tools like the GX code and the MaNTA transport model. Abel’s work also explores machine learning applications in plasma turbulence analysis and centrifugal mirror fusion reactor design for space propulsion. His research leverages advanced numerical methods, including GPU-native algorithms and adjoint-based optimization techniques for plasma equilibria. Key projects include the Centrifugal Mirror Fusion Experiment (CMFX), where he investigates plasma confinement and transport phenomena. His publications emphasize interdisciplinary approaches, integrating computational fluid dynamics, statistical physics, and high-performance computing to address challenges in fusion energy and plasma dynamics. While no specific awards are listed, his contributions to gyrokinetic turbulence modeling and centrifugal confinement systems are central to current fusion research.

• Sustainable transport planning
• Urban spatial modeling
• GIS applications in planning
• +3 more

Professor Yngve Karl Frøyen works at the Department of Architecture and Planning, Faculty of Architecture and Design, Norwegian University of Science and Technology (NTNU). With expertise in sustainable transport solutions, urban spatial modeling, and GIS applications for planning, he has taught and supervised urban and regional planning topics since 2010. His work spans multiple master programs and involves improving transport modeling tools for walking, transit, and bicycling modes. Research Focus: Sustainable urban transport (walking, bicycling, public transit), urban density, GIS methods, land use-transport interactions, and urban logistics. Teaching: Courses in GIS methods, land use-transport integration, regional planning, and master thesis supervision. Publications: 15+ works on transport modeling, urban density impacts, bicycle infrastructure, and planning methodology. Outreach: Regularly presents at conferences and seminars on topics like urban logistics, walking modeling, and transport policy. His academic career spans from 1981 civil engineer graduation to current professorship, with prior roles at Norwegian Institute of Urban and Regional Research (NIBR) and SINTEF. He combines technical GIS proficiency with policy-oriented planning expertise.

Ling TaoView profile

Researcher

• Bioenergy
• Process Integration
• Techno-economic Analysis
• +4 more

Ling Tao is a Researcher at the National Renewable Energy Laboratory (NREL) , focusing on Techno-economic Analysis , Process Integration , and Sustainable Aviation Fuels . Their work spans Bioenergy , Lignocellulosic Biomass , and Energy System Optimization . Education : Bachelor in Chemical Engineering (Tsinghua University), PhD in Chemical Engineering (University of Massachusetts Amherst) Research interests include Catalytic Processes , Life Cycle Assessment , and Supply Chain Simulation for biofuels. Recent publications emphasize Biomass-to-Aviation Fuels and Climate Change Impact on Renewable Energy . 2025 publications highlight Dynamic Process Computation for sustainable aviation fuels and Process Optimization for bioconversion systems. Collaborations involve experts in Catalysis and Green Energy . Awards : NREL Distinguished Member of Research Staff (2021)

Beate ConradyView profile

Associate Professor

• Infectious Disease Epidemiology
• Animal Health Economics
• Veterinary Public Health
• +7 more

Beate Conrady is an Associate Professor in Infectious Disease Epidemiology and Animal Health Economics at the Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, where she joined in April 2021. She has been affiliated with the Centre for Sustainable Health (CSH) since May 2020. Previously, she led the working group on Epidemiology and Animal Health Economics at the University of Veterinary Medicine in Vienna for eight years. Her research focuses on the development and application of mathematical and economic models to assess prevention and intervention strategies for infectious diseases in veterinary and public health contexts. Key areas include zoonoses, cattle disease control, biosecurity, and One Health. She has extensive experience in international consultancy, including with EFSA, the Austrian Government, and European scientific networks. Beate's recent publications (2020–2024) demonstrate a strong emphasis on disease transmission modeling, surveillance systems, and economic evaluation of health interventions. Her work spans Salmonella, foot-and-mouth disease, Cryptosporidium, and vector-borne diseases, often employing advanced modeling techniques and large-scale data analysis. She has received more than 11 scientific awards for her contributions to infectious disease epidemiology and animal health economics. Consultant for European Food Safety Authority (EFSA) Member of international scientific committees (Med-Vet-Net, DISCONTOOLS) Principal investigator and consortium leader with over 7.5 million EUR in research funding, including more than 1 million EUR in third-party funds She is actively involved in editorial and peer-review activities for leading journals and contributes to policy development in animal health and zoonotic disease control.

Remco M. DijkmanView profile

Professor

• Business Process Management
• Data-Driven Process Optimization
• Supply Chain Management
• +3 more

Remco M. Dijkman serves as Full Professor in Information Systems at Eindhoven University of Technology (TU/e), chairing the Information Systems group within the Industrial Engineering and Innovation Sciences school. He additionally holds a Full Professor position at EAISI High Tech Systems and acts as research director for high-tech supply chains at the European Supply Chain Forum—a network of over 50 multinational companies. His research centers on Business Process Management with emphasis on data-driven optimization of business processes. His academic background includes both PhD and Master's degrees in Computer Science from the University of Twente. Publications span Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology, with over 100 papers and service on the editorial board of Information Systems. He has held visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. Dijkman's research interests focus on detecting, diagnosing, and predicting optimal execution scenarios in business processes, developing mathematical models for quantitative process analysis , and resource assignment optimization . These are primarily applied in transportation logistics and high-tech supply chains, where he investigates data-driven predictions for transport order assignment and supply chain planning. His work bridges artificial intelligence with practical business applications. Recent publications (2024-2025) reveal concentrated efforts in deep reinforcement learning for resource allocation, process pattern discovery, and software library development (GymPN, SimPN). Key trends include predictive process monitoring for healthcare applications, event data enrichment frameworks, and uncertainty handling in logistics planning—demonstrating strong interdisciplinary integration. Scientific recognition includes: Best Demo Award (2019) Best Reviewer Award (2016) Test of Time Award (2019) He has supervised 150 students, including Lotte Vugs who received the Dow Chemical Best OML Master Thesis Award in 2020. Grant leadership spans eight projects: NXTGEN Smart Industry (2023-2030), CollChain (2023-2029), CERTIF-AI (2020-2025), FENIX (2019-2023), and DynaPlex (2021-2024), focusing on digital twins, federated networks, and AI-driven supply chain solutions. Dijkman directs the Information Systems group at TU/e and leads the European Supply Chain Forum's high-tech supply chain research. His work integrates with semiconductor manufacturing and transportation logistics through collaborations with industry partners, while his 2023 invited talks at Technical University of Munich and Humboldt University Berlin highlight his international engagement.

Sumanta DasView profile

Associate Professor

• Sustainable Cementitious Materials
• Microstructure and Material Modeling
• Materials Design for Sustainable and Durable Infrastructure
• +5 more

Dr. Sumanta Das is an Associate Professor and Graduate Director in the Department of Civil and Environmental Engineering at the University of Rhode Island. His research focuses on sustainable infrastructure materials, with particular expertise in cementitious materials, composite structures, and advanced computational modeling techniques. He directs a vibrant research group that bridges experimental mechanics with computational modeling and machine learning approaches to address challenges in infrastructure durability and performance. Dr. Das received his educational training from prestigious institutions: Ph.D. in Materials and Structures from Arizona State University (2015) M.Tech. in Structural Engineering from Indian Institute of Technology, Kanpur (2012) B.E. in Civil Engineering from Jadavpur University (2010) His research interests center around developing sustainable and durable infrastructure materials through innovative design approaches. Dr. Das investigates microstructure-property relationships in cementitious systems, with special focus on materials containing microencapsulated phase change materials for freeze-thaw durability, fiber-reinforced composites, and smart cementitious materials with self-sensing capabilities. His work integrates advanced experimental techniques like nanoindentation with computational modeling approaches including finite element analysis, molecular dynamics simulations, and machine learning algorithms to predict material behavior and optimize performance. Dr. Das's recent publications demonstrate a clear trajectory toward integrating machine learning with traditional materials science approaches. His research group has made significant contributions to understanding the behavior of cementitious composites under extreme conditions, developing multifunctional composites with embedded sensing capabilities, and creating computational frameworks that bridge multiple scales from molecular to structural levels. The work shows increasing sophistication in combining experimental validation with predictive modeling. Dr. Das has successfully secured numerous research grants as PI or Co-PI from diverse funding sources including the Office of Naval Research, Department of Defense, US Department of Transportation, and industry partners like Goetz Composites. His research portfolio spans infrastructure durability, composite materials for marine applications, and smart sensing technologies for structural health monitoring. As an educator and mentor, Dr. Das has supervised multiple doctoral and master's students who have completed theses on topics including: Multiscale simulation and machine learning-assisted performance prediction for cementitious composites Performance-based multiscale tuning of inclusion-modified and 3D printed composites Enhancing freeze-thaw durability of cementitious composites through innovative materials design Underwater explosion response of composite structures Implosion pulse mitigation using additively manufactured filler profiles

Per-Arne AndersenView profile

Associate Professor

• Artificial Intelligence
• Reinforcement Learning
• Tsetlin Machines
• +7 more

Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .

• Environmental Engineering
• Water Resource Management
• Urban Hydrology
• +3 more

Thomas Ertl is a Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), leading the Institute of Sanitary Engineering and Water Pollution Control. His research focuses on urban water systems, emphasizing sustainable drainage, climate change adaptation, and nature-based solutions. He has coordinated 55 projects, including international initiatives in Albania and Austria, addressing stormwater management, wastewater heat recovery, and sewer infrastructure resilience. Key Projects : Analysing re-activated watercourses for urban resilience (2024–2028) Resilient rainwater management in Austria (2024–2028) Assessing pollutant emissions in Albania (2024–2027) Research Themes : Building Information Modeling (BIM) in wastewater systems Uncertainty analysis under climate change Stormwater pollution and heat island mitigation Awards : 2018: Goldene Ehrennadel des ÖWAV 1993: Best student award at AGIT 93 His recent publications highlight multidisciplinary approaches to wastewater energy recovery, spatial compatibility of nature-based solutions, and prioritization of stormwater management sites. He has supervised numerous theses and contributed to media discussions on urban climate resilience, including articles in Austrian outlets like futurezone.at and Der Kurier.

Aric RindfleischView profile

Professor

• 3D Printing
• New Product Development
• Consumer Values
• +4 more

Aric Rindfleisch is the John M. Jones Professor of Marketing and Executive Director of the Illinois MakerLab at the University of Illinois Urbana-Champaign’s Gies College of Business. He serves as area chair of marketing and Vernon Zimmerman Faculty Fellow. His research focuses on 3D printing, new product development, consumer values, and AI applications in marketing. Rindfleisch has held editorial roles across 10 journals and received teaching accolades, including recognition by Princeton Review as one of America’s top professors. Education: Bachelor of Science from Connecticut State University (1987) Master of Business Administration from Cornell University (1990) Doctor of Philosophy from University of Wisconsin-Madison (1998) Rindfleisch’s research interests span innovation ecosystems, digital manufacturing, consumer behavior in the sharing economy, and materialism’s societal impact. His work bridges academic rigor with practical applications, particularly in leveraging technology like 3D printing for sustainable innovation. His recent publications highlight themes such as AI’s role in qualitative research, consumer responses to crises like the pandemic, and disruptive innovations in retail and transportation. Rindfleisch actively contributes to academic discourse through editorial roles and serves as a thought leader in marketing strategy and innovation management. Awards: Princeton Review’s “The Best 300 Professors” (2020) His leadership at Illinois MakerLab drives hands-on innovation, emphasizing collaboration between academia and industry. Rindfleisch’s work integrates marketing, technology, and consumer psychology to address modern challenges in product development and societal consumption patterns.

Gyeong HwangView profile

Professor

• Multiscale modeling
• Nanomaterials synthesis
• Energy storage systems
• +4 more

Gyeong Hwang is a Matthew Van Winkle Regents Professor of Chemical Engineering at The University of Texas at Austin. He leads the Hwang Research Group focused on computational materials discovery and design for energy and electronic applications. His work emphasizes multiscale modeling of nanostructured materials, with applications in energy storage/conversion, carbon capture, and semiconductor processing. Educational Qualifications: Ph.D., Chemical Engineering, California Institute of Technology (1999) M.S., Applied Physics, California Institute of Technology (1998) M.S., Chemical Engineering, Seoul National University (1993) B.S., Chemical Engineering, Seoul National University (1991) Research Interests: Hwang's research integrates first-principles modeling with experimental validation to address challenges in: - Surface chemistry and interfacial reactions - Nanostructured materials synthesis - Electrochemical device fabrication - CO₂ capture mechanisms His group develops computational tools for predicting material behaviors at atomic and continuum scales. Recent Publications Trends: Publications (2023-2025) focus on: - Solid-state battery interfaces - Plasma-enhanced material deposition - Ionic liquid interactions - Thermal/spatial transport phenomena - Electrochemical reaction mechanisms Awards: NSF CAREER Award (2005) Electrochemical Society's F.M. Becket Memorial Award (1999) Korean Chemical Engineering Service Award (2010) Advising & Grants: Leads interdisciplinary research funded by NSF, industry partnerships, and regents' endowments. Active in graduate student training through courses like ChE 379 (Molecular Simulation) and ChE 348 (Numerical Methods). Labs/Teams: The Hwang Research Group operates state-of-the-art computational facilities for quantum mechanics simulations and multiscale modeling. Collaborates with experimental groups globally on materials prototyping.