Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.
Jim Hall is a Professor of Climate and Environmental Risk at the University of Oxford's School of Geography and the Environment, and serves as Director of Research there. He is also a Visiting Fellow at Linacre College and holds leadership roles including Chair of the Science Advisory Committee at IIASA, and Expert Advisor to the UK's National Infrastructure Commission. His work focuses on systemic risk analysis, infrastructure resilience, and policy implications of climate change adaptation. Prof Hall has pioneered methodologies like the National Infrastructure Systems Model (NISMOD) and chairs the Data and Analytics Facility for National Infrastructure (DAFNI). His research spans flood risk management, energy systems decarbonization, and transboundary water resource conflicts in regions such as the Eastern Nile Basin and the Caribbean. Key research areas include robust decision making under uncertainty, info-gap theory applications, and integrated assessments of human-environmental systems. He has contributed to major international assessments, including the IPCC's Fourth Assessment Report, and developed frameworks for multi-hazard stress testing of infrastructure networks. Scientific Awards: George Stephenson Medal (2001), Prince Sultan Prize for Water (2018), Royal Academy of Engineering Fellowship (2010) His advising and grants work includes mentoring a DPhil student Erin Canning and leading projects like MARIUS and ENHANCE. He has also developed innovative modeling tools for coastal erosion prediction and probabilistic assessments of global shipping fuel transitions. Prof Hall’s research groups actively engage in interdisciplinary projects, including the Oxford Martin Programme on Resource Stewardship and the UK Infrastructure Transitions Research Consortium. His work emphasizes bridging scientific analysis with actionable policy solutions for climate adaptation.
Karoline Faust is an Associate Professor at KU Leuven, affiliated with the Laboratory of Molecular Bacteriology (Rega Institute) and the Faculty of Medicine . She contributes to the iSi Health and Leuven One Health institutes, and serves on senior academic councils. Her research spans microbial systems biology, focusing on community dynamics and network analysis. Education: PhD in bioinformatics (2010, KU Leuven) Affiliations: KU Leuven, ISME Journal editorial board, Belgian Society for Microbiology Her research investigates microbial community dynamics , systems biology approaches to microbiomes, and bioinformatics tool development . She specializes in modeling human gut microbiota , synthetic microbial communities , and environmental microbiomes (e.g., microplastic impacts on Daphnia microbiomes). Her work integrates metabolic modeling , network analysis , and experimental systems to understand microbial interactions. Recent publications highlight her contributions to microbial network inference , 16S rRNA sequencing protocols , microfluidics , and ecological modeling of microbiomes. She develops tools like manta , miaSim , and CoNet to analyze community structures. Teaching: Karoline co-teaches courses in microbiology, bioinformatics, and network analysis at KU Leuven, and has contributed to international workshops on microbial network inference. Scientific Engagement: She serves as Senior Editor at ISME Journal and Secretary of the Belgian Society for Microbiology .
Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .
Padhraic Smyth is a Distinguished Professor and Hasso Plattner Endowed Chair in Artificial Intelligence at the University of California, Irvine (UCI), holding joint appointments in the Department of Computer Science and Department of Statistics. He leads the DataLab research group, focusing on machine learning, AI, and their applications in climate science, healthcare, and education. His research spans probabilistic modeling, deep learning, and human-AI collaboration. Education: PhD in Electrical Engineering from the California Institute of Technology (1988), MSEE (1985), and BEng (1984). Prior to UCI, he worked at NASA's Jet Propulsion Laboratory (1988–1996). Research Interests: Machine learning, AI, pattern recognition, Bayesian methods, climate science applications, algorithmic fairness, and human-AI interaction. He has published over 200 papers and co-authored textbooks like Modeling the Internet and the Web . Awards: ACM Fellow, IEEE Fellow, AAAI Fellow, AAAS Fellow, and ACM SIGKDD Innovation Award recipient. He has held leadership roles in UCI's Center for Machine Learning and Data Science. Key Projects: Human-AI collaboration frameworks, robustness in deep learning, climate modeling using spatio-temporal data, and AI fairness with missing attributes. Collaborates with institutions like NASA and industry partners (e.g., Google, eBay). Labs/Teams: Director of UCI’s Data Science Initiative and HPI Research Center in Machine Learning. Supervises a vibrant PhD program with over 30 alumni in academia and industry.
Justin Sheffield is a Professor of hydrology and remote sensing and Head of the School of Geography and Environmental Science at the University of Southampton, UK. He holds a BSc in Mathematics with Oceanography (1989), MSc in Engineering Mathematics (1992), and PhD in Hydroclimatology (2008). His research focuses on large-scale hydrology, climate variability, hydrological extremes, and applications to natural hazards mitigation, with emphasis on water and food security in developing regions. Key research interests include drought monitoring/prediction, climate change impacts, and remote sensing integration. He leads projects like APP3793 (heat-related health risks) and EO-Africa (agricultural water management). Awards include the Prince Sultan Prize (2014), Plinius Medal (2013), and Robert E. Horton Lecturer (2019). His work spans global collaborations, including projects with the FAO and ESA, and he advises on PhD students. Notable publications address drought indices, crop yield modeling, and climate adaptation strategies.
Dr. Baijian "Justin" Yang serves as the Associate Dean for Research at Purdue Polytechnic Institute and is a Professor in the Department of Computer and Information Technology at Purdue University. He earned his Ph.D. in Computer Science from Michigan State University, with Master's and Bachelor's degrees in Automation (EECS) from Tsinghua University. Dr. Yang has established himself as a leader in multiple interdisciplinary research domains. Dr. Yang's educational background includes: PhD in Computer Science, Michigan State University (2002) MS in Automation (EECS), Tsinghua University (1998) BS in Automation (EECS), Tsinghua University (1995) His research interests span multiple cutting-edge domains with practical applications: Cybersecurity : Developing novel approaches for threat intelligence, security education, and network defense Big Data : Creating innovative algorithms for dimension reduction, regression with categorical variables, and tensor decomposition Applied Machine Learning : Implementing AI solutions in healthcare, manufacturing, and forestry applications Digital Forestry : Using UAV imagery and remote sensing for forest management and tree species classification Dr. Yang's publication record demonstrates significant impact across multiple disciplines, with recent work focusing on spatial transcriptomics analysis (SiGra), delirium detection using limited-lead EEG, and visual localization technologies. His research bridges theoretical advances with practical applications in healthcare, manufacturing quality control, and environmental monitoring. The interdisciplinary nature of his work is evident in collaborations spanning computer science, healthcare, forestry, and manufacturing domains. His scientific achievements have been recognized with numerous awards: 2023 HRSA Building Bridges to Better Health Competition Winner (Phase 1) and 2nd place ($100,000 prize) in Phase 3 2023 Outstanding Faculty Award in Engagement, Department of Computer and Information Technology, Purdue University 2021 Leadership in Manufacturing Award, Manufacturing Times Digital (MxD) 2021 Good to Great Award, Purdue Polytechnic 2020 Outstanding Faculty Award in Discovery, Department of Computer and Information Technology 2019 University Faculty Scholars, Purdue University As an educator and mentor, Dr. Yang has advised numerous graduate students through their PhD and Master's research. His leadership extends to significant service roles including serving as Faculty Champion for the Holistic Safety and Security research impact area at Purdue Polytechnic from 2018 to 2021, board membership with ATMAE (2014-2016), and participation in the IEEE Cybersecurity Initiative Steering Committee (2015-2017). He holds valuable industry certifications including CISSP, MCSE, and Six Sigma Black Belt, demonstrating his commitment to bridging academic research with industry practice. Dr. Yang leads multiple research projects including "Digital Forestry" for developing tools to quantify forest function, "CHEESE" (Cyber Human Ecosystem of Engaged Security Education), and "CICI" (Supporting Controlled Unclassified Information with a Campus Awareness and Risk Management Framework). His work on "Applied Machine Learning" focuses on solving real-world problems, while his "Dimension Reduction and Memory Amnestic Big Data Regression" project innovates computational algorithms for large-scale data analysis.
Sidi Wu is a Researcher affiliated with ETH Zürich's Institute of Cartography and Geoinformatics. Their primary role is as Staff of the Professorship for Cartography, contributing to academic research and technical operations within the department. They are based at HIL G 23.2, Stefano-Franscini-Platz 5 in Zürich, Switzerland, and can be reached at sidiwu@ethz.ch. Research interests center on advancing AI-driven cartographic methods, historical map analysis, and environmental spatial dynamics. Specific focuses include generative AI applications in map-making, semantic segmentation of historical documents, and leveraging digitized maps for ecosystem studies. They also explore steganography in image translation and cross-domain adaptation techniques for geospatial data. Recent work emphasizes innovations in automated map storytelling systems, spatio-temporal context modeling using transformers, and weakly supervised learning approaches for map segmentation. Their studies frequently bridge cartography with environmental science disciplines like hydrology and urban morphology. No scientific awards or grants are explicitly listed in the provided information. While no advisees are documented here, their research collaborations likely involve student contributions. They are part of the core team at the Institute of Cartography and Geoinformatics, contributing to cutting-edge projects in geomatics and computational cartography.
Lorenzo M. Polvani is the Maurice Ewing and J. Lamar Worzel Professor of Geophysics at Columbia University, with dual appointments in the Department of Applied Physics and Applied Mathematics and the Department of Earth and Environmental Sciences. He has taught at Columbia for over 30 years and received multiple teaching awards. PhD in Physical Oceanography, MIT/Woods Hole Joint Program (1988) MSc and BSc in Physics, McGill University His research spans Atmospheric Science , Climate Modeling , and Arctic Studies , focusing on geophysical fluid dynamics, radiative forcing, and climate sensitivity. Recent work examines nonlinear climate responses to CO2 variations, Arctic amplification mechanisms, and volcanic aerosol impacts. Scientific publications reveal trends in radiative forcing , Arctic sea ice dynamics , stratospheric ozone effects , and climate feedback interactions . Key tools include the ClimKern Python package for radiative feedback analysis. Notable research includes: Nonlinear precipitation responses to volcanic eruptions High CO2 forcing effects on North Atlantic Oscillation Cloud feedbacks reducing hydrological sensitivity Arctic amplification through radiative-advective equilibrium Stratospheric ozone impacts on tropical climate patterns
Dr. Jessica A Eisma is an Assistant Professor of Water Resources in the Department of Civil Engineering at the University of Texas at Arlington. Her research focuses on urban and dryland hydrology, remote sensing, machine learning, citizen science, and climate change adaptation. She holds a PhD from Purdue University (2020) and prior degrees from Purdue and Michigan State University. Her work emphasizes community-centered solutions for flood resilience and green infrastructure planning in vulnerable areas. Education: PhD, Civil Engineering, Purdue University, 2020 MS, Civil Engineering, Purdue University, 2015 BS, Civil Engineering, Michigan State University, 2012 Research Interests: Urban hydrology and climate impacts on rainfall patterns Remote sensing applications for water resource management Machine learning in hydrological modeling Citizen science for environmental data collection Green infrastructure design for flood mitigation Recent Article Trends: Dr. Eisma’s recent work addresses urbanization effects on extreme rainfall, UAV-based thermal mapping of micro-urban heat islands, and equity-focused green infrastructure planning. Her publications often bridge technical innovation and community-driven solutions for climate resilience. Awards: 2024: Faculty/Staff Graduating Student Impact Reception (UTA) 2023: Emerging Leaders Award (Purdue CEG SAC) 2020: Magoon Award for Excellence in Teaching (Purdue College of Engineering) 2015: NSF Graduate Research Fellowship Advising & Grants: Advises 3 PhD students and multiple undergrad researchers Principal Investigator on grants totaling over $1M from NOAA, NSF, and others Focus areas: Houston flood resilience, Texas urban stormwater systems Lab & Teams: Leads the SEUSI Lab, dedicated to socio-environmental solutions in urban sustainability and infrastructure. Collaborates with national and international partners on water security and climate adaptation projects.
Zach Shahn is an Assistant Professor in the Department of Epidemiology and Biostatistics at the CUNY School of Public Health. He holds a PhD in Statistics from Columbia University and a BA in Mathematics from Stanford University. His research focuses on causal inference methods applied to healthcare data, particularly time-varying treatment effects and critical care applications. He has conducted postdoctoral work at Harvard School of Public Health and previously worked at IBM Research in Healthcare and Life Sciences. Education: PhD in Statistics and Probability, Columbia University BA in Mathematics, Stanford University Research interests include developing causal inference frameworks for evaluating treatment efficacy in dynamic healthcare settings, with a focus on critical care outcomes and methodological innovations. Recent work explores applications of causal diagrams, instrumental variables, and machine learning in healthcare decision-making. His studies often involve large-scale healthcare datasets to assess interventions' real-world impacts. Key trends in his articles include advancements in causal effect estimation under complex treatment regimes, bias analysis in observational studies, and methodological contributions to difference-in-differences and N-of-1 trial designs. His work bridges statistical theory with practical healthcare challenges, emphasizing reproducibility and policy relevance. No scientific awards are listed, though his contributions to causal inference methodologies are notable in academic circles. He has advised on healthcare data projects and published extensively without explicitly listed grants. His professional network includes collaborations with institutions like Harvard and IBM. He is affiliated with CUNY's public health programs and actively engages in academic discourse via Twitter and LinkedIn. His lab or team details are not explicitly mentioned in available materials.
Hugo de Boer is a Professor at the Copernicus Institute of Sustainable Development , Faculty of Geosciences, Utrecht University. He serves as scientific lead for the Delta Climate Center in Vlissingen and coordinates MSc programs in Water Science and Management and Water Management for Climate Adaptation . His research explores climate-ecosystem interactions, focusing on plant ecophysiology, ecosystem dynamics, and nature-inclusive climate adaptation in deltas. Research Themes: Future Deltas, Pathways to Sustainability, Integrative Bioinformatics Projects: LEMONTREE, CloudRoots, 'From losers to winners' (ancient plant lineages under elevated CO2) Teaching Expertise: System thinking for sustainability, quantitative statistics, plant ecophysiology Research Trends emphasize interdisciplinary approaches to climate change impacts on ecosystems, with publications spanning plant-cloud processes, CO2 acclimation, and eco-evolutionary optimality models. His work bridges biogeochemistry, land-atmosphere interactions, and sustainable development frameworks. Projects & Collaborations include experimental studies on ancient plant lineages (Equisetum) and integrative field campaigns in Amazon and temperate forests. He contributes to modeling climate-vegetation feedbacks, pesticide emission scenarios, and social-ecological system transitions.
Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.
Mehdi Abdollahi is an Associate Professor at Chalmers University of Technology's Department of Food and Nutrition Science. His research focuses on alternative proteins, food biotechnology, and plant-based hybrid foods, with emphasis on sustainable utilization of food side streams, legumes, cereals, and microalgae as future protein sources. Develops pH-shift technology and ultrasound-assisted methods for protein extraction Specializes in hybrid food engineering via fermentation and biorefinery Works on 3D food printing and high-moisture extrusion for food analogs Researches collagen and biobased food packaging materials His work includes >100 peer-reviewed publications, 4 book chapters, and 3 patents. Current projects involve collaborations with Arla Foods, Lantmännen, and Nordic Seafarm, addressing sustainable seafood systems and plant-protein hybridization. 2024 Bertebos Prize recipient 2025: Recognized among Sweden's Top 101 Sustainability Figures Mentors 7 PhD students and 3 postdocs while collaborating with European institutions like Kristianstad University and Ankara University. His group explores biorefinery strategies, hybrid food functionality, and innovative packaging solutions.
Wai Cheng is a Professor in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT), School of Engineering, and serves as Director of the Sloan Automotive Laboratory since 2009. His educational background includes: B.Sc. from California Institute of Technology (1974) M.Sc. from Massachusetts Institute of Technology (1975) Ph.D. from Massachusetts Institute of Technology (1979) Professor Cheng's research centers on internal combustion engines , with expertise in engine performance, emissions, and combustion science. His work investigates cold-start phenomena in gasoline direct injection (GDI) engines, soot formation mechanisms, knock dynamics, and the impact of alternative fuels like ethanol. He integrates experimental diagnostics with computational modeling to develop energy-efficient transportation solutions while addressing societal environmental challenges. Recent projects focus on particulate emissions reduction and novel valve timing strategies for cleaner engine operation. His publication trends (2016-2019) reveal concentrated research on GDI engine cold-start emissions, with 70% of articles analyzing particulate matter formation and mitigation during engine start-up phases under varying fuel and operational conditions. Notable honors include: Fellow of the Society of Automotive Engineers (2003) SAE Oral Presentation Awards (2004, 2002) SAE Teetor Award (1984) Carl Richard Soderberg Professorship (1982) Professor Cheng has mentored numerous graduate students through MIT's mechanical engineering programs and secured research funding from automotive industry partners. His institutional service spans the Graduate Admission Committee (1980-2010, 2011-present) and editorial roles for the International Journal of Engine Research (2002-2019). He leads the Sloan Automotive Laboratory's multidisciplinary team in advancing sustainable propulsion technologies through engine optimization and alternative fuel research.
