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Jacob BernsteinView profile

Professor

• Geometric Analysis
• Differential Geometry
• Minimal Surface Theory
• +3 more

Jacob Bernstein is a Professor and Vice-Chair in the Department of Mathematics at Johns Hopkins University (JHU), part of the Krieger School of Arts & Sciences. He holds a PhD from MIT (2009) under Tobias Colding. His research focuses on geometric analysis, particularly minimal surfaces and mean curvature flow. He co-organizes the Analysis and PDE Seminar at JHU and the Metro Area Differential Geometry Seminar with the University of Maryland and Howard University. **Education**: PhD in Mathematics, MIT (2009). **Research Interests**: Geometric analysis, minimal surface theory, mean curvature flow, and their applications in differential geometry and PDEs. His work explores topics like entropy, geometric flows, and singularities in minimal surfaces. **Teaching**: Taught courses including Real Analysis, Multivariable Calculus, Riemannian Geometry, and graduate-level Real Analysis. **Affiliations**: Active in academic leadership roles at JHU and collaborates widely with institutions like UMD and Howard. His work bridges theoretical mathematics with applications in geometry and analysis.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +5 more

Dr. Milos Hauskrecht is a Professor of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds a PhD from MIT (1997) and an M.Sc. from Slovak Technical University (1988). His primary research focuses on Artificial Intelligence, Machine Learning, and their applications in healthcare, finance, and biomedical informatics. He leads interdisciplinary projects in clinical monitoring, anomaly detection, and predictive modeling of electronic health records (EHRs). Education: PhD in Electrical Engineering and Computer Science (MIT, 1997), M.Sc. in Electrical Engineering (Slovak Technical University, 1988) Affiliations: Department of Computer Science, University of Pittsburgh; School of Computing and Information His research integrates AI with probability theory, statistics, and operations research. Key areas include planning under uncertainty, machine learning for time-series data, and AI-driven solutions for clinical decision support. Current projects involve real-time patient monitoring, hierarchical models for EHR analysis, and control of biological processes. He has advised over 20 PhD students and holds grants from NIH, DARPA, and other agencies. Notable contributions include outlier detection in clinical actions, temporal predictive patterns, and state-space models for healthcare data. His work emphasizes translating AI advancements into practical clinical tools for improved patient care.

Ciarán HanleyView profile

Lecturer

• Structural Engineering
• Bridge Design and Assessment
• Infrastructure Management
• +5 more

Dr. Ciarán Hanley is a Lecturer in Structural Engineering at University College Cork (UCC), specialized in bridge and infrastructure systems. He holds a PhD in Civil Engineering from UCC (2017), following a BEng (Ord) and BE (Hons) in Civil Engineering (2010–2012). His research focuses on performance-based design, structural safety, and sustainable infrastructure, with contributions to bridge management systems and life-cycle assessment. He serves as a technical reviewer for journals like Structure and Infrastructure Engineering and ICE - Bridge Engineering , and is a board member of the Civil Engineering Research Association of Ireland. Education: BEng (Ord) Civil Engineering, UCC, 2010 BE (Hons) Civil Engineering, UCC, 2012 PhD Civil Engineering, UCC, 2017 Professional Memberships: Institution of Structural Engineers (IStructE) International Association of Bridge and Structural Engineering (IABSE) Fédération Internationale du Béton (FIB) International Association of Shell and Spatial Structures (IASS) His research interests emphasize probabilistic design, structural reliability, and resilience of infrastructure. Key themes include multivariate analysis of bridge networks and the integration of sustainability into infrastructure management. He has contributed to EU projects like TU1406 and serves as Rapporteur for EuroStruct. His publications span over a dozen peer-reviewed articles in journals like Journal of Structural Integrity and Maintenance and Proceedings of the ICE . Dr. Hanley’s teaching includes courses on structural mechanics, prestressed concrete, and design studios. He was a finalist for Engineers Ireland Chartered Engineer of the Year (2019) and actively engages in consultancy for bridge and marine structure design.

Ruitao LinView profile

Assistant Professor

• Bayesian adaptive design
• Robust Bayesian methods
• Meta-analytic trial design
• +6 more

Dr. Ruitao Lin is an Assistant Professor in the Department of Biostatistics at The University of Texas MD Anderson Cancer Center and an Adjunct Assistant Professor at Rice University. He holds a PhD in Biostatistics from The University of Hong Kong (2012–2016) and completed postdoctoral training at the University of Washington and MD Anderson. His research focuses on Bayesian adaptive designs, robust statistical methods, and clinical trial methodologies, particularly in oncology and precision medicine. He leads the development of novel Bayesian approaches for dose-finding in phase I/II trials, meta-analytic trial designs, and high-dimensional data analysis. Dr. Lin is an Associate Editor for Contemporary Clinical Trials , Biometrical Journal , and Pharmaceutical Statistics , and has contributed to software tools like the BOIN design suite and TITE-BOIN12. His work bridges statistical innovation with practical clinical challenges, including late-onset toxicities in immunotherapy and heterogeneous treatment effects. He has secured NIH funding (e.g., R01CA261978) and collaborated with academic and industry partners to advance trial design and analysis. His software platforms, including R packages and Shiny apps, enable clinicians to implement cutting-edge statistical methods in real-world settings. Education : PhD, Biostatistics, The University of Hong Kong (2016); Postdocs at University of Washington (2016–2017) and MD Anderson (2017–2019). Grants : NIH/NCI R01CA261978 (2021–2025), focusing on Bayesian methods for precision oncology trials. Teaching : Teaches clinical trial design courses at Rice University and UTHealth. Labs/Software : Developed the BOIN design suite, TITE-BOIN12, and other tools for dose-finding and phase I/II trials.

Bertram F. MalleView profile

Professor

• Moral Psychology
• Social Cognition
• Human-Machine Interaction
• +3 more

Bertram F. Malle is a Professor of Cognitive and Psychological Sciences at Brown University, holding a joint appointment in the Department of Cognitive and Psychological Sciences. He is affiliated with the Humanity-Centered Robotics Initiative and has collaborated with institutions like the Army Research Laboratory and the Office of Naval Research. His academic journey includes a Master’s in Philosophy/Linguistics (1987) and Psychology (1989) from the University of Graz, Austria, followed by a Ph.D. in Psychology from Stanford University (1995). Before joining Brown in 2008, he was at the University of Oregon. His research focuses on moral psychology, social cognition, and human-robot interaction. Key interests include moral judgments, blame attribution, social norms, and the cognitive foundations of human-machine collaboration. He has been funded by NSF, DARPA, and the Department of Defense, among others. Malle’s work bridges psychology, philosophy, and AI, emphasizing moral competence in robots and the societal implications of human-robot interaction. His awards include the SESP Outstanding Dissertation Award (1995), NSF CAREER Award, and the 2019 SESP Scientific Impact Award. He is also a Fellow of multiple prestigious societies, including APS and SPSP. His teaching spans courses like Social Psychology, Moral Psychology, and Multivariate Statistics. Collaborators include experts in computer science and robotics, reflecting his interdisciplinary approach to advancing human-centric AI systems.

• Food Engineering
• Food Packaging
• Food Process Engineering
• +4 more

Professor Keshavan Niranjan is a faculty member at the University of Reading, serving as Director of the Global Engagement Office. His academic roles include leading international academic programs in teaching and research. He holds a BChem Eng, MChem Eng, and a PhD (tech), and is a Fellow of the Institute of Food Science and Technology (FIFST) and the International Academy of Food Science and Technology. His research focuses on food engineering, particularly in foam stability, sustainable food packaging, high-pressure food processing, and enzyme-assisted extraction. Notable projects include developing plant-based food systems, antimicrobial coatings, and reducing acrylamide in deep-fried products. He supervises PhD projects on topics like date fruit resource recovery and enzymatic protein modification for food processing. Professor Niranjan has authored numerous publications and book chapters, including contributions to Journal of Food Engineering and Food Hydrocolloids . His editorial roles include Editor-in-Chief of Foods and roles at Food and Bioproducts Processing and Scientific Reports . Awards include a Lifetime Achievement Award (2015) and Distinguished Service Award (2019) from the International Association of Engineering and Food.

Catherine WolframView profile

Assistant Professor

• Complex Analysis
• Probability Theory
• Geometry
• +3 more

Catherine Wolfram is a Gibbs Assistant Professor at Yale University and a National Science Foundation (NSF) postdoctoral fellow. She holds a PhD in Mathematics from MIT (2024), advised by Scott Sheffield, and an undergraduate degree from the University of Chicago. Her research focuses on complex analysis, probability, and geometry, with applications to statistical mechanics and random surfaces. She has presented her work at institutions including the University of Michigan, Columbia University, and international conferences such as the World Congress on Probability and Statistics. Her recent activities include talks on dimer models, holography in mathematical physics, and Teichmüller theory. Catherine has also engaged in teaching roles at MIT, leading recitations in probability and multivariable calculus. Her research has been supported by NSF postdoctoral funding, and her work has been published in journals like International Mathematics Research Notices (IMRN). She actively collaborates with researchers in probability, geometry, and mathematical physics, evidenced by her co-authored papers and participation in workshops at IHES, CIRM, and the Fields Institute.

Elli AnastasiadiView profile

Assistant Professor

• Formal Verification
• Concurrency Theory
• Parallel Programs
• +7 more

Elli Anastasiadi is an Assistant Professor in the Department of Computer Science at Aalborg University, part of the Technical Faculty of IT and Design. She is a member of the DEIS (Distributed, Embedded and Intelligent Systems) research group, which focuses on formal methods, verification, and intelligent systems. Prior to her current role, she was a postdoctoral researcher at Uppsala University and completed her PhD at Reykjavik University. Education: PhD in Computer Science, Reykjavik University (2022) Master’s in Applied Mathematics and Computer Science, NTUA, Greece Her research centers on formal verification of concurrent and parallel systems , with emphasis on runtime verification, process algebra, and logical foundations. She works extensively with hyperproperties, modal logic, and equational reasoning. Her work bridges theoretical computer science with practical verification tools. Recent publications show a strong trend in logic-based verification , particularly in modal and temporal logics, recursion, and monitor synthesis. Her work often involves complexity analysis and axiomatization of logical systems. Scientific Awards: PhD grant from Reykjavik University research fund She has advised no publicly listed students yet and is actively involved in academic service, including co-organizing workshops and being an invited speaker. She collaborates closely with leading researchers in concurrency theory and formal methods. Labs and Teams: Member of the DEIS research group at Aalborg University, contributing to projects on verification, distributed systems, and intelligent decision-making.

• Decision Analysis
• Health Economics
• Global Health
• +3 more

Dr. Abigail Colson is a Senior Lecturer in the Department of Management Science at Strathclyde Business School, University of Strathclyde. She specializes in decision and uncertainty analysis with a focus on public health, including expert judgment elicitation methods. Her work addresses global health challenges such as antimicrobial resistance (AMR) and health evaluation in low-resource settings. She holds a PhD in Management Science from the University of Strathclyde, an MPP from the University of Chicago, and a BA in political science and environmental studies from American University. Her research integrates structured expert judgment techniques to inform policy decisions, particularly in cost-effectiveness analysis, benefit-cost prioritization, and health technology assessment. Recent projects include quantifying future AMR trends, evaluating child mental health interventions, and designing antibiotic financing models. She collaborates with international organizations and governments to strengthen healthcare systems in developing countries. Key areas: AMR forecasting, global health economics, expert elicitation protocols Notable projects: EFSA EKE Training, Credible Routes to GB Electricity Collapse Study Professional roles: Principal Investigator on multiple grants, Resident Scholar at Center for Disease Dynamics Dr. Colson’s publications emphasize methodological innovations in decision-making frameworks and their application to pressing global health issues. She develops training programs for structured expert judgment and advocates for evidence-based policy across diverse sectors.

• Construction Engineering
• Simulation Science
• Information Technology in Construction
• +3 more

Simaan Abourizk, PhD, PEng, is the Dean of the Faculty of Engineering at the University of Alberta and holds the rank of Professor in Construction Engineering and Management. He also served as the NSERC/Alberta Construction Industry Research Chair (1997–2011) and Canada Research Chair in Operations Simulation (2001–2008). His roles include Executive Board membership at the Construction Research Institute of Canada. Education: Doctor of Philosophy in Construction Engineering and Management from Purdue University (1990), Master of Science and Bachelor of Civil Engineering (Honors) from Georgia Institute of Technology (1985 and 1984). Research focuses on advancing simulation technologies for construction and natural resource industries, including: Development of the Simphony simulation environment and COSYE framework Integration of AI, visualization, and scheduling tools (e.g., SmartEst, MTRACK) Optimization of tunneling, modular assembly, and industrial fabrication processes Key awards include the E. Whitman Wright Award (2002), E.W.R. Steacie Memorial Fellowship (2001), and Walter Shanly Award (2001). Current projects emphasize synthetic environments, safety analytics, and data-driven decision support systems in construction. He leads initiatives on risk simulation, resource allocation, and industrial automation.

• Digital Twins
• Smart Cities
• Blockchain Technology
• +5 more

Noel Crespi is a Professor and Director of Studies at Telecom SudParis, part of Institut Polytechnique de Paris. He leads research in the NeSS group and is affiliated with SAMOVAR, a prominent research laboratory focusing on networks, systems, and services. His work spans multiple domains in telecommunications, networking, and smart systems. His primary research interests include digital twins for smart cities, blockchain technologies, Internet of Things (IoT) security and applications, 5G/6G networking, and machine learning applications in network management. He has published extensively on these topics, with over 100 publications in top-tier journals and conferences. His recent work shows a strong focus on digital twin applications for urban management, particularly in traffic and air quality monitoring. He has developed modular frameworks for smart city digital twins that integrate real-time data from multiple sources. His research also explores blockchain applications for network security, access control, and service provisioning in next-generation cellular networks. Dr. Crespi has received significant recognition for his work on digital twins, with his 2020 paper "Digital twin in the IoT context" in Proceedings of the IEEE being highly cited. His current research explores the integration of AI with digital twin technologies for sustainable urban development. He has supervised numerous PhD students and collaborates extensively with researchers across Europe and internationally. His work often involves interdisciplinary approaches, bringing together computer science, networking, urban planning, and environmental science. Dr. Crespi has been instrumental in developing frameworks for network digital twins, with applications in traffic management, air quality monitoring, and resource allocation in smart cities. His research demonstrates practical implementations in cities like Madrid, showing measurable improvements in urban management.

John HughesView profile

Associate Professor

• Biostatistics
• Health Data Science
• Statistical Computing
• +6 more

John Hughes, PhD, is an Associate Professor and Chair of the Department of Biostatistics and Health Data Science at Lehigh University's College of Health. With nearly 30 years of experience in higher education, he has held positions at institutions including Frostburg State University, the University of Minnesota, and Pennsylvania State University. His methodological research focuses on statistical models for dependent data, Bayesian methods, and spatial and spatiotemporal analysis. He has developed numerous software packages for R and Perl, including copCAR , ngspatial , and krippendorffsalpha . Dr. Hughes' interdisciplinary work spans environmental health, bioimaging, vaccine hesitancy, and spatial epidemiology of HPV-related cancers. He has consulted for organizations such as the Courage Kenny Research Center and Temple University. His education includes a PhD in Statistics from Penn State University and an MS in Applied Computer Science from Frostburg State University. His research emphasizes statistical computing and the application of advanced models to health data. Recent work includes methodologies for agreement coefficients, environmental noise measurement, and spatial analysis of vaccination refusal patterns. Dr. Hughes teaches courses in biostatistics, data science, and programming, reflecting his dual role as a teacher-scholar. Professional contributions include software development, collaborative research projects, and academic leadership. His work bridges computational innovation and real-world health challenges, positioning him as a key figure in modern biostatistical research.

• Analytical Chemistry
• Elemental and Isotopic Analysis
• Inductively Coupled Plasma Mass Spectrometry (ICP-MS)
• +7 more

Anastassiya Tchaikovsky is a postdoctoral researcher at the Institute of Analytical Chemistry, Department of Natural Sciences and Sustainable Resources, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds a PhD in analytical chemistry and has an extensive research background in elemental and isotopic analysis, particularly using ICP-MS techniques. Her work spans food authentication, environmental forensics, and trace metal speciation. Her research interests include: Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Chemometrics and multivariate data analysis Isotopic and elemental fingerprinting for provenance determination Metrology and method validation Separation techniques coupled to mass spectrometry Applications in food science, ecology, and human health Her recent publications demonstrate a strong trend toward interdisciplinary applications of analytical chemistry, particularly in verifying the geographical origin of food products (e.g., carrots, caviar, fish) using combined isotopic, elemental, and metabolomic fingerprints. She frequently employs chemometric modeling and data fusion techniques to enhance discrimination power. Her work also extends to biomedical applications, such as iron metabolism in neurodegenerative diseases and lead detoxification. She has received multiple scientific awards, including: Scholarship for a postdoc mentoring program (2019) Best talk award at DocDay, Tulln (2014) ESF-Studienabschluss scholarship (2013) Merkur scholarship from TU Vienna (2013) Best student lecture award at ICPMS Anwendertreffen (2012) Science scholarship from TU Vienna (2012) She has been involved in several research projects funded by the European Commission, Austrian federal and local governments, and private institutions. Her collaborative work includes advising on fish migration, caviar traceability, and citizen science initiatives like IsoPROTECT. She actively presents her research at international conferences and contributes to knowledge transfer in food safety and analytical methodology. She is affiliated with the Institute of Analytical Chemistry at BOKU and has no listed advisees, though she collaborates extensively with senior researchers and interdisciplinary teams.

Alan PegnaView profile

Associate Professor

• Cognitive Neuroscience
• Clinical Neuropsychology
• Emotional Face Processing
• +5 more

Associate Professor Alan Pegna is a neuropsychologist at the School of Psychology, University of Queensland, where he has been faculty since 2015. His research focuses on cognitive neuroscience and clinical neuropsychology, with particular expertise in visual and emotional processing using EEG methodologies. Dr. Pegna received his Masters in Psychology from the University of Geneva (Switzerland) followed by a second Masters in Human Physiology from University College London (UK). He completed his PhD at the University of Geneva, where he used brain imaging techniques to study spatial processing in both healthy controls and brain-damaged patients. His research interests center on the neural mechanisms underlying emotional face processing, particularly examining how the brain responds to different facial expressions and variations in perceived approachability and trustworthiness. He has extensive experience working with brain-damaged individuals to investigate the role of specific brain regions in visual and emotional processing. His work frequently employs EEG to measure early neural responses to emotional stimuli under various attentional conditions. Analysis of his recent publications reveals a consistent focus on emotional face processing using EEG methodologies. His work examines how spatial attention, visual awareness, and task relevance modulate neural responses to emotional faces. Key themes include the role of the amygdala in emotional processing, perspective taking in social cognition, blindsight phenomena, and the neural correlates of trustworthiness and dominance perceptions. Dr. Pegna has maintained an active research program since joining UQ in 2015, with over 150 journal articles and 30 conference papers to his name. His work demonstrates strong international collaboration, particularly with researchers in Switzerland and other European institutions. His laboratory specializes in EEG research on visual and emotional processing, with particular expertise in studying both healthy participants and individuals with neurological conditions. Current research focuses on how the brain processes emotional facial expressions under varying conditions of attention and awareness, with implications for understanding social cognition disorders.

• Statistics
• Machine Learning
• Financial Econometrics
• +5 more

Jennifer Chan is a Professor in the Statistics Department at the University of Sydney's Faculty of Science. She earned her PhD from the University of New South Wales in 1997 and previously lectured at the University of Hong Kong before joining her current institution in 2006. Her research integrates statistical and machine learning models with applications in finance and insurance, including volatility modeling, Bayesian methods, and neural network applications. Her interdisciplinary research focuses on: Generalized linear mixed models and multivariate volatility measures Machine learning techniques for financial risk assessment Bayesian robustness and portfolio optimization Time-series analysis of cryptocurrencies and equity markets Recent publications demonstrate strong focus on Bayesian models in finance (42% of last 15 papers), machine learning applications (33%), and actuarial science (25%), with emerging emphasis on neural networks for financial forecasting. Awards & Honors: Second prize, Natural Science Award of China's Ministry of Education (2008) National Drug Strategy Research Scholarship (1994-1996) She supervises doctoral candidates working on machine learning applications in finance and insurance. Her international collaborations include institutions in Israel, Japan, Malaysia, and the United States.