Find Academic Supervisors

• Stochastic Processes
• Financial Mathematics
• Systemic Risk
• +6 more

Jean-Pierre Fouque is a Professor in the Department of Statistics and Applied Probability (PSTAT) at the University of California, Santa Barbara. His research focuses on stochastic processes, financial mathematics, systemic risk, and reinforcement learning, with a particular emphasis on mean field games and multi-scale stochastic models. He explores applications in portfolio optimization, risk management, and algorithmic finance. His work combines theoretical advancements in stochastic analysis with practical applications in economics and finance. Notable contributions include developing models for systemic risk in financial networks, analyzing reinforcement learning algorithms in mean-field frameworks, and studying stochastic volatility effects in derivatives pricing. Recent research trends include integrating deep learning techniques for systemic risk quantification, advancing multi-scale asymptotic methods for portfolio optimization, and investigating strategic interactions in financial systems using game-theoretic approaches. His publications frequently address topics such as stochastic volatility calibration, optimal investment strategies under uncertainty, and the dynamics of financial markets under stress scenarios. Dr. Fouque has contributed to foundational textbooks and edited volumes on systemic risk and mean field games. His interdisciplinary work bridges probability theory, mathematical finance, and computational methods, impacting both academic research and practical risk management practices.

Max LauView profile

Assistant Professor

• Infectious Disease Dynamics
• Machine Learning
• Artificial Intelligence

Max Lau is an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Epidemiology at Emory University. His research focuses on integrating machine learning and computational methods with epidemiological and genomic data to study infectious disease dynamics. He teaches courses such as BIOS 790R (Advanced Seminar in Biostatistics) and DATA 534 (Applied Machine Learning). Dr. Lau's work emphasizes scalable Bayesian inference, graph neural networks, and stochastic modeling to address challenges in disease transmission, outbreak control, and pathogen evolution. His recent research includes developing tools like ScITree and Epilearn, and he has contributed to understanding measles dynamics, tuberculosis treatment, and livestock disease management. His academic contributions span over 30 publications since 2010, with a particular focus on phylodynamics, epidemic modeling, and vaccine strategy evaluation. His interdisciplinary approach bridges computational methods with public health applications, aiming to enhance disease prediction and intervention efficacy.

• HVDC systems
• Power system protection
• Converter modelling
• +3 more

Sahar Pirooz Azad is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. She holds a PEng designation and specializes in power systems engineering, particularly in HVDC systems and grid stability. Previously, she served as an Assistant Professor at the University of Alberta (2015–2017) and conducted postdoctoral research at the University of Toronto’s CAPE Centre and KU Leuven in Belgium. Her research focuses on enhancing power grid stability through advanced control schemes for HVDC grids, converter modeling, and fault protection mechanisms. Dr. Azad’s work addresses challenges in multi-terminal HVDC systems, offshore wind grid integration, and multi-vendor system compatibility. She has taught courses like Power System Protection and Relaying (ECE 765) and Electromechanical Energy Conversion (ECE 260), reflecting her expertise in both theoretical and applied electrical engineering. Her recent publications emphasize innovative protection schemes for HVDC grids, fault detection algorithms using signal processing (e.g., Hilbert-Huang Transform), and robust controller designs for multi-vendor VSC systems. These contributions aim to improve grid reliability, fault resilience, and renewable energy integration efficiency. Dr. Azad is actively recruiting graduate students and holds Sole-Supervisory Privilege Status (SSPS) at Waterloo. Her research has been supported by European Commission-funded projects like MEDOW and leverages interdisciplinary approaches to tackle modern grid challenges.

Deepak GanesanView profile

Professor

• Networking and Distributed Systems
• Mobile and Sensor Systems
• Human-Computer Interactions
• +3 more

Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.

• Data Visualization
• Scientometrics
• Science of Science
• +4 more

Katy Börner is a Professor affiliated with Indiana University, Bloomington, USA. Her research focuses on data visualization, scientometrics, and the science of science, with contributions to tools like Network Workbench (NWB) and Sci2. She leads interdisciplinary projects such as the Human Reference Atlas and explores visualization literacy in education and public health. Her work spans virtual reality applications, biomedical knowledge networks, and AI-driven scientific discovery. Key research interests include mapping scientific collaboration networks, analyzing scholarly publications, and developing visualization frameworks for big data. She collaborates widely with institutions like NIH and VIVO, advancing open science and interdisciplinary research. Her projects often bridge computational methods with human-centric design, enhancing understanding of complex systems in health, technology, and social sciences. Publications highlight innovations in interactive visualization tools (e.g., opioid crisis research networks), data integration (Human Reference Atlas), and AI applications in biomedical research. She emphasizes translating data into actionable insights through visual analytics, impacting policy, education, and healthcare.

Pourang IraniView profile

Professor

• Human-Computer Interaction
• Information Visualization
• Ubiquitous Computing
• +4 more

Pourang Irani is a Professor and Principal’s Research Chair in Ubiquitous Analytics at the University of British Columbia (Okanagan campus), within the Irving K. Barber Faculty of Science’s Department of Computer Science, Mathematics, Physics and Statistics. Previously, he served at the University of Manitoba for 19 years as a faculty member and Acting Associate Dean of Science. His research focuses on Human-Computer Interaction (HCI), Wearable Computing, and Information Visualization, with an emphasis on designing interactive systems for 'anytime, anywhere' sensemaking using emerging technologies like mixed reality and smart devices. He leads interdisciplinary projects such as the NSERC CREATE grant on Visual and Automated Disease Analytics, training data scientists in health analytics. Education: PhD in Computer Science (University of New Brunswick, 2002), supervised by Dr. Colin Ware. Research Interests: Wearable interfaces (smartwatches, smartrings, and AR/VR) Data visualization for health and pervasive systems Persuasive health technologies and data storytelling Mid-air and hands-free interaction techniques Embodied interaction through social robots Recent Work Trends: Articles emphasize innovations in smartwatch interaction (e.g., bezel-to-bezel gestures), tactile visualizations via skin-dragging, and voice assistant-driven health data queries. Projects like Databiting explore transient personal data exploration, while Data Videos focus on narrative-driven health communication. Grants & Leadership: Principal Investigator of NSERC CREATE Visual and Automated Disease Analytics program. Co-leads UBCO’s Digital Transparency cluster. Active in interdisciplinary teams addressing health informatics and HCI challenges. Labs & Teams: Leads a lab developing prototypes in wearable computing, spatial analytics, and immersive technologies. Collaborates with researchers in medicine, engineering, and data science to translate HCI innovations into practical solutions.

Laura AlbertView profile

Professor

• Operations Research
• Public Safety
• Emergency Management
• +4 more

Laura Albert is a Professor of Industrial & Systems Engineering at the University of Wisconsin-Madison and former David H. Gustafson Department Chair (2021-24). She serves as a Fellow of AAAS and IISE, and previously held the INFORMS presidency. Her research focuses on optimizing public-sector systems, with applications in critical infrastructure protection, emergency response, and cybersecurity. She advocates for public engagement through op-eds and blogs like 'Punk Rock Operations Research.' Education: PhD in Industrial Engineering, University of Illinois at Urbana-Champaign (2006) MS in Industrial Engineering, University of Illinois at Urbana-Champaign (2001) BS in Industrial Engineering, University of Illinois at Urbana-Champaign (2000) Research Interests: Dr. Albert’s work bridges operations research and public policy, addressing challenges in emergency medical services, voting system security, law enforcement strategies, and opioid treatment diversion programs. She employs mathematical optimization, game theory, and stochastic modeling to design resilient systems. Awards: INFORMS Impact Prize (2018) NSF CAREER Award (2011) Fulbright Award (2020) AAAS Fellow (2020) Advising & Grants: While explicit student names aren’t listed, her research has been supported by grants from the NSF, Army Research Office, and other agencies. She advises on interdisciplinary projects involving public health, cybersecurity, and disaster management. Labs/Teams: Engaged in collaborative efforts across the College of Engineering, including affiliations with the Electrical & Computer Engineering department. Leads initiatives on resilient infrastructure and emergency response systems.

• Computer Science
• Software Engineering
• Artificial Intelligence
• +5 more

Dongwoo Kim is a researcher affiliated with Hanyang University, ERICA Campus (Department of Electronics and Communication Engineering) and has previously collaborated with institutions like POSTECH , Chungnam National University , and Microsoft . His work spans interdisciplinary domains in Computer Science and Engineering . Hanyang University, ERICA Campus - Department of Electronics and Communication Engineering POSTECH - Power Analog Electronics & Semiconductor Devices Lab Microsoft Chungnam National University Kim's research focuses on formal verification of automotive control software, deep learning applications in environmental monitoring, 3D modeling for indoor positioning, and machine learning for signal processing. His recent publications highlight advancements in graph neural networks (GNNs), including analyzing oversmoothing and gradient dynamics, as well as developing geometric vision-language models with domain-agnostic encoders. His 15 most recent articles (2023-2025) address topics like: Optimizing hybrid electric vehicle engine performance 3D modeling for indoor localization GNN training stability UAV-based environmental monitoring Algorithm difficulty prediction for programming problems Millimeter-wave antenna design Kim collaborates with researchers in software engineering , signal processing , and environmental science domains. His work intersects formal methods , applied machine learning , and embedded systems research.

Richard M. SternView profile

Professor

• Speech Recognition
• Audio Signal Processing
• Music Information Retrieval
• +3 more

Richard M. Stern is a Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), holding courtesy appointments in the Language Technologies Institute and Department of Computer Science, and serving as an Artist Lecturer in the School of Music since 2007. His interdisciplinary work bridges engineering and music technology through the School of Music's programs. Education: Ph.D. in Electrical Engineering from Massachusetts Institute of Technology (MIT), 1976 Professor Stern's research spans sound, speech, hearing, and music, with core emphases on robust speech processing in variable acoustic environments, music information retrieval, automated accompaniment, and foundational contributions to binaural perception theory. His work integrates psychoacoustic principles with machine learning to address challenges in speech recognition and human-robot interaction. Recent publications (2022-2025) reveal intensified focus on deep learning for speech enhancement in reverberant/noisy conditions, human-robot interaction scenarios, and music tagging—highlighting innovations in beamforming, source separation, and temporal modulation modeling. Awards and Honors: Fellow of the IEEE Fellow of the Acoustical Society of America Fellow of the International Speech Communication Association (ISCA) ISCA Distinguished Lecturer Allen Newell Award for Research Excellence (1992) Lutron Award for Teaching Excellence (2018) Professor Stern has advised numerous graduate students in speech and audio research, though specific names are unlisted in source materials. His grant portfolio includes significant National Science Foundation and industry-funded projects in speech technology, with leadership roles in initiatives like Interspeech 2006. He actively collaborates with CMU's Language Technologies Institute and Music and Technology program. He maintains strong ties to CMU's interdisciplinary ecosystem through the Language Technologies Institute and School of Music's Music and Technology program, contributing to research that merges acoustic engineering with musical applications.

Jan Dirk WegnerView profile

Associate Professor

• Machine Learning
• Computer Vision
• Remote Sensing
• +7 more

Jan Dirk Wegner is an Associate Professor at the University of Zurich, holding the chair in 'Data Science for Sciences' and leading the EcoVision Lab. He previously served as a Postdoc (2012–2016) and senior scientist (2017–2020) at ETH Zurich's Photogrammetry and Remote Sensing Group, following his PhD (with distinction) from Leibniz University Hannover (2011). His research bridges machine learning, computer vision, and remote sensing to address environmental and geoscience challenges, focusing on large-scale environmental data analysis, vegetation monitoring, and climate change mitigation. Education: PhD (with distinction) in Geodesy, Leibniz University Hannover (2011) Postdoc, ETH Zurich (2012–2016) Senior Scientist, ETH Zurich (2017–2020) Research Interests: Machine Learning, Computer Vision, Remote Sensing, Environmental Science, Climate Science, Geosciences, Explainable AI, Uncertainty Quantification, and Applications in Sustainability. The EcoVision Lab develops data-driven methods for global-scale environmental monitoring, including vegetation parameter mapping, flood prediction, forest degradation detection, and AI-driven ecological modeling. Awards: ETH Postdoctoral Fellowship (2012–2016) Science Prize of the German Geodetic Commission WEF Young Scientist Class 2020 (Top 25 globally under 40) Advising & Leadership: Director of the University of Zurich's Doctoral School in Data Science, leading the EcoVision Lab, and coordinating the CVPR EarthVision Workshops. His roles include Vice President of ISPRS Technical Commission II, member of the ETH AI Center, ELLIS, and UN-ETH Partnership. Labs/Teams: EcoVision Lab focuses on interdisciplinary AI applications for environmental challenges, collaborating with NGOs, governments, and industry to translate research into societal impact.

• Medical Genetics
• Nephrology
• Genomics
• +3 more

Dr. Ian Wilson is a researcher at Newcastle University with a focus on medical genetics, nephrology, and genomic analysis. His work spans genetic determinants of kidney diseases, mitochondrial disorders, and biomarker development. Notable contributions include studies on uromodulin genetics in African populations, copy-number variations in rare diseases, and kidney ciliopathies. He has collaborated extensively on projects involving genome sequencing, mitochondrial replacement therapy, and muscular dystrophy biomarkers. Wilson's research integrates computational tools like machine learning for predictive modeling in urolithiasis and employs advanced imaging techniques for disease progression monitoring. Key areas: Genetic epidemiology, renal genomics, mitochondrial DNA analysis Focus on translational applications: Biomarker development for kidney stones and muscular dystrophies Interdisciplinary collaborations in ophthalmology and orthopedics His publications reflect a commitment to advancing diagnostic accuracy and understanding complex genetic disorders through multi-omics approaches.

Halim YanikomerogluView profile

Professor

• Wireless Communications
• 5G/6G Networks
• Cellular Networks
• +9 more

Halim Yanikomeroglu is a Full Professor and Chancellor's Professor at Carleton University's Department of Systems and Computer Engineering, part of the Faculty of Engineering and Design. His research focuses on wireless communications, including 5G/6G networks, non-terrestrial systems (HAPS/LEO satellites), MIMO, and cognitive radio. He has supervised numerous graduate students and holds IEEE Fellow status and the Harold Sobol Award. His work integrates machine learning, federated learning, and sustainability into next-generation networks. Affiliations: Carleton University, IEEE Education: Ph.D. (Toronto), M.A.Sc. (Toronto), B.Sc. (Middle East Technical University) Research interests span cellular networks, relay architectures, and energy-efficient systems. He pioneered cell-switching strategies for green networks and contributed to HAPS and UAV-based infrastructure. His recent work addresses NTN integration, AI-driven spectrum management, and 6G innovations. Awards include IEEE Fellow (2017) and multiple Research.com leadership accolades. His 150+ publications span journals like IEEE Transactions and conferences like ICC. Advising over 50 students, he emphasizes interdisciplinary solutions for future wireless challenges.

Christiana MavroyiakoumouView profile

Assistant Professor

• Fluid Dynamics
• Fluid-Structure Interactions
• Vortex Dynamics
• +6 more

Christiana Mavroyiakoumou is a Courant Instructor/Assistant Professor at the Courant Institute of Mathematical Sciences, New York University. She specializes in fluid dynamics and fluid-structure interactions, with a focus on vortex dynamics, membrane flutter, and bio-inspired systems. Her research integrates modeling, numerical simulations, and experimental insights to study phenomena such as bird flock formations and fish swimming hydrodynamics. Mavroyiakoumou holds a Ph.D. from the University of Michigan (2022), an M.Sc. from the University of Oxford (2017), and a B.Sc. from Imperial College London (2016). Education: PhD in Applied & Interdisciplinary Mathematics, University of Michigan (2017–2022) MSc in Mathematical Modeling and Scientific Computing, University of Oxford (2016–2017) BSc in Mathematics, Imperial College London (2013–2016) Her research interests span fluid-structure interactions, vortex dynamics, and collective locomotion. She investigates how fluid flows mediate interactions between bodies, such as the aerodynamics of bird formations and the hydrodynamics of flapping foils. Her work bridges theoretical models with experimental observations, contributing to both fundamental science and bio-inspired engineering. Mavroyiakoumou has received prestigious awards including the Joseph B. Keller Fellowship (NYU), Peter Smereka Award (U-M), and ProQuest Distinguished Dissertation (U-M). She actively engages in academic service, organizing conferences and mentoring students. Her teaching experience includes courses on mathematical modeling, differential equations, and algebra at NYU and the University of Michigan. Key Research Themes: Flow-mediated collective behavior and instability mechanisms Vortex wake interactions and their role in locomotion Membrane dynamics in inviscid and viscous flows She collaborates with experimentalists like Leif Ristroph and Jun Zhang at NYU's Applied Math Lab, focusing on experimental validation of theoretical models. Her recent work explores self-amplifying waves in bird formations and the aerodynamic origins of flight coordination.

Ivan MartinovicView profile

Professor

• Cyber-Physical Systems Security
• Wireless Network Security
• Authentication Systems
• +3 more

Prof. Ivan Martinovic is a Professor of Computer Science at the University of Oxford's Department of Computer Science, holding a Fellowship at the institution. He specializes in cyber-physical systems security, wireless network security, and behavioral biometrics. His research focuses on authentication mechanisms, intrusion detection, and trade-offs between security and performance in systems like satellite communications, EV charging infrastructure, and aviation networks. Education: PhD (TU Kaiserslautern); MSc (TU Darmstadt, Germany). Prior roles include postdoctoral research at UC Berkeley (2011) and UC Irvine (2009–2010), supported by a Carl-Zeiss Foundation Fellowship (2009–2011). He has also been an associate lecturer at TU Kaiserslautern. Research Interests: Cyber-physical systems security, wireless networks, behavioral biometrics (e.g., continuous authentication via physiological signals), robust communication protocols, and analysis of security vs. performance trade-offs in distributed systems. Technologies include software-defined radios, NFC/RFIDs, and EEG/eye-tracking devices. Scientific Awards: Carl-Zeiss Foundation Fellowship (2009–2011). Advising & Grants: No explicit student listings; however, his work involves interdisciplinary collaborations and has been funded by government and industrial grants. His research spans labs and teams focused on satellite cybersecurity, smart infrastructure security, and biometric systems. Labs/Teams: Engages with groups exploring satellite communication security, EV charging infrastructure vulnerabilities, and behavioral authentication systems, though specific lab names are not disclosed in the text.

Scott E. DenmarkView profile

Professor

• Organic Chemistry
• Synthetic Organic Chemistry
• Organoelement Chemistry
• +5 more

Scott E. Denmark is the Reynold C. Fuson Professor of Chemistry at the University of Illinois, Department of Chemistry, within the College of Liberal Arts & Sciences. He earned his S.B. from MIT (1975) and D.Sc. Tech. from ETH-Zürich (1980) under Albert Eschenmoser. His research focuses on synthetic organic chemistry, organoelement systems (Si, P, Sn, S, Li), palladium catalysis, and chemoinformatics. He has pioneered methods in asymmetric catalysis, total synthesis of natural products, and tandem cycloaddition reactions. Denmark chairs editorial boards for top journals and leads the Denmark Group, mentoring over 100 students. Awards include the Paracelsus Prize (2020), Noyori Prize (2019), and membership in the National Academy of Sciences (2018). Education: S.B., Massachusetts Institute of Technology, 1975 D.Sc. Tech., ETH-Zürich, 1980 (Advisor: Albert Eschenmoser) Research Interests: Design of new organic reactions and catalysts Structure-reactivity relationships in organoelement systems Total synthesis of alkaloids, polyenes, and glycosides Machine learning for catalyst optimization Asymmetric phase transfer catalysis Green chemistry using water-based systems Recent Research Trends: Recent work emphasizes indium-catalyzed allylations of carbohydrates (Nature, 2025) and chemoinformatics-driven catalyst design. Collaborations with MIT and industry (e.g., Pfizer, Amgen) highlight applied impact. Awards: Paracelsus Prize (2020) Ryoji Noyori Prize (2019) Member, National Academy of Sciences (2018) Member, American Academy of Arts and Sciences (2017) Advising & Grants: Mentored 40+ PhD students and 60+ postdocs. Active in funding initiatives for chemoinformatics and sustainable catalysis. Recent grants include Pines Fellowship (2025) for student Matthew Albritton. Labs/Teams: Leads the Denmark Group at UIUC, known for interdisciplinary projects merging organic synthesis with computational methods. Collaborates globally, including with ETH-Zürich and Hiroshima University.