Find Academic Supervisors

• Mathematical Foundations of Machine Learning
• Online Convex Optimization
• Statistical Learning Theory
• +5 more

Dr. Tim van Erven is an Associate Professor at the University of Amsterdam , affiliated with the Korteweg-de Vries Institute for Mathematics . His research focuses on the mathematical foundations of machine learning , particularly adaptive methods in online convex optimization, PAC-Bayesian concentration inequalities, and robust learning strategies. Research Interests : Mathematical machine learning, explainable AI, online learning, statistical learning theory, and adaptive optimization. Grants & Awards : VICI (2025), VIDI (2019), TOP grant (2016), NIPS Outstanding Reviewer (2014), Rubicon (2011). Teaching : Involved in graduate-level machine learning and statistical learning theory courses. His recent work explores explainable machine learning and robust optimization , with a focus on algorithmic recourse, gradient filtering, and theoretical guarantees. His publications span top venues like NeurIPS, COLT, and JMLR, often addressing the intersection of statistics and machine learning. He co-organized workshops such as the AI & Mathematics (AIM) initiative and contributed to the COLT program committee. His group develops MetaGrad and other adaptive algorithms for online learning.

• Control Systems
• Operator Theory
• Signal Processing
• +5 more

Arthur E. Frazho is a Professor in the School of Aeronautics and Astronautics at Purdue University, holding this position since 1980. He earned his B.S.E., M.S.E., and Ph.D. in Computer Engineering and Control Systems from the University of Michigan, Ann Arbor. His research focuses on applying operator theory to control systems, including deterministic and stochastic models, signal processing, and inverse scattering. He has authored influential books such as An Operator Perspective on Signals and Systems (2010) and Linear Systems and Control (2003). Frazho received the prestigious 2006 W. A. Gustafson Award for teaching excellence. His work spans theoretical advancements in Hinfinity controller reduction, recursive algorithms, and multirate filterbanks. Collaborations with institutions like Vrije Universiteit, Amsterdam, highlight his international academic reach. Education: B.S.E., University of Michigan, Ann Arbor, Computer Engineering (1973) M.S.E., University of Michigan, Ann Arbor, Computer Information and Control Engineering (1974) Ph.D., University of Michigan, Ann Arbor, Computer Information and Control Engineering (1977) His research integrates operator theory with practical engineering challenges, yielding solutions for control systems, signal processing algorithms, and mathematical frameworks for system analysis. Notable contributions include relaxed commutant lifting techniques and applications to inverse scattering. Frazho has presented invited lectures globally and contributed to over 20 publications across journals and conference proceedings. Awards: 2006 – W. A. Gustafson Award (Teaching Excellence) Grants & Advising: While no student advisees are listed, Frazho has secured research grants supporting his theoretical work in control systems and operator theory. His collaborations include projects on multirate filterbanks and hydraulic cylinder analysis. Labs & Teams: No specific laboratory affiliations are detailed, but his work aligns with Purdue’s broader aerospace and systems engineering initiatives.

Kihong ParkView profile

Associate Professor

• Networking and Operating Systems
• Distributed Systems
• Information Security and Assurance
• +4 more

Dr. Kihong Park is an Associate Professor in the Department of Computer Science at Purdue University, affiliated with CERIAS and the Santa Fe Institute. His research focuses on high-speed networks, network security, distributed systems, and stochastic cellular automata. He joined Purdue in 1996 after earning his PhD from Boston University in 1996, where his thesis explored cellular automata dynamics under noise. He has authored influential works on self-similar network traffic modeling, noncooperative game theory in QoS allocation, and proactive defenses against DDoS attacks. Education: BA in Management (Seoul National University, 1988), MS in Computer Science (University of South Carolina, 1990), PhD in Computer Science (Boston University, 1996). Research interests include traffic control in IP networks, scalable network security, robust distributed systems, and cellular automata theory. His work bridges networking, security, and theoretical computer science, with contributions to both foundational understanding and practical implementations like Cisco router scheduling algorithms. He has received the NSF CAREER Award and served on editorial boards of Computer Networks and IEEE Communications Letters. Key publications include seminal work on self-similar traffic origins (SIGCOMM '96), route-based DDoS defense mechanisms (SIGCOMM '01), and noncooperative game theory in network resource allocation (JCSS 2004). His lab, the Network Systems Lab, investigates complex system behaviors in networks and distributed computing.

Charles Robert KenleyView profile

Professor

• Systems Engineering
• Modeling and Simulation
• Risk Management
• +3 more

Dr. Charles Robert Kenley is Professor of Practice at Purdue University's Edwardson School of Industrial Engineering, specializing in systems engineering methodologies. His research focuses on quantitative approaches for technology development, including Bayesian methods, risk management, and technology readiness forecasting. His work develops frameworks for system architecture synthesis, particularly for systems-of-systems and information fusion applications. Recent publications examine trade-off analytics in engineering design, technology readiness level (TRL) modeling, and verification methods for autonomous systems. He created MATLAB/Python implementations of Kalman filters using influence diagrams and contributed to smart manufacturing reference architectures. Kenley teaches graduate courses including SYS 400 (Systems Praxis), SYS 510 (Tools and Methodologies for Designing Systems), and IE 690 (Decision Models and Methods). Prior to Purdue, he held research positions at MIT's Sociotechnical Systems Research Center and Lockheed Martin, with extensive consulting experience in systems engineering.

Kathleen DonohueView profile

Professor

• Evolutionary Biology
• Plant Adaptation
• Epigenetics
• +5 more

Kathleen Donohue is a Professor of Biology at Duke University’s Trinity College of Arts & Sciences, where she has held this position since 2012. Previously, she served as an Associate Professor from 2008 to 2012. She leads the Donohue Lab, which investigates the genetic and epigenetic mechanisms underlying plant adaptation, including phenotypic plasticity, maternal effects, and niche construction. Her work emphasizes how environmental interactions shape plant life cycles and responses to climate change. Dr. Donohue earned a Ph.D. in Biology from the University of Chicago (1993) and holds degrees from Stanford University: B.A., M.S., and B.S. (all 1985). She has directed the University Program in Ecology at Duke from 2017–2020 and has held leadership roles such as President of the International American Society of Naturalists (2015). Her research focuses on seed dormancy, dispersal strategies, and the evolutionary consequences of phenological changes. Notable awards include the 2013 Guggenheim Fellowship, recognition as an AAAS Fellow (2012), and a Bullard Fellowship at Harvard University (2001). She has secured major grants from the National Science Foundation and NIH, including the Genetics Training Grant (1979–2020). Dr. Donohue’s lab actively mentors students and postdocs, with recent advisees including Brandie Quarles (Ph.D. candidate), Mariano Alvarez (Postdoc), and Emily Thayer (Research Associate). Her work is published across top journals in ecology and genetics, addressing topics like climate adaptation, transgenerational epigenetic effects, and plant invasion dynamics. She teaches courses such as BIOLOGY 453S (Gene-Environment Interaction) and BIOLOGY 263-1 (Biological Responses to Climate Change), integrating research insights into education. Her outreach includes mentoring high-school students and community engagement through Duke’s programs.

• Economic theory
• Applied economics
• Econometrics
• +3 more

Prof Martin Cripps is a Professor of Economics at University College London (UCL), Department of Economics. His academic journey includes roles at the University of Exeter (1984-1987), University of Warwick (1987-2000), and Olin Business School (2000-2006) before joining UCL in 2006. He holds a BSc, MSc, and PhD from the London School of Economics and Political Science (1981-1986). His research focuses on economic theory, applied economics, and econometrics, with a strong emphasis on strategic behavior, reputation dynamics, and Bayesian learning models. Notable themes in his work include repeated games, collusion under private information, and the interplay between experimentation and resource allocation in queues. His contributions extend to foundational topics like optimal learning strategies and the design of auctions and tenders. Prof Cripps has authored over 60 publications spanning theoretical and applied economics. His recent work explores asymptotic complexity in strategic settings and common learning mechanisms in dynamic systems. He has held editorial roles and contributed to policy discussions on economic coordination and institutional design. His academic leadership includes roles in curriculum development and interdisciplinary collaboration. He is affiliated with UCL’s Department of Economics and has advised multiple institutions on economic modeling and strategic decision-making frameworks.

• Power Electronics
• Renewable Energy Systems
• Energy Storage
• +3 more

Prof. Dylan Lu is a Professor and Head of Discipline for Electrical Power and Energy Systems at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). He holds a Ph.D. in Electronic and Information Engineering from The Hong Kong Polytechnic University (2004). Previously, he served as academic staff at the University of Sydney from 2006 to 2016, progressing from Lecturer to Associate Professor. His research focuses on power electronics, renewable energy systems, and grid integration, with an emphasis on converter topologies, control techniques, and power quality solutions for microgrids and energy storage systems. Prof. Lu's academic leadership includes roles as Associate Editor for IEEE Transactions on Industrial Electronics and IEEE Journal of Emerging and Selected Topics in Power Electronics. He chairs the IEEE NSW Joint Chapter PEL/IES/IAS and is a Senior Member of the IEEE. His teaching contributions include coordinating Renewable Energy Systems studios and supervising graduate projects in areas like electro-thermal modeling of power devices and three-port DC-DC converter synthesis. Research highlights include advancements in cascaded H-bridge converters, battery management systems, and grid-connected inverter control strategies. His work addresses challenges in high-efficiency power conversion, renewable integration, and energy storage reliability. Current projects explore fault-tolerant converter designs and predictive control algorithms for electric vehicle chargers.

Benjamin GuedjView profile

Professor

• Machine Learning
• Statistical Learning Theory
• PAC-Bayesian Theory
• +6 more

Benjamin Guedj is a Professor of Machine Learning and Foundational Artificial Intelligence at University College London (UCL) and a Research Director at Inria (France). He leads the Inria London Programme, fostering Franco-British scientific collaboration. His research focuses on PAC-Bayesian theory, generalisation in machine learning, and frugal AI. He holds a PhD from Sorbonne Université and an Habilitation à diriger des recherches. He has supervised eight PhD students and contributed over 70 research articles. Awards include the NeurIPS Best Reviewer Award and PEDR excellence bonus. He co-founded the ELLIS London Unit and chairs roles in French-British academic initiatives. Education: PhD in Mathematical Statistics (Sorbonne Université, 2013), MSc in Pure/Applied Mathematics (Sorbonne, 2010–11), postdoctoral research at Sorbonne and DTU Compute. Research interests span statistical learning, PAC-Bayes, computational statistics, and deep learning. Grants: Led ANR projects BEAGLE/APRIORI (€180k each), Inria's 6PAC project, and EU-funded PERF-AI (€600k). Awards: Multiple best reviewer recognitions, Young Leader of Franco-British Council. Advising: Current PhD students include Chloé Hashimoto-Cullen and Reuben Adams; alumni include Théophile Cantelobre and Felix Biggs. His group explores PAC-Bayes, generalisation, and AI ethics. Labs/Teams: Co-director of ELLIS London, Inria Modal team, and UCL Centre for AI. Serves as associate editor for JMLR/TMLR and chairs ICML/PAC-Bayes workshops.

Sy-Miin ChowView profile

Professor

• Dynamical Systems Modeling
• Emotion Regulation
• Longitudinal Data Analysis
• +5 more

Sy-Miin Chow is a Professor in the Department of Human Development and Family Studies at Pennsylvania State University and Director of the Quantitative Developmental Systems Methodology Core (Quantdev). She leads the Emotions and Dynamic Systems Lab, focusing on developing dynamical systems models to study emotion regulation and longitudinal data analysis in social sciences. Her work integrates Kalman filters, state-space models, and machine learning to understand complex behavioral processes. Dr. Chow holds a Ph.D. in Quantitative Psychology from the University of Virginia. Her research spans emotion dynamics, family systems, and health interventions, with recent emphasis on applying nonlinear methods to real-world datasets from ecological momentary assessments and wearable sensors. Key research interests include: dynamical systems modeling, emotion regulation mechanisms, intensive longitudinal data methods, and bridging computational theory with applied behavioral science. She has contributed novel frameworks for subgrouping heterogeneous time series and handling missingness in multilevel studies. Her methodological innovations have been applied to diverse topics such as adolescent social media use, maternal-infant interaction dynamics, and obesity intervention design. Current projects include advancing adaptive control systems for health applications and developing open-source tools for spatial data analysis from GPS tracking. Dr. Chow's work is supported by NIH grants and institutional funding through Penn State's Social Science Research Institute. She actively collaborates on large-scale initiatives like the Inner Lives of Healthy Babies Network (ILHBN), addressing challenges in harmonizing heterogeneous developmental datasets.

• Geophysics
• Seismology
• Volcano Monitoring
• +5 more

Dr. Ivan Lokmer is an Associate Professor in Petroleum Geoscience at the School of Earth Sciences, University College Dublin. His research focuses on geophysical inversion techniques, volcano seismology, and seismic wave propagation in complex media. He holds a PhD from UCD and has expertise in numerical modeling, machine learning applications, and subduction zone dynamics. Key research areas include stress field analysis along the Hikurangi Margin, diffraction imaging using deep learning, and long-period volcanic seismic event mechanisms. He has coordinated modules such as 'Applied Geophysics' and 'Geocomputation' at UCD since 2019. Education: BSc in Physics (University of Zagreb, 1997), MSc in Geophysics (University of Zagreb, 2002), PhD in Volcano Seismology (UCD, 2008). Research highlights include studies on seismic source inversion, borehole stress orientation variability, and volcanic tremor analysis. His work integrates field observations with computational methods to advance understanding of tectonic and volcanic processes. Notable contributions include the FAME project using fiber-optic sensing for volcano monitoring and publications on subduction zone stress patterns. Teaching responsibilities include courses on geophysical methods and geocomputational tools. Ongoing projects focus on machine learning in seismic imaging and geohazard analysis.

• Operations Research
• Optimization Algorithms
• Combinatorial Optimization
• +3 more

Cesar Rego is a Full Professor of Operations Management and Business Analytics at the University of Mississippi's School of Business Administration, Department of Marketing, Analytics and Professional Sales. He holds tenured positions at multiple institutions, including visiting roles at MIT. His academic journey includes a B.Sc. in Computer Science and Applied Mathematics from Universidade Portucalense (1990), an M.Sc. in Operations Research from the University of Lisbon (1993), a Ph.D. in Computer Science from the University of Versailles (1996), and a Habilitation (post-doctorate) from the same university (2012). Rego specializes in optimization algorithms, heuristics, and metaheuristics, with a focus on combinatorial optimization, parallel computing, and operations research applications. His research addresses problems like the Traveling Salesman Problem, resource scheduling, and clustering. He has contributed to advancements in Tabu Search, Scatter Search, and Ejection Chain methods. Rego has served on NSF and NSERC committees, organized international conference sessions, and delivered invited lectures. His work spans over 50 publications in journals like European Journal of Operational Research and Management Science. Notable areas include algorithm design for large-scale problems and interdisciplinary curriculum development at the operations research-computer science interface. His career includes faculty roles at Portucalense University and the University of Lisbon, alongside his current tenure at the University of Mississippi since 2011. He advises on complex planning procedures and collaborates on projects involving data analytics and optimization frameworks.

• Human-Robot Interaction
• Social Influence
• Trust
• +3 more

Dr. William Volante is a Lecturer in the Department of Psychology at Clemson University's College of Behavioral, Social and Health Sciences. He holds a Ph.D. in Human Factors and Cognitive Psychology from the University of Central Florida. His research explores critical areas of human-technology interaction, including Human-Robot Interaction, Social Influence, Trust in Automation, Usability, and Gamification. Dr. Volante teaches courses such as Advanced Experimental Psychology, Cognitive Psychology, Drugs and Human Behavior, and Team-Based Research seminars focused on Trust in Technology and UX/Game Design. His research emphasizes understanding how humans interact with technology in complex environments, particularly examining trust dynamics in automation and the psychological factors influencing technology adoption. Recent work investigates cybersecurity challenges like phishing susceptibility and the impact of automated filters on user behavior. Dr. Volante actively contributes to the field through peer-reviewed publications in journals including Ergonomics , Human Factors , and PLOS ONE . His collaborations extend to interdisciplinary projects such as semi-automated meteorite recovery systems.

Tiffany SchrieverView profile

Associate Professor

• Community and ecosystem ecology
• Freshwater ecology
• Herpetology
• +4 more

Dr. Tiffany Schriever is an Associate Professor jointly appointed in the Department of Biological Sciences and the School of Environmental, Geography, and Sustainability at Western Michigan University. Her research focuses on community and ecosystem ecology in freshwater habitats, emphasizing how environmental variability influences ecological dynamics across scales. Key areas include hydrology's impact on communities, stable isotope-based trophic studies, and biodiversity patterns in temporary water bodies. Education : Ph.D., Ecology and Evolutionary Biology, University of Toronto (2010) Postdoctoral Research, Oregon State University (2010-2012) M.S., Biology, Southeastern Louisiana University (2005) B.S., Biology, Winona State University (2003) Research Interests : Dr. Schriever investigates freshwater ecosystems, particularly wetlands and streams, exploring topics such as hydrologic variability effects, food web structures using stable isotopes, and functional traits influencing biodiversity. Her lab employs experimental and comparative field methods, with recent focus on Great Lakes interdunal wetlands and montane desert streams. Awards & Grants : While specific awards are not listed, her active research program suggests sustained grant support from environmental agencies or foundations, given the complexity of her fieldwork and isotopic analyses. Lab & Advising : Her research group includes PhD students Adam Austin and Sara Diller, and M.S. student Jennifer Shamel. The Schriever Lab maintains an active webpage and collaborates widely, as evidenced by publications in journals like Ecosphere and Ecology. Labs/Teams : Primary affiliation with the Schriever Lab at Western Michigan University, focusing on freshwater ecology and environmental dynamics. Collaborations likely exist with regional conservation agencies and universities.

• Spacecraft Design
• Aerospace Engineering
• Astrodynamics
• +4 more

Dr. Vittorio FRANZESE is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg's SPASYS department. His work focuses on CubeSat technology, autonomous space systems, and deep-space exploration. He leads projects like the POQUITO PocketQube mission and the LUMIO lunar CubeSat, aiming to advance miniaturized satellite capabilities for interplanetary navigation and meteoroid impact monitoring. Key research areas include spacecraft autonomy, optical navigation algorithms, and mission design for CubeSats. He has contributed to initiatives such as the ERC-funded EXTREMA project, developing self-driving interplanetary CubeSats. His technical expertise spans satellite systems engineering, trajectory optimization, and sensor development for space applications. Publications highlight advancements in laser communication terminals, asteroid mission analysis, and swarm satellite technologies. Collaborative efforts include the Hera Milani CubeSat mission for asteroid exploration. His work bridges theoretical research with practical implementation, emphasizing innovation in low-cost space technologies.

Alan ZucconiView profile

Senior Lecturer

• Artificial Intelligence
• Game Development
• Shader Programming
• +3 more

Alan Zucconi is a Senior Lecturer in Artificial Intelligence and Science Communicator at Goldsmiths, University of London. He leads the MA Computer Games: Art & Design and MSc Computer Games Programming courses. His work spans game development, shader programming, and STEM advocacy. He has authored influential books like Unity 2018 Shaders and Effects Cookbook and publishes extensively on topics like AI, game mechanics, and mathematics. Recognized in Develop’s 30 Under 30, Zucconi is also a Video Game STEM Ambassador, focusing on inclusivity in the gaming industry. Education: MRes in Advanced Computing (Imperial College London, 2012), BSc in Computer Science (University of Pisa, 2011). Research & Teaching : Specializes in AI applications in games, procedural content generation, and educational technology. Courses include Game AI Programming and Advanced Programming for Games. His tutorials and documentaries (e.g., The Fourth Dimension Is Real ) bridge complex concepts with practical implementations. Publications & Media : Over 20 books and articles, including work on Kalman filters, 4D geometry, and Minecraft world generation. Media engagements include BBC and documentary contributions. His blog and Patreon offer free educational resources for developers worldwide.