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Yevhen SuprunenkoView profile

Researcher

• Epidemiology
• Mathematical Modeling
• Spatial Dynamics
• +3 more

Dr. Yevhen Suprunenko is a Visiting Researcher in the Department of Plant Sciences at the University of Cambridge, actively contributing to the Epidemiology and Modelling research group. His work bridges theoretical physics and plant pathology to address critical challenges in agricultural sustainability and global food security through advanced spatial modeling of disease dynamics. He holds a PhD in Theoretical Physics (Condensed Matter) from Lancaster University, UK, which provides the mathematical foundation for his interdisciplinary research in plant disease epidemiology. This unique background enables innovative approaches to complex biological systems. Suprunenko's research centers on mathematical modeling of spatial epidemic spread in agricultural systems, focusing on intrinsic scales of epidemics, cropping patterns, and host landscape structure. He investigates how spatially explicit dynamics, stochasticity, and time-variability influence pest/pathogen distribution, epidemic severity, and optimal control strategies for threats like oak processionary moth and cassava brown streak disease. His work integrates computational methods with field data to develop practical solutions for crop protection. Analysis of his publication trajectory reveals a distinct evolution from chronotaxic systems in physics (2012-2017) to advanced spatial epidemiology in plant sciences (2019-2025). Recent work demonstrates increasing sophistication in modeling landscape-pathogen interactions, with strong emphasis on analytical approximations for invasion thresholds, individual-based model frameworks, and real-world applications in crop disease management. Key thematic areas include spatial scaling effects, infection rate optimization, and data refinement techniques for improved predictive accuracy. No scientific awards were explicitly documented in the provided materials. While specific student supervision details are absent from available records, Suprunenko's collaborative publications indicate active mentorship within the Epidemiology and Modelling group. Grant funding specifics are not disclosed, though his research aligns with major initiatives in agricultural security and environmental sustainability at Cambridge. As a core member of the Epidemiology and Modelling research group, Suprunenko collaborates on projects addressing plant-pathogen interactions within the Department of Plant Sciences. His work interfaces with Cambridge's broader environmental research ecosystem including the Centre for Global Wood Security and Global Food Security IRC, contributing to interdisciplinary efforts in ecosystem conservation and agricultural resilience.

• computational neuroscience
• theoretical neuroscience
• sensory systems
• +3 more

Wiktor Młynarski is a Professor and Research Group Leader at the Faculty of Biology, Ludwig-Maximilians-University Munich, where he directs computational neuroscience research focused on adaptive neural computations in sensory systems. His work bridges theoretical frameworks with experimental validation to uncover fundamental principles of biological information processing. His research centers on computational and theoretical neuroscience, leveraging information theory, statistics, and probabilistic machine learning to model how neural systems efficiently represent dynamic natural environments. Key interests include sensory coding adaptation across timescales, statistical structure of natural stimuli, and the development of normative frameworks applicable from synaptic to behavioral levels. This inherently collaborative approach integrates theoretical predictions with experimental neuroscience to identify universal processing rules. Analysis of Młynarski's publication trajectory (2014-2025) reveals consistent exploration of efficient coding principles across auditory and visual domains, with recent work emphasizing anticipatory processing during locomotion, time-constrained decision-making, and panoramic visual statistics. His research demonstrates how environmental dynamics shape neural representations, moving beyond static models to capture the brain's adaptive capabilities in real-world contexts. Professor Młynarski leads the Computational Neurobiology Research Group (https://compneurobio.org), fostering interdisciplinary collaborations to confront theoretical models with experimental data. The group's work aims to establish general rules for biological information processing by examining how sensory systems dynamically optimize computations in response to environmental regularities and changes.

Lauren E. GillespieView profile

Assistant Professor

• Machine Learning
• Global Ecology
• Genomics
• +5 more

Dr. Lauren E. Gillespie is an Assistant Professor in the Department of Geospatial Data Sciences at the University of Michigan, specializing in AI-integrated approaches for large-scale ecosystem monitoring. With a background in computer science and biology, her research focuses on developing foundation models to analyze noisy environmental data from remote sensing and citizen science platforms, aiming to enhance ecological forecasting under rapid climate change. PhD : Computer Science, Stanford University BS : Computer Science & Chemistry, Southwestern University Her work bridges machine learning , global ecology , and remote sensing , with recent publications on biodiversity mapping using deep learning, domain adaptation in citizen science datasets, and genetic diversity loss in the Anthropocene. She actively explores ethical frameworks for scalable environmental AI applications. Key scientific awards include the Best Paper Award at AAAI 2025, Fulbright Program support (2024), and NSF Graduate Research Fellowship (2019). Her projects have received grants such as the Climate Change AI Innovation Grant for ForestBench (2022) and the Ethics, Society and Technology Hub grant for Scenes from the Anthropocene (2022).

• Web Security
• Identity Management
• System Security
• +3 more

Dr. Wanpeng Li is a Lecturer in Cyber Security within the Department of Computer Science at the University of Liverpool. Prior to this role, he held lecturer positions at the University of Aberdeen and Manchester Metropolitan University, and worked as a postdoctoral researcher at City, University of London. His research focuses on critical areas in cyber security including web security, identity management, authentication mechanisms, and malware detection using machine learning. Research Trends: His recent publications span both cyber security and mathematical modeling domains. Key security themes include automated vulnerability detection, federated learning attacks, and privacy-preserving protocols for vehicular networks and IIoT systems. Parallel studies in grey system models explore energy consumption forecasting and environmental impact analysis using fractional calculus and neural network integrations. Advising: Dr. Li actively accepts PhD students in cyber security-related fields.

William PetermanView profile

Associate Professor

• Landscape Ecology
• Conservation Biology
• Population Genetics
• +3 more

William Peterman is an Associate Professor in Wildlife Ecology and Management at The Ohio State University. His research integrates field observation, molecular lab work, and quantitative modeling to study biodiversity responses to climate change, habitat alteration, and urbanization. He focuses on animal population connectivity, habitat restoration, and conservation strategies across spatial-temporal scales. Landscape ecology and conservation biology Population genetics and metapopulation dynamics Climate change impact on amphibians and reptiles Recent publications highlight advancements in landscape resistance modeling, hybridization effects on conservation, and climate-agroecosystem interactions. His lab emphasizes interdisciplinary methods including biophysical models and camera trap technology for biodiversity monitoring. Current students in his lab include Grant Ravary, Olivia Ruppert, Marissa Roseman, Aidan McCarthy, Jess Dong, Ryan Wagner, and Allison Williams. He has developed specialized software (ResistanceGA) and teaches courses like ENR 5370: Management of Wildlife Habitat .

Maria BrbicView profile

Assistant Professor

• Machine Learning
• Computational Biology
• Biomedical Informatics
• +3 more

Maria Brbic is an Assistant Professor of Computer Science at EPFL, previously a postdoctoral researcher at Stanford University under Jure Leskovec. Her research focuses on developing machine learning methods for biological and biomedical applications, particularly representation learning of high-dimensional datasets, open-world semi-supervised learning, and single-cell genomics. Her work includes the STELLAR method for spatial cell type discovery (Nature Methods 2022), the ORCA framework for open-world learning (ICLR 2022), and contributions to the Fly Cell Atlas (Science 2022). She is involved in the Chan Zuckerberg Biohub and Neuro-omics projects. She received the University of Zagreb's best thesis award, was recognized as a MIT Rising Star in EECS, and won the Basel Computational Biology Conference best poster award. Her research bridges computer science with cutting-edge biomedical discovery.

• Robotics
• Evolutionary Robotics
• Artificial Evolution
• +6 more

Leni Le Goff is a Lecturer at the School of Computing, Engineering and the Built Environment , Edinburgh Napier University. Her research bridges robotics , evolutionary computation , and environmental sustainability . Key research interests include: Evolutionary design of robot morphologies and controllers Integration of individual and cultural learning in artificial evolution Application of autonomous systems for terrestrial biodiversity monitoring Optimization frameworks for robotic policy search Manufacturability constraints in morpho-evolution Transdisciplinary collaboration between ecologists and roboticists Recent publications highlight her work on: Developing generalized early stopping criteria for policy search Mapping fitness landscapes in morpho-evolution Assessing robotic solutions for ecological surveying Overcoming hierarchical optimization challenges in coevolution Creating biodegradable and deployable robotic systems Evaluating manufacturability trade-offs in evolved robot designs Active in the Autonomous Robot Evolution (ARE) project, she collaborates with leading researchers like Prof Emma Hart and Prof Karen Diele. Her work receives funding from EPSRC and the Carnegie Trust , focusing on real-world deployment challenges and computational efficiency improvements.

Marcos Gridi-PappView profile

Professor

• Acoustic Communication
• Animal Behavior
• Evolutionary Biology
• +6 more

Marcos Gridi-Papp is a Professor in the Department of Biological Sciences at University of the Pacific, specializing in the study of acoustic communication systems in animals. His research investigates the interplay between hearing, vocal anatomy, and communication behavior, with a focus on frogs and crickets. He also teaches courses related to biological sciences and advises biology and pre-dental majors. PhD in Integrative Biology, University of Texas, Austin (2003) MS in Ecology, State University of Campinas, Brazil (1997) BS in Biological Sciences, State University of Campinas, Brazil (1994) Gridi-Papp's research explores how anatomical structures influence vocal performance and auditory sensitivity. His lab investigates: Laryngeal morphology and vocal control in túngara frogs Auditory tuning mechanisms and ultrasound sensitivity Environmental impacts on communication strategies Physiological and behavioral adaptations in vocal systems Signal complexity evolution and middle ear mechanics Eustachian tube control and acoustic reflexes Recent research trends focus on: Bioacoustic adaptations in amphibians Behavioral responses to environmental changes Anatomical constraints on vocalization Acoustic signal optimization Frequency modulation mechanisms Multi-component call structures His lab offers research opportunities in anatomy, electrophysiology, animal behavior, and computational methods, supporting students with credit hours and technical training.

Tanja KaiserView profile

Researcher

• Multi-Robot Systems
• Evolutionary Robotics
• Autonomous Intelligent Mobile Robot Systems
• +4 more

Tanja Kaiser is a Senior Researcher in the Department of Computer Science & Artificial Intelligence at the University of Technology Nuremberg, Germany. She leads a junior research group and serves as an Ada Lovelace Distinguished Research Fellow at ScaDS.AI Dresden/Leipzig and Technische Universität Dresden. Her work spans evolutionary robotics, swarm intelligence, and collective behavior in autonomous systems. Dr.-Ing., Computer Science, University of Lübeck (2022) M.Sc., Computer Science, Technical University of Berlin (2017) B.Sc., Computer Science, DHBW Stuttgart (2014) Kaiser focuses on multi-robot systems and surprise minimization in swarm robotics. Her research explores evolutionary algorithms, self-organization, and autonomous decision-making, with applications in UAV tracking and onboard manipulation behaviors. Recent publications emphasize dynamic collective behaviors and task-independent behavior characterization. Kaiser’s scientific contributions include awards like the Bernd Fischer Prize (2023). She actively contributes to academic equity as a representative for the equity of women in sciences and arts at the University of Technology Nuremberg.

• Female Entrepreneurship
• Real Estate Management
• Service Management
• +2 more

Michela Mari is an Associate Professor of Economics and Business Management at the Department of Management and Law, Faculty of Economics, University of Rome Tor Vergata. She serves as Deputy Coordinator of the Master's Degree in Real Estate Economics and Management and the Departmental Research Center "Scientific Observatory on Female Entrepreneurship - OSIF," and is a Faculty Member of the PhD in Management. Since 2018, she has chaired the "Female Entrepreneurship" Track at the European Academy of Management Conference (EURAM) and has been an active member of the Global WEP Network since 2017. Her research centers on Female Entrepreneurship , Real Estate Management , and Service Management , with particular focus on work-family conflict dynamics, virtual retail environments, and public-private partnerships. Her interdisciplinary approach bridges business strategy with gender studies and urban development, resulting in publications in leading journals such as International Entrepreneurship and Management Journal , Cities , and The Service Industries Journal . She has pioneered research on Italian female entrepreneurs' experiences and global STEM entrepreneurship barriers. Analysis of her publication trends reveals strong thematic continuity in gender-focused business research since 2011, with increasing emphasis on sustainability and digital transformation in recent years. Her work consistently addresses practical implications for policy and management while maintaining rigorous academic standards. Mari's scientific recognition includes: borsa di studio per giovani ricercatori, XXXIII Convegno Nazionale AIDEA 2010 for corporate governance research As PhD faculty and OSIF Research Center Deputy Coordinator, she actively mentors emerging scholars in female entrepreneurship research while collaborating with international networks like Global WEP to shape policy frameworks. Her editorial leadership in special journal issues demonstrates scholarly influence beyond traditional publication metrics. She directs the Departmental Research Center "Scientific Observatory on Female Entrepreneurship - OSIF," which conducts empirical studies on gendered business practices and advises policymakers on women's economic empowerment initiatives through evidence-based research.

Joy O'KeefeView profile

Associate Professor

• Bat Ecology
• Wildlife Conservation
• Human-Wildlife Interactions
• +4 more

Joy O'Keefe is an Associate Professor at the University of Illinois Urbana-Champaign within the School of Integrative Biology and Department of Natural Resources and Environmental Sciences. She leads the Human-Wildlife Interactions Lab and holds additional affiliations with the Prairie Research Institute. Primary Affiliation: School of Integrative Biology Department: Natural Resources and Environmental Sciences Institute: Prairie Research Institute Dr. O'Keefe's research focuses on understanding bat ecology in human-altered landscapes, particularly examining: Roosting and foraging behaviors Mitigation strategies for bat conservation Thermal ecology of artificial roosts Wildlife trade impacts and solutions Acoustic monitoring techniques Effects of climate and disease on bat populations Her recent work addresses critical conservation challenges such as: Ending online ornamental bat trade Optimizing bat box thermal conditions Assessing white-nose syndrome impacts Improving habitat suitability modeling Dr. O'Keefe collaborates extensively with: USDA Forest Service National Park Service State wildlife agencies Private landowners

Andrea FrommelView profile

Assistant Professor

• Sustainable Aquaculture
• Climate Change
• Fish Physiology
• +5 more

Andrea Frommel is an Assistant Professor in Applied Biology and Chair in Sustainable Aquaculture at the University of British Columbia's Faculty of Land and Food Systems. She leads research at the intersection of climate change, fisheries science, and sustainable aquaculture practices, with particular emphasis on early life stages of commercial fish species. Her educational background includes a BSc from the University of California at Santa Cruz, an MSc from the University of Southern Denmark, and a PhD from the Hemholtz Center for Ocean Research in Kiel, Germany. This international training has informed her interdisciplinary approach to aquatic research. Dr. Frommel's research focuses on three interconnected areas: the effects of climate change (particularly ocean acidification and warming) on commercial fish species; the development of alternative sustainable feeds for aquaculture; and optimizing fish welfare practices in aquaculture systems. Her work examines species-specific and life-stage-specific responses to environmental stressors, with implications for both wild fisheries management and aquaculture production. Her recent publications reveal a strong emphasis on understanding how combined climate change stressors affect fish physiology during critical life stages, particularly during the transition from freshwater to seawater in salmonids. She has made significant contributions to understanding how fish species vary in their resilience to ocean acidification, with important implications for stock assessment models and aquaculture production management. Dr. Frommel actively collaborates with the Hakai Institute, Department of Fisheries and Oceans, local NGOs, government agencies, industry partners, and international research institutions. She welcomes graduate students interested in projects related to sustainable aquaculture, climate change impacts on fisheries, and fish physiology under changing environmental conditions. She directs the Aquaculture and Climate Change Lab, which investigates how environmental stressors affect commercial fish populations and develops mitigation strategies to enhance the sustainability of aquaculture operations. Current projects include examining how kelp can mitigate ocean acidification effects, researching alternative feed ingredients, and studying local variability in coastal systems that may provide resilience to climate change.

Jeffery D. WeirView profile

Adjunct Professor

• Operations Research
• Decision Analysis
• Risk Analysis
• +6 more

Dr. Jeffery D. Weir is an Adjunct Professor in the Department of Operational Sciences at the Air Force Institute of Technology (AFIT). A former U.S. Air Force officer, he specializes in decision analysis, risk analysis, and multi-objective optimization, with applications spanning military logistics, energy systems, and transportation modeling. His research addresses complex operational challenges such as aircraft scheduling, RNA foldability prediction, and cost analysis for military installations. Doctor of Philosophy (Ph.D.), Industrial Engineering & Operations Research, Georgia Institute of Technology, 2002 Master of Science (M.S.), Operations Research, Air Force Institute of Technology, 1995 Bachelor of Science in Electrical Engineering (B.S.E.E.), Georgia Institute of Technology, 1988 Dr. Weir's research bridges theoretical and applied domains, focusing on metaheuristics, data envelopment analysis, and robust optimization. His recent work includes RNA structure prediction frameworks, multi-modal distribution networks, and energy model recommendation systems. His publications span journals like BMC Bioinformatics , European Journal of Operations Research , and IEEE Transactions on Evolutionary Computation , reflecting interdisciplinary expertise in computational biology, military logistics, and building energy systems. Scientific awards include the Toulmin Medal for best article in 2004. He has received grants from the Defense Intelligence Agency, United States Transportation Command, Air Force Materiel Command, and other military organizations. Dr. Weir is a member of the Institute for Operations Research and the Management Sciences (INFORMS), Military Operations Research Society, and Institute of Industrial Engineers. His work emphasizes practical decision support tools for military personnel and resource management.

• Fuzzy Logic Systems
• Artificial Intelligence
• Model-Based Predictive Control
• +6 more

Professor Mahdi Mahfouf holds the Chair in Intelligent Systems at the University of Sheffield's School of Electrical and Electronic Engineering . He obtained his MPhil (1988) and PhD (1991) in Control Systems from the same institution. After postdoctoral research (1992-1996) on Leverhulme-funded projects in Model-Predictive Control and Fuzzy Logic, he progressed through academic ranks at Sheffield to Full Professor (2005). Recipient of the IEE Hartree Premium Award (1992) and MEDIPEX Innovation Award (for ICU Decision Support Systems) Over 370 publications, including 130+ journal papers Head of the Intelligent Systems Research Laboratory Research Themes His work spans fundamental research in Fuzzy Logic (modelling, control), Neural-Fuzzy Systems, Self-Organising Control, and Evolutionary Optimization, alongside applied domains in pharmaceutical manufacturing, aerospace systems, biomedical engineering (ICU monitoring), and intelligent transportation. Recent publications focus on hybrid AI for pharmaceutical processes , type-2 fuzzy control systems , and machine learning in manufacturing metrology . Lab initiatives include multistage process monitoring and human-machine interaction systems for stress management.

Robin PurshouseView profile

Professor

• Computational Modelling of Complex Social Systems
• Agent-Based Modelling
• Machine Learning
• +6 more

Professor Robin Purshouse is a leading academic at the University of Sheffield , currently serving as Professor of Decision Sciences in the Department of Automatic Control and Systems Engineering within the School of Electrical and Electronic Engineering . With a career spanning academia and industry, his work bridges computational modelling , optimization , and systems science to address complex challenges in public health and engineering. His research has been pivotal in developing mechanisms for agent-based modelling and evolutionary multi-objective optimization . Education: PhD in Control Systems (2004), MEng in Control Systems Engineering (1999) from the University of Sheffield Professor Purshouse's research focuses on computational modelling of complex social systems , decision analytics for population health policy , and Bayesian optimization . He has pioneered the integration of machine learning and uncertainty quantification in social science simulations, with notable projects like the Sheffield Alcohol Policy Model and CASCADE initiative. His work spans interdisciplinary domains, including health economics , policy evaluation , and engineering design . Recent publications highlight his expertise in agent-based modelling for smoking/vaping dynamics , intersectional disparities in alcohol consumption , and inclusive economy frameworks . He has secured substantial funding (exceeding £16 million) through grants from NIH , CRUK , UKPRP , and MRC , including his role as co-PI in the HealthMod cluster. His contributions to multi-objective optimization and evolutionary algorithms have advanced methodologies in both engineering and public health domains. Scientific Awards: ESRC Future Research Leaders Award (2012-2015) As a co-developer of the Liger optimization environment , Purshouse has fostered open-source tools for complex decision-making. He leads the SIPHER consortium for systems science in public health and serves on editorial boards for journals like Environmental Modelling & Software . His teaching includes Agent-Based Modelling (ACS6132), and he maintains professional memberships in the Association for Computing Machinery and Research Society on Alcohol .