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Mathew Arun ThomasView profile

Assistant Professor

• Beyond Standard Model Particle Physics
• Extra Dimensions
• Baryon Number Violation
• +3 more

Dr. Mathew Arun Thomas is an Assistant Professor at the Indian Institute of Science Education and Research Thiruvananthapuram (IISER-TVM), specializing in Theoretical Particle Physics. His research focuses on phenomena beyond the Standard Model, including Baryon Number Violation, Extra Dimensions, Effective Field Theory, and Flavour Physics. Education: BSc (Hons) from St. Stephen's College, University of Delhi; MSc and PhD in Physics and Astrophysics from the University of Delhi (supervised by Prof. Debajyoti Choudhury). Postdoctoral work at the Indian Institute of Science (supervised by Prof. Sudhir K Vempati). His recent work explores Dark Matter-assisted Baryon Number Violation processes, such as Hydrogen-antihydrogen oscillation and Proton decay suppression, using six-dimensional orbifolded torus models. He also investigates constraints on Randall-Sundrum models from charge lepton flavour violations and phenomenology of low-energy Flavour Physics. The 15 most recent publications span neutrino oscillations, dark matter phenomenology, warped geometry models, and collider signatures, reflecting his expertise in connecting high-energy theory with experimental observables. Scientific Awards: INSPIRE Faculty Fellowship. He has mentored students like Akshay Anilkumar and Krishnanand N, contributing to projects on Flavour Violations and Cosmological Bounce models. He teaches courses including Quantum Field Theory and Scientific Computation, with a 2023 Mechanics course for 330 students.

• Geotechnical Engineering
• Disaster Response and Mitigation
• Digital Data Collection Systems
• +4 more

Dr. J. David Frost is the Elizabeth and Bill Higginbotham Professor of Civil Engineering at Georgia Institute of Technology and a Regents' Entrepreneur. He has held academic positions at Purdue University and Georgia Tech, with a focus on geotechnical engineering and disaster response. As founding director of Georgia Tech's Savannah campus and head of the Geosystems Engineering Group, Frost has shaped academic programs and research initiatives. Education: B.A.I and B.A. in Civil Engineering and Mathematics, Trinity College, Dublin (1980) M.S. and Ph.D. in Civil Engineering, Purdue University (1986, 1989) Research Interests span geotechnical engineering, bio-inspired design, and disaster resilience. His work emphasizes digital data collection systems for subsurface hazard assessment, soil-polymeric material interactions, and geotechnical responses to earthquakes, hurricanes, and anthropogenic disasters. Recent projects integrate ant nest geometry, plant root mechanics, and geosynthetic innovations into infrastructure solutions. Scientific Contributions include two U.S. patents for subsurface data systems, leadership in NSF-funded post-disaster reconnaissance missions (e.g., 9/11, Türkiye earthquakes), and co-founding the Geotechnical Extreme Events Reconnaissance (GEER) Association. His articles reflect expertise in bio-inspired geotechnics, machine learning for disaster modeling, and advanced computational simulations. Awards & Recognition: ASCE Huber Civil Engineering Research Prize NSF National Young Investigator Award Georgia Society of Professional Engineers Engineer of the Year in Education Coastal Business & Education Technology Alliance Leadership Innovation Award Professional Engagement includes chairing the Savannah Area GIS board, advising on ASCE Geo-Legislative Committees, and founding a software company serving 350+ global clients. His work bridges academia, policy, and industry innovation.

Michael T. MonaghanView profile

Professor

• Freshwater Molecular Ecology
• Evolution
• Metabarcoding
• +12 more

Michael T. Monaghan is a Professor at the Faculty of Biology, Chemistry and Pharmacy, Freie Universität Berlin, and leads the Research Group in Molecular Ecology and Genomics at the Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB). His work bridges evolutionary biology, molecular ecology, and environmental monitoring, focusing on freshwater systems and urban aquatic habitats. Education: B.S. (The Ohio State University, 1995), M.S. (Idaho State University, 1998), Dr. sc. nat. (ETH Zürich, 2002) Key Positions: Senior Scientist/Research Group Leader at IGB (2008–present), Visiting Professor at Duke-NUS Medical School (2016), Guest Professor at Ehime University (2015–2016) Dr. Monaghan's research explores freshwater biodiversity dynamics using molecular tools like metabarcoding and phylogenomics. His team investigates how environmental changes—climate warming, urbanization, pollution—affect microbial and insect communities, with a focus on eDNA applications and ecohydrology. His publications (2022–2025) span topics such as climate-driven plankton shifts, urban habitat adaptation by bees, toxin genetics in algae, and metagenomic monitoring of aquatic systems. Collaborative projects like BiNatUr and ODER~SO emphasize urban resilience and disaster ecology. Teaching includes data science in biology, evolutionary ecology, and environmental genomics at Freie Universität Berlin and the Institute of Computer Science. He mentors doctoral and master’s students in molecular ecology and trains interns in biodiversity genomics. Lab Members: Dr. Dagmar Frisch (Scientific Staff) Dr. Katrin Kiemel (Postdoc) Elisabeth Funke (Research Technician) Doctoral Candidates: Onur Erk Kavlak, Athena Karapli-Petritsopoulou, Daniel Wewer

Juan Pablo LopezView profile

Assistant Professor

• Neurosciences
• Psychiatry
• Molecular mechanisms of psychiatric disorders
• +4 more

Dr. Juan Pablo Lopez is an Assistant Professor at the Department of Neuroscience, Karolinska Institutet (Sweden) , leading research on stress-related psychiatric disorders. He earned undergraduate degrees in Psychology and Biology (Florida International University), a PhD in Psychiatry (McGill University), and postdoctoral training at the Max Planck Institute of Psychiatry in Munich. His work combines single-cell transcriptomics behavioral mouse models automated behavioral tracking viral-mediated gene manipulations to study stress susceptibility, resilience, and antidepressant mechanisms. Research interests include: Neurobiology of stress and trauma Molecular mechanisms in psychiatric disorders Developmental neuroendocrinology Sex differences in stress response Neural circuits of depression His recent work analyzes how stress exposure during development influences lifelong mental health and treatment outcomes. Scientific accolades include 2023 ECNP Rising Star Award ERC Starting Grant (2023) Swedish Research Council Starting Grant (VR, MH-12) StratNeuro Startup Funding He leads the Lopez Lab, which collaborates with international groups through the NeSTED network (Neuropharmacology and Stress/Trauma Exposure during Development).

• Control Theory
• Distributed Control
• Networked Systems
• +12 more

Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University, Sweden. She joined the department in January 2021 and holds a prestigious WASP (Wallenberg AI, Autonomous Systems and Software Program) professorship. Her research focuses on the analysis and control of large-scale networked systems, with applications in distributed electric power networks and socio-epidemiological networks. She is actively involved in multiple research projects, supervises several PhD students, and contributes to major academic events in control theory. Education: Ph.D. in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013) B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2011) Emma Tegling's research centers on the fundamental limitations of distributed control, particularly in large-scale and non-normal network systems. Her work addresses critical challenges in vehicular formations, power grids, and social networks. She develops scalable control designs, consensus protocols, and optimal control strategies for complex networked environments. Her recent publications highlight breakthroughs in string stability, transient performance, and distributed optimization. The trend in her articles shows a strong focus on mathematical control theory, network dynamics, and real-world applications in socio-technical systems. Scientific Awards: WASP professorship (Wallenberg AI, Autonomous Systems and Software Program) Emma Tegling leads and co-leads several significant research grants, including WASP NEST: Learning in Networks and Dynamics of Complex Socio-Technological Network Systems. She actively supervises PhD students such as Jonas Hansson and David Ohlin, whose work has led to novel consensus protocols and optimal control formulations. Her academic leadership extends to organizing the European Control Conference and co-organizing interdisciplinary workshops on power and democracy in modern societies. She is also involved in public engagement and academic service through supervision and project coordination. Emma Tegling is a key member of the Department of Automatic Control at Lund University, contributing to research teams focused on networked systems, control theory, and AI integration. She collaborates extensively within ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and participates in cross-disciplinary labs working on AI, digitalization, and natural/artificial cognition. Her work is aligned with UN Sustainable Development Goals related to sustainable energy and resilient infrastructure.

• Primatology
• Animal Behavior
• Evolutionary Anthropology
• +3 more

Ian Gilby is an Associate Professor at the School of Human Evolution and Social Change, Arizona State University. His research focuses on the social behavior, ecology, and cognition of wild chimpanzees, particularly within the context of long-term studies at Gombe National Park, Tanzania. Gilby investigates topics such as cooperative hunting, dominance hierarchies, social bonding, and the influence of ecological factors on primate behavior. His work bridges primatology, evolutionary biology, and conservation science, with a strong emphasis on understanding the adaptive strategies of chimpanzees in complex social environments. Key themes in Gilby’s research include the evolution of cooperation, reproductive strategies, and the ecological drivers of social behavior. He has contributed significantly to studies on chimpanzee aggression, hunting tactics, and the role of vocal communication in group coordination. His findings highlight the intricate relationship between social structure, ecological conditions, and individual success in primate communities. Notably, Gilby is involved in the Gombe Chimpanzee Project, analyzing long-term datasets to address questions about data sharing in conservation science and the impacts of environmental changes on wildlife. While no formal awards or grants are explicitly mentioned in the provided texts, his extensive publication record underscores his expertise in primate behavior and ecology.

Alain PIROTTEView profile

Professor

• Econometrics
• Panel Data Econometrics
• Spatial Econometrics
• +4 more

Alain PIROTTE is a Professor of Economic Sciences at University Paris-Panthéon-Assas, affiliated with the Center for Research in Economics and Law (CRED). His research and teaching focus on econometrics, particularly panel data and spatial econometrics, with applications in labor, transportation, and urban economics. His research interests include: Panel data econometrics and forecasting Spatial econometrics and spatial dependence modeling Transportation and urban economics Labor market dynamics Environmental and agricultural econometrics The recent articles highlight a strong focus on spatial panel data models, prediction techniques, and applications to real-world economic issues such as housing prices, traffic demand, and urban sprawl. His work frequently employs advanced econometric methods, including hierarchical Bayesian models and instrumental variable approaches, often in collaboration with leading scholars like B.H. Baltagi. He has held significant academic responsibilities, including: Head of Master 1 in Managerial and Industrial Economics Member of the Scientific Council at Panthéon-Assas University Member of Doctoral Schools at both Panthéon-Assas and University of Paris-Est Member of AERES expert evaluation committee He is actively involved in research leadership and academic governance, contributing to the development of econometric theory and its application across economic domains.

• Numerical and analytical modeling of subsurface multi-component, multiphase flows
• Environmental and ecological implications of coastal groundwater flow
• Aquifer parameter estimation
• +3 more

Dr. Li Hailong is a Chair Professor at the School of Environmental Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen. He holds a PhD in Hydrogeology from the University of Hong Kong (2003), an MSc (1991) and BSc (1988) in Applied Mathematics from Fudan University. His academic journey includes professorships at China University of Geosciences-Beijing (2009-2020) and Anshan Normal University (1999-2009). Recipient of 2010 NSFC Outstanding Young Scientist Grant 2022 Dayu Water Conservancy Science and Technology Award 2008 Chutian Professorship (Hubei Province's highest academic honor) Dr. Li's research focuses on multi-component, multi-phase subsurface flows in coastal zones and their ecological/environmental effects. His work spans aquifer parameter estimation, ecohydrology, marine groundwater discharge, and computational fluid dynamics. Recent projects involve submarine groundwater discharge (SGD) quantification in Bohai Sea and Jiaozhou Bay using radium/radon isotopes. His publications in top journals like Nature Geoscience , Geochimica et Cosmochimica Acta , and Water Resources Research have been cited 7,072 times (H-index 49). He has led 19 research projects, including 6 NSFC grants and 973 Program subprojects. Dr. Li serves on editorial boards of Advances in Water Resources and Water Science and Engineering , and was Associate Editor for Hydrogeology Journal (2012-2015).

• Computer Vision
• Deep Learning
• Robotics
• +7 more

Dr. João Henriques is a Research Fellow of the Royal Academy of Engineering (RAEng) at the Visual Geometry Group (VGG), University of Oxford. His research focuses on advancing computer vision, deep learning, and robotics, particularly in areas like 3D scene understanding, reinforcement learning, and multi-agent systems. He is renowned for developing the KCF and SiameseFC visual trackers, which won the VOT Challenge and are deployed in consumer hardware. His work spans 3D geometry, self-supervised learning, causal inference, and neuro-symbolic systems. Key contributions include methods for egocentric video analysis, unsupervised reconstruction, and robot navigation. He leads the VGG's research on neural feature fields, hierarchical scene understanding, and real-time 3D perception. Recent publications emphasize 3D-aware segmentation, universal place recognition, and neuro-symbolic world modeling for robotics. His research often bridges theoretical guarantees with practical applications, such as medical imaging and autonomous systems. Dr. Henriques collaborates with industry and academia on AI ethics, friendly AI, and interpretable learning. His lab hosts DPhil students advancing creative AI applications, such as generative models for gameplay design and LLM evaluations in real-world editorial workflows.

• Hypersonics
• Fluid Dynamics
• Thermodynamics
• +4 more

Ingo Jahn is a Professor at The University of Queensland's School of Engineering. His academic career spans roles including R&D at Rolls-Royce (2007–2012) and academic positions at The University of Queensland (2012–2022). He holds an MEng (Oxford, 2005) and PhD (Oxford, 2011). Education: MEng in Engineering, University of Oxford (2005) PhD in Aerospace Engineering, University of Oxford (2011) Research Interests: Hypersonics: vehicle design, glide trajectory optimization, and aerothermodynamics Fluid Dynamics: computational methods, turbulence, and flow control Control Systems: model predictive control and co-design frameworks Thermodynamics: heat transfer in supercritical CO2 cycles and thermal protection systems His work bridges theoretical and experimental approaches, with a focus on hypersonic vehicle integration and propulsion systems. Publications: Recent articles emphasize hypersonic vehicle co-design, fluid-structure interaction, and experimental methods. Key themes include trajectory optimization, thermal management, and advanced simulation techniques. Grants & Awards: No awards explicitly listed, but extensive industry collaboration (e.g., Rolls-Royce) and leadership in high-impact projects indicate significant recognition. Supervision: Currently supervising 8 doctoral students on topics like hypersonic co-design, unstart prevention in ramjets, and scramjet trajectory optimization. Affiliations: Institute for Advanced Engineering and Space Sciences, AIAA, ASME. Active in conferences like AIAA SciTech and Global Power and Propulsion Society events.

Monowar BhuyanView profile

Associate Professor

• Machine Learning
• Anomaly Detection
• Systems and AI Security
• +6 more

Monowar Bhuyan is an Associate Professor in the Department of Computing Science at Umeå University, Sweden, leading the Cyber Analytics and Learning Group within ADSLab. He holds a Ph.D. in Computer Science from Tezpur University and has held academic positions at Assam Kaziranga University and Umeå University. His research focuses on machine learning, anomaly detection, edge AI, and distributed systems security. He has secured over 35 MSEK in grants from WASP, STINT, and EU Horizon programs. Education Ph.D. in Computer Science and Engineering, Tezpur University (2014) M.Tech. in Information Technology, Tezpur University (2009) B.E. in Computer Science and Engineering, IETE (2007) Research Interests Distributed/Federated/Responsible Machine Learning Cybersecurity and Anomaly Detection in Edge Clouds AI for DDoS Defense and Cyber Resilience Edge AI and Serverless Computing Recent Contributions His recent work addresses secure federated learning, DDoS attack detection in cloud-edge systems, and responsible AI. Key publications include novel frameworks for VSI-DDoS detection and federated learning optimizations. Awards & Grants Best Paper Awards at ICONIP 2023 and ACM ICACCI 2012 WASP NEST Grant (AIR2 Project, 5 MSEK) EU Horizon Europe Grant (SovereignEdge.Cognit, 8.27 MSEK) Lab & Collaborations He leads the Cyber Analytics and Learning Group (ADSlab), collaborating with institutions like KTH, Linköping University, and Nara Institute of Science and Technology (NAIST). The lab focuses on AI-driven security solutions for distributed systems.

Ryan BrowneView profile

Assistant Professor

• Model-based Clustering
• Classification
• Measurement Models
• +4 more

Ryan Browne is an Assistant Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a BMath (2004), MMath (2006), and PhD (2009) from the same institution. His research focuses on model-based clustering , classification , and measurement system quality assessment , with applications in multivariate analysis and statistical inference. He is particularly known for contributions to mixture models and their computational optimization. Education: BMath in Statistics, University of Waterloo (2004) MMath in Statistics, University of Waterloo (2006) PhD in Statistics, University of Waterloo (2009) Ryan’s work emphasizes flexible statistical methodologies , including advancements in skewed distributions, high-dimensional data analysis, and robust algorithms for clustering and classification. He has received the prestigious 2011 W.J. Youden Award from the American Statistical Association for his PhD research on measurement system evaluation. His research trends span computational statistics (e.g., sketching algorithms for big data) and model-based clustering innovations (e.g., mixtures of generalized hyperbolic distributions). Recent work explores parsimonious models, nested Gaussian structures, and efficient parameter estimation for complex datasets. Key Awards: 2011 W.J. Youden Award (American Statistical Association) Ryan collaborates on applied projects, including industrial ecology and sensory data analysis. He has developed R packages like mixture and MixGHD , which implement his methodological contributions.

Catherine MarlerView profile

Professor

• Behavioral Neuroendocrinology
• Animal Behavior
• Social Neuroscience
• +7 more

Catherine Marler is a Professor in the Department of Psychology at the University of Wisconsin-Madison, where she leads the Marler Lab focused on the Biology of Brain and Behavior. Her research program investigates the intricate connections between endocrine systems and social behaviors, with particular emphasis on how hormones like testosterone and oxytocin shape complex social interactions in monogamous mammals. Dr. Marler's research primarily utilizes the California mouse (Peromyscus californicus) as a model organism, capitalizing on its unique monogamous, biparental, and territorial nature. Her work spans both laboratory and field settings, allowing for comprehensive investigation of neuroendocrine mechanisms in naturalistic contexts. Key research themes include the role of testosterone in territorial behavior and winner effects, oxytocin's influence on pair bonding and parental behavior, and the neural substrates of ultrasonic vocalizations. Recent publications reveal a strong focus on conditioned place preferences related to testosterone pulses, oxytocin's effects on social behaviors across different developmental stages, and the neuroendocrine mechanisms underlying aggression and pair bonding. Her work demonstrates how social experience, environmental context, and endocrine systems interact to shape complex behavioral outcomes, with particular attention to sex differences and transgenerational transmission of behaviors. Dr. Marler has published extensively in top journals including Hormones and Behavior, Proceedings of the Royal Society, and Animal Behaviour, with her most recent work appearing in high-impact venues throughout 2023-2025. Her research program represents a sophisticated integration of behavioral observation, endocrine manipulation, and neural analysis to unravel the mechanisms underlying social behavior in mammals. As an advisor, Dr. Marler mentors students in behavioral neuroscience and endocrinology, fostering research that bridges laboratory and field approaches to understand the evolution and mechanisms of social behavior. Her lab maintains a strong commitment to rigorous scientific methodology and innovative experimental design in the study of neuroendocrine-behavior relationships.

Nick HeardView profile

Professor

• Computational Bayesian Inference
• Clustering
• Changepoint Analysis
• +6 more

Nick Heard is a Professor and Chair in Statistics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His research focuses on computational Bayesian inference, clustering, and changepoint analysis applied to dynamic networks (e.g., computer networks, social networks) and bioinformatics. He leads the EPSRC-funded NeST project on Network Stochastic Processes and Time Series, collaborating with universities including Bristol, Oxford, and LSE. His work bridges statistical theory with applied problems in cyber-security and neuroscience. Research Interests - Modelling large dynamic networks - Changepoint analysis and anomaly detection - Statistical methods for cyber-security - Bayesian computation and inference - Spectral clustering and graph embeddings Grants & Collaborations - Co-leads the NeST project on Dynamic graph embeddings: procedures and inference - EPSRC Programme Grant (EP/T004870/1) supporting Network Stochastic Processes and Time Series research Software & Tools - Developed open-source packages for Bayesian changepoint analysis (e.g., changepoints ) - Code for p-value combination methods ( standardised_partial_product )

Anna GautierView profile

Assistant Professor

• Multi-Agent Systems
• Robotics
• Artificial Intelligence
• +3 more

Anna Gautier is an Assistant Professor in the Department of Computer Science at Chalmers University of Technology, affiliated with the Division of Data Science and AI. Previously, she was a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology (2023–2025), focusing on mechanism design for multi-robot systems. Her research emphasizes planning under uncertainty, multi-agent systems, and human-robot interaction. She holds a PhD from the University of Oxford (2023), an MSc from the London School of Economics, and dual undergraduate degrees from Washington University in St. Louis. Education Background: PhD in Computer Science, University of Oxford (2023) MSc in Applied Mathematics, London School of Economics BA in Mathematics and BS in Computer Science, Washington University in St. Louis Research Interests: Dr. Gautier explores planning algorithms for multi-agent systems, particularly in uncertain environments. She designs mechanisms to coordinate robots and humans, leveraging game theory and formal methods. Her work addresses challenges like resource allocation, risk-aware decision-making, and trust in autonomous systems. Recent projects include contingency planning for autonomous vehicles and auction-based resource distribution. Professional Activities: She co-chairs the ECAI 2025 Demonstration Track and teaches the course Safe Robot Planning and Control at KTH. Her projects include collaborations with WASP-Nest (PerCorSo) and TECoSA on trustworthy autonomy. She actively publishes in top venues like AAMAS and AAAI. Labs and Teams: Affiliated with Chalmers' Data Science and AI division, she leads research in multi-agent systems and human-AI collaboration.