John Serences is a Professor in the Department of Psychology at the University of California, San Diego (UCSD). He leads the Perception and Cognition Lab, which participates in the Neuroscience Graduate Program. His research focuses on how behavioral goals and attention influence perception, memory, and decision-making, employing techniques like psychophysics, computational modeling, EEG, and fMRI. Key projects explore serial dependence, neural adaptation in visual cortex, and the interplay between sensory processing and mnemonic storage. Recent work highlights mechanisms reconciling repulsive neuronal adaptation with attractive behavioral biases. Affiliations: Department of Psychology, UCSD; Neuroscience Graduate Program. Research Themes: Visual perception, working memory, decision-making, neuroimaging. His lab investigates neural dynamics underlying cognitive processes, with particular emphasis on how attentional modulations and stimulus history shape neural representations. Notable contributions include studies on adaptive sensory coding and the role of top-down signals in perceptual stability.
Dorte Hammershøi is a Professor in the Department of Electronic Systems at The Technical Faculty of IT and Design, Aalborg University, Denmark. Her research focuses on acoustics, sound engineering, and hearing science with significant contributions to human hearing, ear canal acoustics, and audio technology applications. Her research interests include: Temporary Threshold Shift and frequency resolution in human hearing Ear canal acoustics and sound pressure level measurement Distortion Product Otoacoustic Emission (DPOAE) analysis Impulse response and acoustic impedance studies Hearing aid technology and rehabilitation methodologies Virtual reality audio interfaces and accessibility applications Professor Hammershøi's recent publications demonstrate a strong clinical-engineering interdisciplinary approach, bridging theoretical acoustics with practical hearing rehabilitation applications. Her work on hearing aid fitting methodologies, occupational noise exposure effects, and virtual reality audio interfaces shows consistent innovation in translating engineering principles to clinical practice. The research shows particular attention to individualized hearing solutions and accessibility technologies. Her scientific contributions have been recognized with: Dansk Lydpris 2020 (awarded November 17, 2021) Ambassadør for Aalborg (awarded September 15, 2004) Professor Hammershøi has supervised 5 PhD students and led numerous research projects including the ongoing "Audio Only VR for Blind Gamers" project (2024-2028) funded by the Independent Research Foundation of Denmark, and the completed "BEAR: Better Hearing Rehabilitation" project (2016-2022). Her research has attracted significant media attention with 110 press/media appearances discussing hearing damage prevention, tinnitus, and public health implications of noise exposure. She maintains active professional engagement through committee memberships (46 documented activities), international collaborations, and contributions to clinical practice guidelines. Her work continues to influence both academic research and practical applications in hearing science and audio engineering.
Ben Seiyon Lee is an Assistant Professor in the Department of Statistics at George Mason University's College of Science. His work bridges computational statistics, climate modeling, and environmental risk assessment. Education: PhD in Statistics, Pennsylvania State University (2020) Lee specializes in computational methods for high-dimensional spatiotemporal data and uncertainty quantification in climate models. His research explores climate change impacts on extreme hydrological events, wildfire emissions, and medical decision-making. Recent publications focus on Bayesian spatiotemporal frameworks for extreme precipitation analysis, zero-inflated spatial models, and multisector uncertainty quantification. His work addresses challenges in flood risk assessment, agricultural yield projections, and healthcare compliance metrics.
Leah K VanWey is Professor of Environment and Society and Sociology at Brown University, where she also serves as Dean of the School of Professional Studies. She holds affiliations with the Department of Sociology, Institute at Brown for Environment and Society, Population Studies and Training Center, Spatial Structures in the Social Sciences, and Department of Portuguese and Brazilian Studies. Previously, she served as Senior Deputy Director of the Institute at Brown for Environment and Society, Associate Director of the Population Studies and Training Center, and Associate Provost for Academic Space. VanWey completed her education at the University of North Carolina, earning a BA (1996), MA (1999), and PhD (2001). Her research focuses on social demography and environmental social science, particularly examining household responses to reforestation programs in Brazil's Atlantic Forest and the social/environmental impacts of frontier settlement in the Amazon. Her research interests include agricultural intensification, land use change, migration patterns, population-environment interactions, household dynamics, intergenerational support systems, and remittance economies, with a geographic focus on Brazil. She employs interdisciplinary approaches, collaborating with anthropologists, geographers, ecologists, and other social scientists. VanWey has secured significant research funding including grants from NSF, NIH, and NASA totaling over $2.5 million. Major projects include studying agricultural expansion in Brazil, climate variability impacts, land use change dynamics, and population-environment linkages. She mentors graduate students and postdoctoral researchers, including Trina Vithayathil. She teaches courses on human-environment interactions and research methods, including: Feeding Ten Billion, Methods for Interdisciplinary Environmental Research, Multivariate Statistical Methods, Fields and Methods of Social Research, and Professional Development seminars.
Britt Koskella is an Associate Professor at the University of California, Berkeley, affiliated with the Department of Environmental Science, Policy, and Management within the College of Natural Resources. Her research focuses on evolutionary biology, particularly host-pathogen coevolution and microbial interactions, integrating experimental evolution, field studies, and molecular biology. She leads the Koskella Lab, which investigates how microbial communities, phages, and pathogens influence host health and agricultural sustainability. Research Interests: Dr. Koskella explores the coevolutionary dynamics between hosts and their symbionts, including bacteriophage-bacteria interactions in plant microbiomes. Her work bridges ecological and evolutionary principles to address applied challenges in disease management and sustainable agriculture. Key areas include understanding phage-mediated selection in natural populations, the role of microbiomes in host defense, and the spatial/temporal adaptation of pathogens. Advancing Knowledge: Dr. Koskella’s lab employs experimental evolution in greenhouses and lab settings to test hypotheses derived from field observations. Recent studies highlight the indirect role of phages in plant disease protection and the design of synthetic microbial communities for agricultural applications. She collaborates on initiatives like the Joint Berkeley Initiative for Microbiome Sciences (JBIMS), emphasizing interdisciplinary approaches. Lab Team & Contributions: The lab includes students and researchers such as Eli Mehlferber, Asa Conover, and others, advancing projects on microbiome assembly, phage therapy, and pathogen coevolution. Dr. Koskella’s work has been published in high-impact journals like Current Biology , American Naturalist , and Ecology Letters .
Owen Price is an Associate Professor and Director in Bushfire Risk Management at the School of Earth, Atmospheric and Life Sciences (SEALS), University of Wollongong. His roles include leading research on wildfire impacts on ecosystems, human health, and infrastructure. He holds a PhD from the Australian National University (1998), an MSc from the University of Strathclyde (1986), and a BSc (hons) from the University of York (1985). Director, Centre for Environmental Risk Management of Bushfire (since 2020) Principal Fellow, SEALS (2019–2021) His research integrates fieldwork, GIS/remote sensing, and statistical modeling to address landscape-scale wildfire risks. Key interests include fire severity effects on biodiversity, smoke pollution impacts, and cost-effective fire management strategies. He supervises postgraduate students in topics like coastal wetland vulnerability and fire regime analysis. Recent grants include studies on coastal wetlands' fire resilience (2023–2026), Bayesian fire spread modeling (2023–2026), and evaluating aerial firefighting efficacy (2023). His work bridges ecological, social, and technical dimensions of wildfire risk. Notable awards and recognitions are not explicitly listed in the provided materials. His contributions to fire policy and community adaptation are highlighted through collaborative projects with government and environmental agencies.
Ebrahim Bedeer Mohamed is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Saskatchewan. He joined in July 2019, following roles as an Assistant Professor (Lecturer) at Ulster University, UK, and postdoctoral fellowships at Carleton University and the University of British Columbia. He holds a Ph.D. (Distinction) from Memorial University of Newfoundland (2014), with expertise in signal processing and wireless communications. His research focuses on optimizing communication systems through advanced signal processing techniques, including faster-than-Nyquist signaling, IoT network design, AI integration, and energy-efficient protocols. Key areas include next-generation communication networks, non-orthogonal modulation, and MIMO systems. Notable contributions include work on channel estimation for FTN signaling, RIS-aided wireless systems, and LR-FHSS protocols in IoT. His publications span spectral efficiency, interference minimization, and energy management in 5G/6G contexts. He actively seeks Ph.D. students with strong backgrounds in signal processing fundamentals. Awards and grants are not explicitly listed in the provided texts. His work emphasizes practical applications, such as UAV trajectory optimization for IoT data collection and energy-efficient caching strategies in dynamic networks.
Jesper Rindom Jensen is an Associate Professor in the Department of Electronic Systems at Aalborg University, Denmark, under the Technical Faculty of IT and Design. He is the Head of the Audio Analysis Lab, a leading research group in audio signal processing, since 2023. His work bridges theoretical signal processing and practical applications in artificial intelligence and audio systems. Full Name: Jesper Rindom Jensen Institution: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Audio Analysis Lab Email: jrj@es.aau.dk Office: Fredrik Bajers Vej 7B, B5-206, 9220 Aalborg Øst, Denmark Education: M.Sc. in Electronic Systems, Aalborg University (cum laude, 2009) Ph.D. in Signal Processing, Aalborg University (2012) Research Interests: Jesper Rindom Jensen's research centers on audio signal processing, with a strong emphasis on artificial intelligence, speech enhancement, noise reduction, beamforming, and multichannel systems. His work applies to diverse domains including robot and drone audition, spatial audio, and active noise control. He develops novel filtering techniques, including variable span linear filters and harmonic beamformers, to improve speech quality and intelligibility in noisy and reverberant environments. Publication Trends: His recent publications (2023–2025) show a strong trend toward integrating deep learning with classical signal processing, particularly in direction-of-arrival estimation, underwater acoustics, and robust multichannel systems. There is a clear focus on real-world applications, including sound zone control, active noise control, and limited-data scenarios using knowledge distillation. His work consistently emphasizes robustness, efficiency, and practical deployment. Scientific Awards and Recognition: AAU Talent for emerging research leaders Recipient of a competitive postdoc grant from the Danish Independent Research Council Advising and Grants: Jesper has supervised multiple PhD and master’s students, including Nørholm, Karimian-Azari, Zhang, and Wang. He has led significant research projects such as 'Sound Processing for Robots and Drones' (2018–2020) and participated in others related to joint audio-visual tracking and speech enhancement. His research has been supported by national funding bodies, reflecting its innovation and impact. Labs and Teams: He is a founding and core member of the Audio Analysis Lab at Aalborg University, which focuses on cutting-edge audio signal processing and AI-driven solutions. The lab fosters interdisciplinary collaboration and has produced numerous publications, datasets, and real-world applications. Jensen’s leadership since 2023 underscores his pivotal role in shaping the lab’s research direction.
Maiken H. Mikkelsen is the James N. and Elizabeth H. Barton Associate Professor in the Department of Electrical and Computer Engineering at Duke University, with a joint appointment in the Department of Physics . Her research focuses on quantum nanophotonics , plasmonics , and light-matter interactions in nanoscale materials, aiming to advance optoelectronics, quantum science, and biomedical diagnostics. Education B.S. in Physics, University of Copenhagen (2004) Ph.D. in Physics, University of California, Santa Barbara (2009) Postdoctoral Fellowship, University of California, Berkeley Her work explores nanophotonic engineering for quantum optics , spintronics , and ultrafast optoelectronics , with recent studies on nonlinear metasurfaces and plasmonic enhancement of immunoassays for point-of-care diagnostics. Publications highlight 2D semiconductor emission control , ultrafast single-photon sources , and metasurface-based photodetectors . Scientific Awards Maria Goeppert Mayer Award (2017) NSF CAREER Award (2015) Moore Inventor Fellow (2021) ONR/Air Force/Army Young Investigator Awards (2015-2017) Cottrell Scholar (2016) Stansell Family Distinguished Research Award (2021) She advises graduate students in Duke’s Electrical & Computer Engineering and Physics programs and leads the Mikkelsen Lab , which emphasizes ultrafast spectroscopy and quantum material development . The lab has graduated PhD students like Eunso Shin and Hengming Li (2025).
Esa Ollila serves as Associate Professor in the Department of Signal Processing and Acoustics at Aalto University, Finland, and holds an adjunct professorship in Statistics at the University of Oulu. His academic appointments include Academy of Finland Research Fellow (2010-2015) and prior senior research/lecturing roles at both institutions. His educational background features: M.Sc. in Mathematics, University of Oulu (1998) Ph.D. in Statistics (with honors), University of Jyväskylä (2002) D.Sc.(Tech) in Signal Processing (with honors), Aalto University (2010) Professor Ollila's research centers on statistical signal processing and robust statistical methodologies , with significant contributions to array processing, high-dimensional data analysis, and covariance matrix estimation. His work bridges theoretical statistics with practical applications in radar systems, wireless communications, and big data analytics, emphasizing robustness against outliers and computational efficiency in modern data-intensive environments. Current focus areas include compressed sensing, sparse approximation, and blind source separation techniques. Analysis of his 15 most recent publications (2024-2025) reveals three dominant trends: (1) robust covariance learning for massive random access systems, (2) integrated sensing and communications (ISAC) for 6G networks using advanced beamforming, and (3) geometric approaches to elliptical distributions in statistical inference. His work increasingly incorporates deep learning (GANs, graph neural networks) while maintaining strong foundations in classical signal processing theory. Key recognitions include: Academy of Finland Postdoctoral Fellowship (2004-2007) Academy of Finland Research Fellowship (2010-2015) His research has been supported through prestigious Academy of Finland grants totaling over a decade of continuous funding. Professor Ollila currently leads an active research group at Aalto University, supervising doctoral candidates and collaborating internationally with institutions including Princeton University (where he served as Visiting Post-doctoral Research Associate during 2010-2011). He maintains strong ties with the University of Oulu through his adjunct professorship and has contributed to EURASIP's Special Area Team on Theoretical and Methodological Trends in Signal Processing. The Esa Ollila Research Group focuses on cutting-edge challenges in statistical signal processing, with current projects spanning robust DOA estimation under non-Gaussian noise, covariance matrix learning for massive MIMO systems, and machine learning-enhanced radar-communication integration. The group actively develops open-source tools like the fitHeavyTail R package for heavy-tailed distribution modeling and maintains collaborations with industry partners in wireless communications.
Prof. Bernhard U. Seeber is an Extraordinary Professor at the Technical University of Munich (TUM), leading the Chair of Audio Signal Processing within the TUM School of Computation, Information and Technology. His work bridges auditory neuroscience and engineering, focusing on improving hearing aids, cochlear implants, and virtual acoustic systems. He holds affiliations with the Bernstein Center for Computational Neuroscience, Munich Institute of Biomedical Engineering, and others. Education: Studied and earned his PhD (2003) in Electrical Engineering and Information Technology at TUM. Postdoctoral research included time at UC Berkeley and the MRC Institute of Hearing Research (UK), where he pioneered studies on binaural hearing and cochlear implant optimization. Research Interests: Combines experimental and theoretical approaches to explore auditory scene analysis, binaural unmasking, and spatial hearing. Key areas include signal coding for cochlear implants, virtual acoustics, and non-destructive acoustic monitoring. His work emphasizes interdisciplinary collaboration with industry and academia. Awards: Lothar Cremer Award (2010), Emmy Noether Fellowship (2007), and recognition from the German Acoustical Society. Teaching: Offers courses on audio communication, computational neuroscience, and technical acoustics. Projects: Leads initiatives like HAPPAA and Auralization, advancing sound field synthesis and hearing aid algorithms. Current Roles: Head of Chair of Audio Signal Processing, Board Member of DEGA, and spokesperson for the ITG Technical Committee on Hearing Acoustics.
Prof. Dr. Ralf Merz serves as Head of the Department of Catchment Hydrology at the Helmholtz Centre for Environmental Research (UFZ) and holds a Full Professorship in Catchment Hydrology at Martin-Luther University Halle-Wittenberg since 2011. His career bridges hydrological modeling, flood risk assessment, and water quality analysis across diverse climates from Central Asia to Europe. MSc in Civil Engineering (Technical University of Karlsruhe, 1997) PhD in Hydrology (Vienna University of Technology, 2002) Habilitation in Hydrology (Vienna University of Technology, 2009) Research Interests span comparative hydrology, flood generation mechanisms, climate change impacts on water resources, and nitrate dynamics in river systems. His work emphasizes process-based understanding of runoff events and regional flood modeling through innovative approaches like the PHEV distribution framework. Scientific Contributions include over 100 publications (2003-2025) on: Flood frequency analysis in changing climates Groundwater recharge in arid regions Hydrochemical response to droughts Remote sensing applications for groundwater studies Multi-response calibration of hydrological models Key projects involve MOSES observatory development, TRACER research school, and Pamir Mountains glaciological studies. Recognitions : APART research grant (Austrian Academy of Sciences, 2006) Leadership extends to directing the Catchment Hydrology department and participating in European hydrological networks like the Bode Hydrological Observatory and TERENO infrastructure. His methodological advancements include flood time-scale analysis and event runoff coefficient regionalization.
Anup Basu is a Professor in the Department of Computing Science at the University of Alberta. His research focuses on computer graphics, computer vision, and multimedia communications. He holds an B.S. in Math & Statistics from the Indian Statistical Institute (1980), an M.E. in Computer Science from the Indian Statistical Institute (1983), and a Ph.D. in Computing Science from the University of Maryland (1990). His work emphasizes Quality of Service (QoS) in multimedia delivery for e-commerce and telelearning, adaptive bandwidth monitoring, and 3D visualization tools. He pioneered foveated image compression and stereo visualization techniques, contributing to MPEG-4 coding standards. He leads major initiatives like the ASRA/TelePhotogenics/IBM 3D Medical Imaging project ($2M+ funding) and developed patented SHR Stereo/3D scanning technologies. Awards include the American Neurological Association Fellowship. He has held leadership roles as General Chair for IEEE International Conferences on SMC (2017), Multimedia & Expo (2013), and SMC (2014). His research integrates interdisciplinary collaborations across universities and industry partners, leveraging advanced equipment like the CAVE system for immersive visualization.
Jason Schweinsberg is a Professor in the Department of Mathematics at the University of California, San Diego (UCSD), where he has been a faculty member since Fall 2004. His academic journey began with a Ph.D. in Statistics from the University of California, Berkeley in 2001, followed by a three-year NSF Postdoctoral Fellowship at Cornell University. His research focuses on probability theory with applications to evolutionary biology and population genetics. Schweinsberg's work centers on stochastic processes involving coalescence, branching Brownian motion, and their connections to biological phenomena. He has made significant contributions to understanding population models undergoing selection, cancer evolution, and spatial mutation processes. Recent publications reveal a strong emphasis on coalescent theory (particularly Λ-coalescents and nested coalescents), branching processes with absorption, and spatial evolutionary models. His work often bridges rigorous mathematical analysis with biological applications, especially in population genetics and cancer modeling. The 15 most recent articles demonstrate consistent focus on asymptotic analysis of stochastic processes, genealogical structures, and mutation dynamics in evolving populations. Scientific Awards: Fellow of the Institute of Mathematical Statistics NSF Postdoctoral Research Fellowship While specific student names aren't listed in the source material, Schweinsberg has delivered numerous lecture series at international institutions including the Indian Institute of Science (Bangalore), Centre de Recherches Mathématiques (Montreal), and the Isaac Newton Institute (Cambridge), indicating active mentorship and academic leadership. His collaborations span multiple institutions, with frequent co-authorship with researchers like Julien Berestycki, Nathanaël Berestycki, and Rick Durrett. Though no formal lab structure is mentioned, Schweinsberg participates in interdisciplinary research communities through workshops at institutions like BIRS (Banff International Research Station), where he presented on mutation patterns in spatially structured populations in May 2025. His work connects probability theory with biological applications through sustained collaborations across mathematics, statistics, and computational biology fields.
Prof. Slawomir Stanczak is a Full Professor in Network Information Theory at Technische Universität Berlin and Head of the Wireless Communications and Networks department at Fraunhofer Heinrich-Hertz-Institut (HHI). His expertise spans wireless communications, signal processing, and machine learning, with a focus on 5G/6G networks and reconfigurable intelligent surfaces. He has held visiting roles at RWTH Aachen University and Stanford University, and leads initiatives like the 6G Research & Innovation Cluster and the xG-Incubator project. Education: Dipl.-Ing. in Electrical Engineering, TU Berlin (1998) Dr.-Ing. (summa cum laude), TU Berlin (2003) Habilitation (venia legendi), TU Berlin (2006) Research & Awards: Recipient of the Best Paper Award from the German Communication Engineering Society (2014) Research grants from the German Research Foundation Co-authored over 200 peer-reviewed papers and two books Chair of the ITU-T Focus Group on Machine Learning for Future Networks (2017-2020) Leadership & Projects: Chairman of 5G Berlin association since 2020 Coordinator of 6G Research & Innovation Cluster and CampusOS flagship project Project lead of xG-Incubator (StartUpConnect initiative) Teaching: Offers courses on Machine Learning and Wireless Communication at TU Berlin.
