Julio Rozas is a Full Professor of Genetics at the Universitat de Barcelona (since 2009) and a member of the Bioinformatics Barcelona (BiB) board. He holds a PhD in Biology (1990) and a postdoctoral fellowship at Harvard University (1991-1992). His research focuses on molecular evolution mechanisms, genomic basis of adaptation, and chemosensory systems in invertebrates. He has developed bioinformatics tools like DnaSP and contributed to genome sequencing consortia. He has published over 113 articles in the last decade, including high-impact journals like Nature and Science, with an h-index of 40. He has supervised 10 doctoral theses and serves as an associate editor for BMC Genomics. Research interests include population genomics, comparative genomics, and bioinformatics. Notable achievements include the ICREA Academia Prize (2011) and the Excellence Award in PhD studies (1991).
Manuel Arellano is Professor of Economics at the Center for Monetary and Financial Studies (CEMFI) in Madrid since 1991, with prior appointments at the University of Oxford (1985-89) and London School of Economics (1989-91). A leading econometrician specializing in panel data analysis, his work bridges theoretical econometrics and labor economics applications. He earned his undergraduate degree from the University of Barcelona and Ph.D. from the London School of Economics. Arellano's research focuses on econometric methodology for panel data, particularly dynamic models with heterogeneity. His seminal book Panel Data Econometrics (2003) established foundational frameworks for nonlinear and dynamic panel estimation. Current work extends to distributional analysis of random coefficients and robust inference under uncertainty, maintaining consistent emphasis on labor market applications like unemployment duration and policy evaluation. His publication history reveals a 30-year trajectory advancing panel data econometrics, evolving from specification testing (1987-1995) to sophisticated dynamic and nonlinear models (2003-2014), with persistent focus on practical implementation and labor economics applications. Major honors include: President of the Econometric Society (2014) Foreign Honorary Member of the American Academy of Arts and Sciences (2014) Rey Jaime I Prize in Economics (2012) ISI Highly Cited Researcher status (2010) Fellow of the Econometric Society (2002) No information on student advising or research grants appears in the source materials. Similarly, details about research laboratories or collaborative teams are not documented in the provided texts.
Matthew Fagan is an Associate Professor in the Department of Geography & Environmental Systems at the University of Maryland, Baltimore County (UMBC), holding a Ph.D. from Columbia University (2014). His research integrates remote sensing, landscape ecology, and conservation biology to study forest dynamics across tropical and temperate ecosystems. His primary research interests focus on: Landscape-scale habitat degradation and restoration Remote sensing applications for forest monitoring Policy effectiveness in tropical conservation corridors Socio-ecological drivers of agricultural expansion Connectivity and reforestation processes Recent publication trends reveal increasing emphasis on machine learning integration with high-resolution satellite imagery for tropical forest monitoring, particularly in assessing degradation patterns, carbon sequestration potential, and the distinction between natural regeneration versus plantation forestry. His work increasingly addresses the intersection of climate change mitigation, biodiversity conservation, and poverty reduction through land use studies in Africa and Latin America. Dr. Fagan leads the "Earth from Above" research laboratory, which conducts field and remote sensing work in Costa Rica, Maryland, and the Caribbean, with specific projects examining timber plantation impacts, riparian forest connectivity using LiDAR, and conservation of endangered species like the Bahama Oriole.
Zhipeng Lu is currently an Associate Professor of Pharmacology and Pharmaceutical Sciences at the University of Southern California (USC) School of Pharmacy. His research focuses on understanding RNA molecules and their structural complexity as a second layer of genetic instructions beyond protein encoding. He directs the Lu Lab at USC, which develops and applies novel technologies to investigate RNA structures, interactions, chemical modifications, and functions in cellular processes and animal development. Dr. Lu's research interests center on "RNA machines" in living cells, with particular emphasis on how RNA molecules fold into structures and form intermolecular interactions to execute genetic instructions. His work spans multiple dimensions of RNA biology, including RNA structure-function relationships, RNA-protein interactions, RNA modifications, and the role of RNA in human diseases such as genetic disorders and viral infections. The lab combines computational, chemical, and biological approaches to elucidate fundamental mechanisms of RNA machines, with the ultimate goal of developing new understanding and therapies targeting human diseases. Analysis of Dr. Lu's publication history reveals a strong trajectory in RNA structure and interaction mapping technologies. His work has evolved from foundational studies on RNA processing and modification to developing innovative high-throughput methods like PARIS and RISE for analyzing RNA interactomes. Recent publications focus on specific RNA systems like XIST and snoRNAs, demonstrating how his lab has moved from method development to applying these tools to solve longstanding biological questions in epigenetics and RNA therapeutics. Dr. Lu has received numerous prestigious awards recognizing his contributions to RNA research: NHGRI K99/R00 NIH Pathway to Independence Award (2017-2022) RNA Society Scaringe Award (2017) Stanford University Jump Start Award for Excellence in Research (2016-2017) Damon Runyon-Sohn Fellowship (2015-2017) His research is supported by multiple funding sources from organizations including the National Institutes of Health and other foundations. The Lu Lab is actively recruiting PhD students and postdoctoral researchers to work on several cutting-edge directions including RNA structures, interaction networks, RNA modification mechanisms, and their roles in development and disease. The lab integrates biological, chemical, and computational approaches to advance RNA biology and push forward RNA medicine. The Lu Lab at USC is a dynamic research environment focused on "RNA machines" with recent highlights including solving aspects of the orphan snoRNA problem and discovering snoRNAs that control eMet tRNA activity. The lab's vision emphasizes creative exploration of RNA biology, with researchers encouraged to pursue innovative ideas much like "wild animals running in the African savannah." Current research directions include analysis of RNA structures, interaction networks, RNA modification mechanisms, and their roles in development and disease, with applications to genetic disorders, cancers, and viral infections.
Theodore Kim is a Professor of Computer Science at Yale University, where he co-leads the Computer Graphics Group with Julie Dorsey and Holly Rushmeier. His research focuses on physics-based simulation, including fluid dynamics, solid mechanics, and fractal growth structures. He holds a PhD from the University of North Carolina at Chapel Hill and has held academic positions at UCSB and the University of Saskatchewan. His work has been applied in over two dozen films, earning him SciTech Oscars in 2012 and 2022. He previously served as a Senior Research Scientist at Pixar, contributing to projects like *Cars 3*, *Coco*, and *Incredibles 2*. Education: Ph.D., Computer Science, University of North Carolina at Chapel Hill (2006) M.S., Computer Science, University of North Carolina at Chapel Hill (2006) B.S., Computer Science, Cornell University (2001) Research Interests: Kim’s work bridges academia and industry, emphasizing practical applications of physics-based simulation. Notable areas include hair and skin simulation for animation, fluid dynamics, and the historical context of computer graphics innovations. His research also addresses racial biases in graphics, such as in hair and skin modeling. Articles Trends: Recent work emphasizes diverse representation (e.g., Black hair simulation), biomechanical accuracy (feather modeling), and historical analysis of technical contributions (e.g., Búi Tướng Phong’s legacy). Earlier publications focus on fluid subspace methods, wavelet turbulence, and efficient simulation techniques. Awards: Academy Award for Scientific and Technical Achievement (2012, 2022) NSF CAREER Award (2013–2018) UCSB Harold J. Plous Award (2015) Best Paper Awards at SCA (2011, 2016, 2018) Grants & Labs: Leads Yale’s Critical Computing Initiative and directs undergraduate studies in CS. His lab collaborates with industry (e.g., Pixar) and emphasizes open-source software. Current projects include fractal design tools and anti-racist graphics research.
Thomas Bjørner is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. He serves as Head of the Media Innovation & Game Research (Me-Ga) unit and co-founded the research network for qualitative methods (since 2007) with 40+ company collaborations. Specializes in qualitative/mixed methods for technology evaluation Teaches PhD courses in advanced qualitative methods EU expert evaluator for research grants His research focuses on gamified learning , VR for social communication , and technology acceptance studies , often addressing UN Sustainable Development Goals. Recent projects include: Audio-only VR for blind gamers Generative AI integration in education Plastic crisis awareness games Smart city implementation barriers Scientific Awards: Serious Game Competition Award (2022) International conference prizes (2020, 2018) With over 121 publications including two textbooks, his work emphasizes applied qualitative methods with improved validity in technology contexts, particularly for youth education and media research.
Dr Paul Sidwell is an Honorary Associate in the Department of Linguistics at The University of Sydney. His research focuses on Austroasiatic languages, particularly their classification, historical development, and syntactic structures. He has authored and edited numerous works including A Grammar of May: An Austroasiatic Language of Vietnam (2021) and contributed to major volumes like The Languages and Linguistics of Mainland Southeast Asia: A Comprehensive Guide (2021). His work spans comparative linguistics, epigraphy, and the prehistory of Southeast Asian languages. Recent publications include studies on Nicobarese language classification (2022), Austroasiatic syntax (2020), and Tai-Kadai language history (2021). His research integrates phylogenetic analysis, historical reconstruction, and areal linguistics to explore language relationships across Mainland Southeast Asia. Notable contributions include foundational works on Palaungic languages (2015), Old Khmer (2014), and the Munda Maritime Hypothesis (2019). His scholarship combines rigorous linguistic fieldwork with theoretical insights, advancing understanding of Austroasiatic linguistic diversity.
Pier Palamara is an Associate Professor of Statistical and Population Genetics at the University of Oxford's Department of Statistics, affiliated with the Centre for Human Genetics. He holds a PhD in Computer Science from Columbia University (2014) and completed postdoctoral training at Harvard Chan School of Public Health and the Broad Institute of MIT and Harvard. His research integrates statistics, computer science, and genetics to develop methods for analyzing large genomic datasets, focusing on evolutionary parameters, demographic history, complex trait genetics, and disease variation. Key research interests include reconstructing population movements via genetic data, studying natural selection and mutation rates in human genomes, and developing scalable algorithms for genomic analysis. He leads the Palamara Lab, which collaborates on projects like the Genomics England haplotype reference panel and the UK Biobank imputation. His lab's work is supported by grants and partnerships, and they develop software tools such as ASMC, Quickdraws, and Threads. Recent publications highlight contributions to Indo-European genetic origins, scalable mixed-model association methods, and ancient DNA analysis of European farmers. He advises graduate students and has mentored researchers in computational biology and statistical genetics.
Piet Desmet is a full professor at KU Leuven's Faculty of Arts, serving as vice rector of KU Leuven, Kulak Kortrijk Campus, and academic director of the Office of the Academic Director, Bruges Campus. He leads multiple research divisions including itec and its Language and Technology subdivision, and is a member of Leuven.AI - KU Leuven Institute for Artificial Intelligence. As general coordinator of itec and academic director of the imec smart education research program, he oversees significant research initiatives spanning multiple campuses. Desmet's research focuses on the intersection of language learning and technology, with particular expertise in Second Language Acquisition and Technology, Computer-assisted Language Learning (including AI-based chatbots), Learning Analytics, and Language Technology and Corpus Linguistics. His work explores intelligent feedback systems, linguistic complexity prediction, adaptive testing, and natural language processing applications for educational contexts. His research spans theoretical linguistic frameworks to practical educational implementations, with a strong emphasis on empirical validation of technological interventions in language learning. Analysis of Desmet's recent publications reveals a strong trajectory toward integrating artificial intelligence with language education, particularly through conversational AI and learning analytics. His work increasingly focuses on chatbot-assisted language learning, adaptive assessment systems powered by large language models, and the application of computational linguistics to educational problems. The publications demonstrate a consistent methodological approach combining theoretical linguistics with empirical educational research, often employing eye-tracking, ERP studies, and learning analytics to evaluate effectiveness. Desmet actively supervises numerous PhD students and leads multiple major research projects including Smart Education at Schools (2025-2026), Enhancing EFL Learners' Speaking Ability through Chatbot-Assisted Dynamic Assessment Powered by LLMs (2024-2028), and the Flanders Ed Tech Hub (2022-2025). His research portfolio demonstrates significant funding success across multiple national and international initiatives focused on educational technology and language learning. As head of itec (an imec research team at KU Leuven), Desmet leads a substantial research ecosystem focused on smart education technologies. The itec team collaborates extensively with Leuven.AI and the KU Leuven Educational Research Institute (LIVO), creating a multidisciplinary environment that bridges computational linguistics, educational psychology, and artificial intelligence. Recent initiatives include the 'AI in Education' online training course and the network for Edtech and Learntech in Flanders.
Mia Filic is a Full Professor of Theoretical Philosophy at the Faculty of Philosophy of the Università Vita Salute San Raffaele in Milan. She holds a doctoral affiliation with ETH Zürich's Department of Computer Science (D-INFK) and is affiliated with the Institute for Information Security. Her career includes teaching aesthetics at the Venice Academy of Fine Arts and collaborating with Massimo Cacciari at the IUAV. She co-founded the journal Paradosso and directs the column Theorein in Anfione-Zeto . Education: Graduated from the University of Venice in 1981 under Emanuele Severino Research Focus: Ontology, aesthetics, philosophy of music, and interdisciplinary studies in arts Her work bridges philosophy with art, literature, and music, emphasizing ontological questions in contemporary cultural production. Recent publications explore photography's philosophical dimensions, Lucio Battisti's musical philosophy, and Calvino's narrative structures. Awards: Premio Capalbio (2014) Labs/Teams: Co-director of Diaporein Research Center (meta-physics and philosophy of arts)
Jim Berryman is an Affiliate in Information Studies at the University of Glasgow's School of Humanities. His research spans art history, cultural studies, and social theory, with a focus on the intersection of art, technology, and historical narratives. He explores topics such as AI-generated art, Marxist critiques of art history, and the role of documentation in conceptual art. Berryman has conducted extensive work on Australian cultural history, including studies of national identity, colonial legacies, and the historiography of art. His research interests include the social origins of art, the ethics of cultural repatriation, and the application of digital methods to art analysis. Berryman has collaborated with institutions like the University of Melbourne on projects involving Robert Menzies’ collections and has contributed to debates around museum ethics and the representation of human remains. His interdisciplinary approach bridges art history with philosophy, sociology, and technology studies. Key Themes: AI in Art, Marxist Art Theory, Australian Cultural History, Art Documentation Publications: Over 29 peer-reviewed articles and book chapters since 2012 Collaborations: Caitlin Stone on Menzies collections, studies of Robert Hughes and Bernard Smith Berryman’s recent work examines the implications of generative AI for artistic creativity and critiques traditional historiographical frameworks. His analysis of Arnold Hauser’s theories demonstrates a commitment to reinterpreting foundational art historical narratives through contemporary lenses.
Tom Verhoeff is an Assistant Professor at the Faculty of Mathematics and Computing Science of Eindhoven University of Technology (TU/e) , working within the Software Engineering & Technology group. His research focuses on Model-Driven Engineering (MDE) , Domain-Specific Languages (DSLs) , and the intersection of mathematics, computing, and the arts . He teaches courses in data analytics, programming, algorithms, theoretical computer science , and logic . Verhoeff earned both his MSc and PhD in Technical Science (Mathematics and Computer Science) from TU/e. He is actively involved in promoting mathematics and informatics through initiatives like the annual Bridges conference , and serves as board member and treasurer of the Dutch Mathematics Olympiad , as well as chair of the Koos Verhoeff MathArt foundation . He has also held roles as guest lecturer in Lithuania and Finals Director for the ACM International Collegiate Programming Contest . Research Interests: Verhoeff’s work spans Model-Driven Engineering , domain-specific language development , and 3D geometric modeling . His scholarship often explores symmetry, recursion, and mathematical visualization , particularly through computational art and algorithmic puzzles . Recent publications highlight 3D rotation methods , knot theory , and mathematical art using lattice paths and geometric transformations . Scientific Awards: ACM ICPC European Founders Award (2004) IOI Distinguished Service Award (2007) Second Place in the 2022 Wolfram Computational Art Contest Notable Collaborations and Affiliations: He is affiliated with the Esprit Working Group on Asynchronous Circuit Design (ACiD-WG) , WIRE (TUE Mathematics Alumni) , ACM (Senior Member) , CSTA , IEEE Computer Society , and Royal Dutch Mathematical Society (KWG) .
David Frazier is a Professor in the Department of Econometrics & Business Statistics at Monash University, specializing in simulation-based inference, financial econometrics, and nonparametric/semiparametric modeling. He teaches ETC 1010: Data Modeling and Computing. His research focuses on robust statistical methods, Bayesian computation, and model misspecification. Key projects include 'Consequences of Model Misspecification in Approximate Bayesian Computation' (2020-2025) and 'Loss-based Bayesian Prediction' (2020-2025). Recent work addresses forecasting in misspecified models, weak identification in econometric frameworks, and robust variational Bayes techniques. His contributions align with UN Sustainable Development Goals related to economic and environmental sustainability. Projects: 4 active/funded projects with ARC, Brown University, and international collaborators. Publications: Over 37 peer-reviewed articles in journals like the Journal of the American Statistical Association and Journal of Econometrics. Research interests include advancing Bayesian methodologies for complex models, with applications in asset pricing and economic forecasting. His work emphasizes reliability in statistical inference under model uncertainty and computational efficiency.
Skirmantas Janusonis is an Associate Professor in the Department of Psychological and Brain Sciences at the University of California, Santa Barbara (UCSB). He is a core faculty member of the UCSB Neuroscience Research Institute and the Interdepartmental Graduate Program in Dynamical Neuroscience, and a member of the California NanoSystems Institute. His research program lies at the intersection of neuroscience, complex systems, and computational modeling. Education: Ph.D. in Neuroscience and Behavior, University of Massachusetts Amherst Postdoctoral Research, Department of Neuroscience, Yale University School of Medicine B.S./M.S. in Biology, Vilnius University, Lithuania Dr. Janusonis's research focuses on the stochastic (random walk-like) behavior of serotonergic axons in the brain, particularly within the ascending reticular activating system and the broader serotonergic matrix. His work integrates molecular neurobiology, comparative neuroanatomy (from sharks to rodents to humans), advanced microscopy, and supercomputing simulations. He investigates how these complex systems self-organize and their relevance to mental disorders, especially autism and the enigma of platelet hyperserotonemia. His lab collaborates with physicists, mathematicians, and engineers to model anomalous diffusion and fractional Brownian motion in 3D brain spaces. His recent publications reveal a strong trend toward computational and theoretical neuroscience, using high-resolution data and mathematical generalizations to model axonal distributions. Key themes include reflected fractional Brownian motion, self-organization of serotonergic densities, and the interface between central and peripheral serotonin systems. His work challenges traditional views of the blood-brain barrier and proposes interdisciplinary solutions involving immunology, physiology, and computer science. Scientific Awards and Recognition: Elected to the Board of Directors of the Organization for Computational Neurosciences (2024) NSF, NIMH, and California NanoSystems Institute grant funding Multiple student awards under his mentorship, including the Harry J. Carlisle Award and NIH IRTA NSF CRCNS and Frontera supercomputing grants UCSB Art of Science People's Choice Award (awarded to lab member) Dr. Janusonis actively mentors PhD students such as Justin Haiman and Dahyana Arroyo, and has advised alumni including Dr. Angela Chen, Dr. Kasie Mays, and Dr. Melissa Hingorani. His lab has received numerous grants from the NSF and NIH, supporting research on stochastic axon systems and super-resolution imaging. He teaches graduate and undergraduate courses including Neuroanatomy (Psy 269), Neurobiology of Brain States (Psy 136), and Complex Systems (Psy 113L). Research Team and Collaborations: The Janusonis Lab is an interdisciplinary group combining neuroscience, mathematics, and engineering. It collaborates with institutions such as UC San Diego, the University of Pisa, and MIT. The lab is equipped with advanced imaging tools and has access to Frontera, a leading NSF supercomputer. Outreach includes science nights at local schools and public lectures at the Santa Barbara Museum of Natural History.
Dr Manuela Truebano is a Lecturer in Marine Molecular Biology at the University of Plymouth, affiliated with the School of Biological and Marine Sciences (part of the Faculty of Science and Engineering). She holds a BSc in Marine Biology from the University of Liverpool, an MSc in Shellfish Biology from Bangor University, and a PhD in Molecular Ecophysiology (focusing on thermal stress) from Swansea University and the British Antarctic Survey. Her research group is part of the Ecophysiology and Development Research group within the Marine Biology and Ecology Research Centre. Her teaching portfolio includes module leadership roles in Marine Molecular Biology, Ecophysiology of Marine Animals, Conservation Physiology, and field courses. She has supervised two postgraduate research degrees: Michael Collins (PhD, 2019) and George Mason (ResM, 2021). Dr Truebano’s research focuses on thermal tolerance, hypoxia, and environmental stress responses in marine organisms, particularly invertebrates. She employs molecular and physiological approaches to study climate change impacts, including the development of tools like Dev-ResNet and HeartCV for automated phenotyping. Her work intersects with global sustainability goals, emphasizing organismal resilience to environmental shifts. Her recent publications highlight advancements in understanding transgenerational plasticity, thermal acclimation, and the interplay of multiple stressors. Teaching and learning grants include a 2015 initiative exploring video tutorials for lab skill training. She collaborates extensively in interdisciplinary projects, contributing to both academic and applied marine science.
