Prof. Dr. Alex Hall is an Associate Professor at the Department of Environmental Systems Science and Head of the Institute of Integrative Biology at ETH Zürich , Switzerland. He holds a PhD from the University of Edinburgh (2008), followed by postdoctoral work at the University of Oxford and ETH Zürich, including prestigious SNSF Ambizione and Marie Curie Intra-European fellowships. Research Focus: The Hall lab investigates Microbial interactions in human microbiomes Antibiotic resistance evolution Horizontal gene transfer dynamics Computational and in vitro modeling of microbial communities Evolutionary medicine applications Scientific Contributions: His recent studies analyze probiotic treatments for Staphylococcus aureus decolonization, strain-specific ecological success in gut microbiomes, and CRISPR-Cas system roles in plasmid conflicts. The lab employs computational frameworks combined with experimental validations. Scientific Awards: SNSF Ambizione fellowship Marie Curie Intra-European fellowship He also serves on the SNSF PRIMA fellowship evaluation panel and the ETH Zürich Coordination Council Medicine .
Emily A. Gasser is an Associate Professor in the Linguistics Department at Swarthmore College , specializing in Austronesian languages , Wallacea & northwest New Guinea , and language documentation . Her research spans phonology, morphology, typology , and language contact , with a focus on endangered languages and computational phylogenetics . She is currently on sabbatical for the 2025-26 academic year, conducting fieldwork in Manokwari, writing a Wamesa grammar, and developing new courses. Research Interests include: Language documentation and fieldwork in Austronesian and Papuan-speaking regions Phonological variation and vowel harmony systems Typological surveys of adnominal possession and morphological structures Interaction between prosodic features in media speech and socio-phonetics Computational tools for historical linguistics and classifier system analysis Recent publications focus on vowel harmony , prosodic perception , and possessive constructions across Wallacea and Northwest New Guinea. She edits volumes on Austronesian-Papuan language contact and contributes to open-access research initiatives.
Aapo Hyvärinen is a Professor of Computer Science at the University of Helsinki , affiliated with the Helsinki Institute for Information Technology and the Helsinki Probabilistic Machine Learning Lab . He previously held the position of Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London (2016-2019). Education : Undergraduate Mathematics at University of Helsinki, Vienna, and Paris; Ph.D. in Information Science from Helsinki University of Technology (1997) His research focuses on machine learning and computational neuroscience , particularly: Independent Component Analysis (ICA) Natural Image Statistics Causal Representation Learning Neural Signal Processing Applications to brain imaging (MEG, CryoEM) Recent publications emphasize causal discovery , identifiable machine learning , and nonlinear ICA . Key projects include: VETURI (AI for health) DIGIMIND (AI in mental health) CIFAR grants (2022-2025) Scientific awards : Highly Cited Researcher (2010) He serves as Action Editor for the Journal of Machine Learning Research and Neural Computation , and has held Area Chair roles at NeurIPS, ICML, ICLR, AISTATS, and UAI conferences. His work bridges theoretical machine learning with neuroscience and philosophical implications of artificial intelligence .
Trent K. Bollinger is a Professor in the Department of Veterinary Pathology at the University of Saskatchewan's Western College of Veterinary Medicine (WCVM), and serves as Regional Director for the Western/Northern Region of the Canadian Wildlife Health Cooperative (CWHC). His academic credentials include a BSc (Honours) from the University of Saskatchewan (1984), a DVM (Distinction) from the University of Saskatchewan (1988), and a DVSc in Pathology from the Ontario Veterinary College (1992). Dr. Bollinger's research focuses on the pathology and epidemiology of diseases in wildlife and fish, with particular emphasis on chronic wasting disease in deer/elk and white-nose syndrome in bats. He has conducted extensive studies on disease transmission dynamics, wildlife population health, and the ecological impacts of emerging pathogens. His work bridges veterinary science, ecology, and conservation biology. His publications demonstrate expertise in viral and bacterial zoonoses, fungal pathogens affecting bats, and spatial epidemiology of wildlife diseases. Recent research highlights include investigating sylvatic plague in prairie dogs, coronavirus persistence in hibernating bats, and landscape connectivity's role in chronic wasting disease spread. His studies often combine molecular diagnostics, field observations, and ecological modeling. Dr. Bollinger collaborates with national and international wildlife agencies, contributing to disease surveillance and management strategies for endangered species. His work emphasizes the interconnectedness of wildlife health, ecosystem health, and public health concerns.
Prof. Waldemar Kolanus leads the Molecular Immunology and Cell Biology department at the University of Bonn's Life & Medical Sciences Institute (LIMES) . His research bridges immunoregulation , stem cell dynamics , and metabolic stress responses in immune cells. Unit 2 member at LIMES Principal investigator in SFB 704 and ImmunoSensation Cluster Leads a multidisciplinary lab with postdocs, PhD students, and technical staff His work focuses on intracellular signaling pathways connecting immune activation to tissue homeostasis, particularly through: Cytohesin proteins in integrin-mediated adhesion and migration TRIM71 in stem cell regulation and congenital hydrocephalus High-salt environments affecting macrophage function Publication trends show expertise in immune cell migration , genetic models , and chemical inhibition , with frequent use of mice and zebrafish for in vivo studies. Key articles explore: TRIM71's dual role in auditory development and germ cell maintenance Cytohesin family's Golgi regulation and insulin signaling Ruxolitinib's off-target migration inhibition of dendritic cells Contact details: Address: LIMES Institute, Carl-Troll-Straße 31, Bonn Email: kolanus.sekretariat@uni-bonn.de Phone: +49 228 73-62788
Dr. Frances Chen is a Professor and Area Coordinator in the Department of Psychology at the University of British Columbia (UBC), located on the traditional, ancestral, and unceded territory of the Musqueam People. She holds a PhD from Stanford University (2009). Her research integrates health psychology, social psychology, and neuroendocrinology to explore how social experiences influence mental and physical health. Key areas include the physiological impacts of loneliness, social support, and hormonal changes during puberty on adolescent development. Education: PhD, Psychology, Stanford University, 2009 Research Focus: Dr. Chen investigates how social interactions 'get under the skin' through studies on loneliness, stress, conflict negotiation, and hormonal mechanisms. Her work emphasizes interventions to enhance social connection and reduce health disparities. Recent Article Trends: Recent publications highlight interdisciplinary approaches, including genetic influences on depression, effects of near-infrared lighting on cognition, and longitudinal studies on adolescent hormonal contraceptive use. Her work bridges basic science and applied health outcomes. Awards & Grants: Michael Smith Health Research BC C2 Award (2022) Killam Faculty Research Fellowship (2019) Teaching & Learning Enhancement Fund Grant (2025) SSHRC Prosociality Project Funding (2023) Lab & Mentorship: Director of the Social Health Lab, she mentors graduate and undergraduate students, prioritizing equity and inclusion. Recent lab achievements include studies on teen health development and interventions to improve student success in psychology programs. Lab Initiatives: UBC Teen Health and Development Study (longitudinal hormonal/mental health tracking) NIR lighting health impact research (collaborative interdisciplinary project) Prosociality 'in the Wild' SSHRC project
Dylan Hadfield-Menell is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, holding the Bonnie and Marty (1964) Tenenbaum Career Development Professorship. His research focuses on AI alignment and human-AI interaction within MIT's School of Engineering. His research interests center on agent alignment problems in AI systems, particularly examining uncertainty in objective optimization for human-robot teams and societal oversight of machine learning systems. Key areas include the principal-agent alignment problem , assistance games frameworks , and robust preference learning that accounts for hidden contextual factors in reinforcement learning from human feedback. His recent publications reveal strong trends toward multi-agent cooperation , formal contract mechanisms for resolving social dilemmas, and advanced evaluation methodologies for AI safety. The research spans theoretical frameworks like open-universe assistance games while addressing practical challenges in language model alignment and cultural bias assessment. Scientific awards include: AI2050 Early Career Fellowship from Schmidt Futures Berkeley Fellowship NSF Graduate Research Fellowship C.V. Ramamoorthy Distinguished Research Award His work bridges theoretical computer science with real-world AI governance challenges, as demonstrated through MIT's participation in AI policy white papers. Current research directions include developing frameworks for transparent AI systems and addressing fundamental limitations in aligning recommender systems with human values through interdisciplinary synthesis.
Dr. Abdullah Bal is a researcher at Georgia State University's College of Arts & Sciences, Department of Computer Science, with over 25 years of academic experience. He holds a Ph.D. in Electrical Engineering from Yildiz Technical University (2002) and has taught graduate and undergraduate courses in algorithms, machine learning, and optical pattern recognition. B.Sc., Electronics and Communication Engineering, Istanbul Technical University (1993) M.Sc., Electrical Engineering, Yildiz Technical University (1997) Ph.D., Electrical Engineering, Yildiz Technical University (2002) His research focuses on data science, machine learning, and hyperspectral imaging applications in fields ranging from forensic analysis to historical structure preservation. He has led projects funded by the U.S. Army Research Office and the Scientific and Technological Research Council of Turkey, including real-time target detection systems and digital imaging for historical structures. Recent publications demonstrate his expertise in kernel-based transforms, ensemble learning, and hyperspectral data analysis. His work spans food safety inspection, infrared target tracking, and biometric verification systems. Faculty Outstanding Research Publication Award (2006) Turkish Air Force Academy Science Competition Winner (2009) Best Paper Award at ICFCT (2016) Previously, he chaired YTU's Informatics Department (2009-2016) and participated in academic governance through the Electrical and Electronics College Executive Committee (2012-2015). You can contact him at abal@gsu.edu in room 739, 25 Park Place.
Tracey Galloway is an Associate Professor in the Department of Anthropology at the University of Toronto Mississauga (UTM), where she conducts critical research on Indigenous health disparities and policy interventions in northern Canada. Her work bridges medical anthropology, public health, and community-based participatory research to address systemic inequities affecting circumpolar populations. Education: PhD, McMaster University, 2008 MA (institution unspecified) BA (institution unspecified) BScN (institution unspecified) Dr. Galloway's research program centers on chronic disease risk assessment and health system improvement in Indigenous communities, with specific expertise in nutrition transition, food security, child growth patterns, and public health policy evaluation. She examines the impact of federal programs like Nutrition North Canada while developing community-led solutions for health equity. Her methodological approach combines quantitative analysis of health outcomes with qualitative community engagement, emphasizing Indigenous research sovereignty and decolonizing methodologies. Her publication record reveals consistent thematic focus across 15 recent articles, demonstrating interdisciplinary collaboration between anthropology, epidemiology, and health economics. Key trends include rigorous evaluation of colonial impacts on Indigenous food systems, innovative analysis of subsidy program effectiveness, and centering Indigenous patient experiences in healthcare design. Her work consistently prioritizes community-defined research questions and actionable policy recommendations. Dr. Galloway actively mentors graduate students including Darci Belmore, Carly Checholik, Neda Maki, and Hiliary Monteith, guiding research on Indigenous health determinants and policy interventions. While specific grant details aren't publicly enumerated, her collaborative projects involve partnerships with Indigenous communities across Northern Canada and interdisciplinary teams addressing complex health system challenges. She maintains strong community partnerships for her applied research, particularly in Nunavut and Northwestern Ontario, working directly with Anishinabeck and Inuit communities to translate findings into culturally safe health initiatives and policy reforms that address the root causes of health inequities.
Professor Amin Abbosh is a faculty member at the School of Electrical Engineering and Computer Science, University of Queensland. His research focuses on Medical Microwave Imaging and Millimeter-wave Engineering, with contributions to advanced imaging systems, antenna design, and communication technologies. He leads projects in electromagnetic medical sensing, including portable brain scanners and wearable diagnostic systems. His work integrates applied electromagnetics with AI-driven algorithms, addressing challenges in stroke detection, liver health monitoring, and deep vein thrombosis diagnosis. With over 16 patents and collaborations across biomedical and engineering domains, his research bridges clinical needs with cutting-edge electromagnetic techniques. Key projects include the development of low-cost healthcare monitoring systems and reconfigurable antennas for satellite communications. Research interests span medical imaging systems, antenna array design, and signal processing for healthcare applications. His team innovates in areas like phased arrays, dielectric property analysis, and non-invasive diagnostics. Recent advancements include synthetic microwave focusing techniques and self-supervised deep learning models for clutter removal in imaging. Publications highlight contributions in IEEE journals and conferences, emphasizing clinical applications and device prototyping. Collaborations with institutions like the University of Queensland’s medical faculty and industry partners ensure practical implementation of his research.
Christian Grönroos is Professor of Marketing at Hanken School of Economics, recognized among the top marketing researchers globally. His pioneering work established service marketing theory and the service logic paradigm. Research focuses on value co-creation frameworks, relationship marketing evolution, and service-driven business model innovation. Publications have transformed understanding of customer management and service productivity. Awards include the Don Schultz Award (2025) and AMS-Parasuraman Best Paper Award. Recent work examines service-informed marketing reform and employee alignment in brand promise co-creation.
Leslie Ann Goldberg is a Senior Research Fellow at St Edmund Hall and Professor of Computer Science at the University of Oxford. She currently serves as Head of the Department of Computer Science (on sabbatical 2025-26) and focuses on foundational problems in Algorithms and Complexity Theory , particularly randomised algorithms for network communication, machine learning, and statistical physics models. Her research includes solving Aldous' 1987 conjecture on backoff protocol instability (with John Lapinskas), developing rigorous mathematical analysis frameworks for algorithmic efficiency, and advancing approximate counting techniques via Markov Chain Monte Carlo methods (with Andreas Galanis and collaborators). Key projects involve graph homomorphisms , Moran process dynamics , and #BIS complexity class analysis. Recent publications (2023-2024) span topics like Sybil defense mechanisms, low-temperature sampling on random graphs, and parameterised subgraph counting modulo 2. Her work demonstrates cross-disciplinary impact in computational biology, statistical physics, and database theory. Scientific Awards include Best Paper Prizes at ICALP 2016, ICALP 2010, and IPEC 2017. She supervises PhD student Paulina Smolarova and collaborates extensively with researchers in Oxford and beyond.
Conor Ryan is a Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a Science Foundation Ireland-funded Investigator since 2002 and a member of multiple research centres including Lero – the Irish Software Research Centre and the Limerick Digital Cancer Research Centre. His research focuses on Genetic Programming, Grammatical Evolution, and their applications in domains like healthcare analytics, digital circuit design, and financial modeling. He has authored over 250 publications, with recent work emphasizing automated feature selection in medical diagnostics, neural architecture search, and blockchain ecosystems. Teaching includes courses on Foundations of Computer Science and Computer Games Programming. Research interests span evolutionary computation, machine learning, and interdisciplinary applications. Collaborations involve global institutions, reflecting his work's impact across computer science, engineering, and healthcare. His research has addressed challenges in breast cancer diagnosis via genetic algorithms, cryptocurrency volatility prediction using random forests, and automated generation of digital circuits. Ongoing projects explore interpretability in AI, energy-efficient computing, and sustainable transport systems through predictive analytics. Professional memberships include roles in the Centre for Research Training in Foundations of Data Science and the Data-Driven Computer Engineering Research Centre, underscoring his commitment to interdisciplinary innovation.
Xiang Ji is an Assistant Professor in the Department of Mathematics at Tulane University, affiliated with the School of Science & Engineering. His research focuses on statistical phylogenetics, computational biology, and bioinformatics, particularly in viral evolution and genomic epidemiology. He collaborates with Dr. Wu-Min Deng on cancer biology research from a bioinformatics perspective. Education: Ph.D., 2017: Bioinformatics and Statistics (Co-Major), North Carolina State University M.S., 2013: Material Science and Engineering, North Carolina State University B.S., 2011: Economics (Double Major) and Physics, Peking University Research Interests: Dr. Ji develops statistical models and computational tools for phylogenetic analysis, including scalable algorithms for large-scale genomic data. His work spans viral evolution, zoonotic disease surveillance, and parallel computing libraries for Bayesian inference. He emphasizes practical implementations such as Torchtree and TreeFlow . Articles Trends: Recent publications emphasize viral evolution dynamics (e.g., SARS-CoV-2, avian influenza), genomic surveillance strategies, and computational methods for phylogenetic inference. His work often bridges statistical theory with real-world applications in public health and epidemiology. Advising & Grants: While specific grant details are not listed, his active research program indicates involvement in funding initiatives related to computational biology and viral evolution. He teaches advanced courses in data analysis, linear models, and probability theory. Labs & Teams: Collaborates with Tulane’s Cancer Biology group and maintains partnerships with institutions globally, focusing on genomic epidemiology and phylogenetic software development.
Xiuwei Zhang is the J.Z. Liang Early-Career Assistant Professor in the School of Computational Science and Engineering (SCoSE) at Georgia Institute of Technology, part of the College of Computing. Her research focuses on computational biology and bioinformatics, particularly in developing machine learning methods for analyzing single-cell omics data, including multi-modal, temporal, and spatial data integration. She leads a lab that designs tools like scDART , scMoMaT , and scMultiSim , which address challenges in multi-omics integration, lineage reconstruction, and simulation. Before joining Georgia Tech, she held postdoctoral positions at UC Berkeley (Nir Yosef’s group), the European Bioinformatics Institute (EBI), and École Polytechnique Fédérale de Lausanne (EPFL). She earned her PhD in computer science from EPFL under Bernard Moret. Her Erdős number is 3, reflecting her collaborative work across computational fields. Her research spans four key areas: multi-batch/single-cell data integration, temporal analysis of cell differentiation, spatial-temporal omics dynamics, and simulation tools for benchmarking methods. She has received prestigious awards, including the NSF CAREER Award (2022) and NIH MIRA (2021). She actively participates in conferences (RECOMB, ISMB) and serves on editorial boards (Journal of Computational Biology). Her group’s recent work includes the scMultiSim simulator (2025), which generates multi-omics spatial data, and LinRace (2023), reconstructing cell lineage histories. She mentors over 15 students and collaborates internationally on projects like the InQuBATE Workshop on Single-Cell Transcriptomics.
