Juho Härkönen is Professor of Sociology, Dean of Postdoctoral Studies, and Director of the Max Weber Program for Postdoctoral Studies at the European University Institute (EUI). He earned his PhD from the EUI in 2007, held a postdoctoral position at Yale, and was based in Stockholm from 2009. He served as visiting professor at the University of Turku (2010-2018). Current Affiliation: European University Institute Roles: Professor of Sociology, Dean of Postdoctoral Studies, Director of Max Weber Program His research focuses on life course research, family dynamics, social stratification, and health. Recent work examines divorce outcomes, health disparities, and educational inequality. He primarily uses quantitative methods but supports qualitative approaches. Juho Härkönen co-directs the Comparative Life Course and Inequality Research Center and Florence Population Studies at EUI, and serves as editor-in-chief of Advances in Life Course Research . His recent publications analyze parental separation’s impact on education and the life course consequences of the COVID-19 pandemic.
Mary A. Carskadon is Professor of Psychiatry and Human Behavior at Brown University's Warren Alpert Medical School and Director of the EP Bradley Hospital COBRE Center for Sleep and Circadian Rhythms in Child and Adolescent Mental Health. Her distinguished career spans over five decades with foundational contributions to sleep science. Her educational background includes a BA in psychology from Gettysburg College (1969) and a doctorate with distinction in neuro- and biobehavioral sciences from Stanford University (1979), earned under William C. Dement. She is a distinguished alumna of Gettysburg College and holds an honorary doctor of sciences degree from that institution. Carskadon's research focuses on circadian timing systems and sleep/wake patterns in children, adolescents, and young adults. Her work on school start times has significantly influenced public health policy, prompting organizations like the American Academy of Pediatrics and CDC to advocate for later school schedules. She developed the multiple sleep latency test (MSLT) with Dr. Dement, which remains a global standard for assessing sleep disorders. Current research examines sleep-health disparities in urban children with asthma, sleep patterns in suicide risk populations, and the impact of sleep restriction on adolescent performance. Her extensive publication record shows consistent focus on adolescent sleep physiology, circadian rhythms, and public health implications. Recent work explores connections between sleep timing, mental health, and academic performance, particularly during the COVID-19 pandemic, while maintaining her foundational work on sleep measurement methodologies. Lifetime Achievement Award of the National Sleep Foundation Distinguished Scientist and Outstanding Educator Awards of the Sleep Research Society (the latter now presented in her name) 2023 Brown University Distinguished Research Achievement Award William C. Dement Academic Achievement Award (2023) V. Sagar Sethi, M.D., Mental Health Research Award Leadership in Sleep Medicine Award from American Academy of Physicians of Indian Origin-Sleep Elected Fellow of the Association for Psychological Science Elected Fellow of the American Association for the Advancement of Science Carskadon directs the NIH/NIGMS-funded Bradley Hospital COBRE Center, mentoring junior researchers in pediatric sleep and circadian rhythms. She serves as inaugural editor-in-chief of SLEEP Advances and has secured multiple NIH grants including R01 HL142058 examining ethnic differences in children's sleep patterns with asthma, P20 GM139743 for the COBRE center, and R01 HD103665 investigating sleep restriction effects using neuroimaging. Her work bridges laboratory research with real-world applications, particularly in school policy reform and health equity initiatives. She leads multiple research teams including the CLASS Study (Circadian Light in Adolescence, Sleep and School), projects on sleep disruption in urban children with asthma, and studies examining sleep's role in opioid use disorder treatment. Her laboratory continues to innovate in sleep measurement techniques while maintaining longitudinal studies on adolescent sleep patterns across developmental stages.
David H Laidlaw is a Professor of Computer Science at Brown University, specializing in virtual reality, scientific visualization, and medical imaging. His work spans interdisciplinary applications in neuroscience, biomedical research, and educational tools. Brown University Affiliation Department of Computer Science His research focuses on: Immersive visualization for complex data analysis Diffusion MRI and neuroimaging techniques Human-computer interaction in virtual environments 3D interaction methods for scientific exploration Collaborative visualization tools for multidisciplinary teams Recent trends in his publications highlight advancements in: Graph neural networks for biomedical data Memory-efficient segmentation algorithms Perceptual studies in VR environments Annotation and analysis of placental vasculature Technological innovations in foot dynamics research He teaches courses in virtual reality design and scientific visualization, including: CSCI 1370 - Virtual Reality Design for Science CSCI 1951S - Virtual Reality Software Review CSCI 1951T - Surveying VR Data Visualization Software CSCI 2370 - Interdisciplinary Scientific Visualization
Anne G Hoen is an Associate Professor at the Geisel School of Medicine , Dartmouth College, with joint appointments in Epidemiology , Biomedical Data Science , and Microbiology and Immunology . Her research focuses on microbiome development in infants, environmental exposures, and their associations with health outcomes, using interdisciplinary approaches including statistical modeling and bioinformatics. Research Interests: She explores how microbial communities in early life influence disease risk through environmental and dietary factors. Her work integrates microbiome-metabolome interactions, computational methods for microbial network analysis, and epidemiological studies of infectious diseases. Recent Article Trends: 2025-2024 publications highlight maternal diet-microbiome links, microbial interaction networks, ECHO consortium collaborations, and novel computational approaches for microbiome data. Key sub-fields include perinatal exposome, microRNA profiling, and longitudinal metabolomic analysis. Scientific Awards: K01LM011985: Bioinformatics strategies for early life microbiomics R01LM012723: Multi-omic functional integration using networks Advising: Mentors current PhD students in Dartmouth's Quantitative Biomedical Sciences (QBS) program, including Becky Lebeaux and Quang Nguyen, while alumni like Sara Lundgren and Wes Viles hold postdoctoral and academic positions.
Alistair McCulloch is a Professor in the Learning and Teaching Unit at the University of South Australia, with significant expertise in doctoral education and research supervision. Previously, he served as Professor and Dean of Research and Knowledge Transfer at Edge Hill University near Liverpool for over 12 years, where he was responsible for the development and quality of the university's research degree programs. His primary research interests focus on doctoral education, PhD supervision, and graduate education, with particular attention to the experiences of part-time doctoral students, especially working mothers. McCulloch's work explores sociocultural transitions in doctoral education, the role of oral examinations (vivas), and the concept of serendipity in research. His research demonstrates a consistent concern with the wellbeing of doctoral students and the structural factors that affect their success. McCulloch's publication record shows a clear evolution from early work in political history (notably his 1979 thesis on the 1910 UK General Election) toward contemporary issues in higher education. His recent work (2022-2025) focuses on critical issues in doctoral education including student wellbeing, supervisor-student relationships, and assessment practices. He has been particularly active in examining the experiences of marginalized doctoral student populations and has contributed significantly to the literature on part-time doctoral study. As an academic leader, McCulloch has been involved with the Quality in Postgraduate Research (QPR) conference series held in Adelaide, South Australia, which brings together international scholars interested in doctoral education. His work bridges theoretical perspectives (including Marxist theory on work and alienation) with practical concerns in doctoral program design and implementation.
Rachel N Clark is a Lecturer in the School of Physics at the University of Bristol, actively contributing to the Quantum Engineering Technologies research group with a focus on quantum photonics and quantum light source development. Education: Master of Physics (MPhys) Master of Science (MSc) Doctor of Philosophy (PhD) Her research spans Quantum Engineering , Quantum Optics , and Photonics with concentrated expertise in solid-state quantum emitters—particularly aluminum nitride color centers—and single photon source engineering. Key investigations include evanescent-field photon collection enhancement, room-temperature quantum emitter characterization, and nanofabrication of quantum photonic devices for improved efficiency and integration. Analysis of her 13 publications (2022-2025) reveals dominant trends in aluminum nitride quantum emitter development, with 60% of works addressing room-temperature quantum light sources and photon collection efficiency. Her research bridges fundamental quantum optics with practical quantum technology applications, emphasizing scalable fabrication methods and metrology standards for quantum photonic systems. No scientific awards were documented in the provided materials. Information regarding graduate students, research grants, or specific laboratory teams beyond her Quantum Engineering Technologies affiliation was not indicated in the source texts.
Andrei Khrennikov is Professor of Mathematics at the Department of Mathematics, Linnaeus University, where he also serves as director of the International Center for Mathematical Modeling (ICMM) . He leads a vibrant research group focused on interdisciplinary modeling in physics, biology, cognition, and social systems. Research Interests: His work spans a vast interdisciplinary landscape, including mathematical physics, p-adic and non-Archimedean analysis, quantum foundations, quantum-like modeling of cognition and decision-making, econophysics, and biological dynamics . He is a pioneer in applying quantum probability and formalism outside quantum physics, especially in psychology and social sciences. The Växjö series of quantum theory conferences , which he organizes, is the longest-running continuous conference series on quantum foundations, fostering dialogue between theorists, experimentalists, and philosophers. His recent publications (2021–2025) show a strong focus on quantum cognition, p-adic biology, entanglement models, and social laser theory , often leveraging generalized probability and open quantum systems frameworks. Scientific Contributions: Developed quantum-like models for cognition, decision-making, and biological processes. Pioneered use of p-adic and ultrametric analysis in genetics and brain dynamics. Advanced classical random field models as alternatives to quantum interpretations. Introduced the social laser model for collective emotional amplification in societies. He is actively involved in major research projects such as QUARTZ (Quantum Information Access and Retrieval Theory) and DYNALIFE (Information, Coding, and Biological Function) . His work bridges mathematics, physics, and cognitive science, promoting a unified framework for understanding complex systems through quantum-inspired tools.
Yang Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at the Baskin School of Engineering, University of California, Santa Cruz. Previously, they were affiliated with Harvard University and earned their PhD in 2015 from the Department of EECS at the University of Michigan, Ann Arbor. Their research lies at the intersection of machine learning, fairness, and trustworthy AI, with a strong focus on large language models, federated learning, and causal reasoning. Their research interests include: Machine Learning and Fairness Federated and Privacy-Preserving Learning Large Language Model Safety and Unlearning Causal Inference and Counterfactual Reasoning Anomaly Detection and Robust Forecasting Human-AI Interaction and Ethical AI Recent publications (2024–2025) demonstrate a strong trend in developing methods for machine unlearning, fairness in LLMs, and robustness under label noise and distribution shifts. Their work frequently appears in top-tier venues such as NeurIPS, ICLR, ICML, AAAI, and KDD, often in collaboration with researchers like Zhaowei Zhu, Mingyan Liu, Jiaheng Wei, and Kun Zhang. Themes include algorithmic fairness, model accountability, and human-aligned AI systems. Scientific contributions include: Frameworks for LLM unlearning and model editing Methods for fair classification and recourse Robust time series forecasting under anomalies Test-time adaptation in multimodal models Causal approaches to debiasing and policy learning While no formal advising list is provided, the depth and volume of collaborative work suggest active mentorship of graduate students and postdocs. Their research program is highly active, with numerous ongoing projects in trustworthy and socially responsible AI.
Dr. Patrick S. Market is a Professor of Atmospheric Science and currently serves as the Director of the School of Natural Resources at the University of Missouri. He also acts as Interim Co-Director of the Missouri Water Center. His research focuses on synoptic and mesoscale dynamics, particularly winter weather, heavy rainfall, flash flooding, and severe local storms. He has contributed to advancements in precipitation efficiency studies and operational forecasting techniques. His work explores the role of artificial intelligence in weather prediction and communication, emphasizing the continued importance of human expertise in an automated forecast process. Dr. Market has secured grants for data stream maintenance and digital equity planning, and he has led educational initiatives integrating research into synoptic meteorology classrooms. Notable collaborations include projects with the National Weather Service and studies on the Ozark Plateau's topographical influence on weather systems.
Antonio Simonetti is an Associate Professor at the University of Notre Dame in the Civil & Environmental Engineering & Earth Sciences department, affiliated with the College of Engineering. He leads the Isotope Geochemistry Laboratory and MITERAC facility, focusing on nuclear forensics, geochronology, and isotope geochemistry. His research spans high spatial resolution analysis of Earth materials, lunar studies, and bioarchaeological mobility tracing. Ph.D., Carleton University (1994) M.S., McGill University (1989) B.S., McGill University (1986) Research interests include: Nuclear Forensics: Developing microanalytical techniques for post-detonation materials and source attribution. Geochronology: Dating igneous and biogenic materials using U-Pb and other isotopic systems. Isotope Geochemistry: Investigating mantle-derived carbonatites and environmental pollution tracing. Bioarchaeology: Using Sr, Nd, Pb isotopes to study ancient human migration in Nubia and the Nile Valley. Recent trends in his publications highlight interdisciplinary applications of isotopic analysis across nuclear materials, lunar science, and archaeological studies. His group employs LA-MC-ICP-MS for high-resolution chemical and isotopic mapping. Students and collaborators span graduate, undergraduate, and international PhD candidates, with projects on uranium isotope signatures, carbonatite petrogenesis, and isotopic tracing of ancient civilizations. Current students include Julia Rufener (lunar KREEP analysis), Jiahua Wu (nuclear fuel cycle signatures), and Bennett Schmitt (REE mineralization in carbonatites). Labs and teams: Directs the Isotope Geochemistry Laboratory and MITERAC facility, supporting advanced ICP-MS and laser ablation analyses. Collaborates with institutions in Brazil, Turkey, China, and Ireland on geological and archaeological projects.
Professor Charlotte Kloft is Head of the Department of Clinical Pharmacy & Biochemistry at the Institute of Pharmacy, Free University of Berlin since 2011, and spokesperson for the interdisciplinary Graduate Research Training Program PharMetrX 'Pharmacometrics and Computational Disease Modelling' since 2008. She previously served as Professor and Head of the Department of Clinical Pharmacy at Martin-Luther-University Halle-Wittenberg (2005-2011) and as Scientific Assistant/Senior Assistant at Freie Universität Berlin (1999-2005). Her academic credentials include a habilitation in Clinical Pharmacy from Freie Universität Berlin (2003) and a Dr. rer. nat. (summa cum laude) from the same institution (1997). She earned her license as a pharmacist in 1992 after completing pharmacy studies at Johannes Gutenberg-University, Mainz (1987-1991). Professor Kloft's research focuses on pharmacometrics, computational disease modeling, and therapeutic drug monitoring across multiple therapeutic areas. Her work bridges pharmaceutical sciences with clinical practice, with particular emphasis on personalized dosing strategies for oncology, antimicrobial resistance, and inflammatory bowel diseases. She has pioneered research in optimizing drug dosing through pharmacokinetic/pharmacodynamic modeling, with applications in both antibiotic and cancer therapies. Her recent publications demonstrate a strong evolution toward integrating advanced computational approaches with clinical pharmacology, including machine learning applications in pharmacometrics, personalized dosing strategies for biologics during pregnancy, and developing nationwide infrastructure for therapeutic drug monitoring in cancer therapy through the ON-TARGET study. Academic Center of Excellence of Pharsight (now Certara), USA (since 2000) Habilitationsreisestipendium of Dr. August and Dr. Anni Lesmüller-Stiftung (2002) Ernst-Reuter-Preis of Ernst-Reuter-Gesellschaft (1998) Joachim-Tiburtius-Preis of Berlin Senate (1998) Young Investigator Award of EORTC-PAMM (1997) Professor Kloft has successfully supervised numerous doctoral students whose research spans diverse areas including CAR-T cell therapy, antimicrobial resistance, inflammatory bowel disease treatment optimization, and pharmacokinetic modeling of novel therapeutic agents. Her research group has secured significant funding for projects including GlobalResist, ON-TARGET, ABIMMUNE, COMBINATORIALS, and TAIN. She leads a vibrant research ecosystem at the Free University of Berlin with strong collaborations across Europe and internationally, maintaining state-of-the-art laboratory facilities including Biosafety Level 2 certified labs for infectious disease research.
Roderich Gross is a Senior Lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield. He is also a Visiting Scientist at CSAIL, MIT, and leads the Enabling Technologies theme at Sheffield Robotics. His academic journey includes a Ph.D. in engineering science from Université libre de Bruxelles (2007), followed by postdoctoral fellowships as a JSPS Fellow (Tokyo Institute of Technology), Research Associate (University of Bristol), and Marie Curie Fellow (EPFL & Unilever). Research Interests : Swarm robotics, self-reconfigurable robots, multi-robot coordination, robotics software/tools (human-robot interaction interfaces, formal design tools), machine learning for behavior inference (Turing Learning, GANs), autonomous systems, natural computing (swarm intelligence, evolutionary algorithms). Scientific Contributions : Inventor of Turing Learning, a machine learning method for behavior inference. Key work includes swarm coordination, self-assembly, fault-tolerant quadcopters, energy-efficient drone delivery, and infrared-based swarm communication. Scientific Recognition : Held prestigious fellowships including JSPS and Marie Curie, and served as Associate Editor for leading robotics journals (IEEE Robotics and Automation Letters, Swarm Intelligence) and conference roles (General Chair DARS 2016, Program Co-Chair GECCO 2018). Grants : Principal Investigator on Horizon Europe OpenSwarm (£463,699), EPSRC Core Capital (£104,196), DSTL Multi Robot Systems (£98,781), and industry-funded modular robotics projects. Labs : Affiliated with the Natural Robotics Lab at the University of Sheffield.
Xuhui Lee is the Sara Shallenberger Brown Professor of Climate Science at Yale University's School of the Environment. He maintains offices at Kroon Hall (195 Prospect Street) and laboratory facilities at the Class of 1954 Environmental Science Center (21 Sachem Street, Room 300) in New Haven, Connecticut. Professor Lee is an active researcher and educator specializing in the interactions between the terrestrial biosphere, atmosphere, and anthropogenic drivers, with particular expertise in boundary-layer meteorology and climate science. He is currently on leave for the Fall 2025 semester but continues to accept doctoral students. Professor Lee received his B.S.C. and M.S.C. from Nanjing Institute of Meteorology in China, followed by a Ph.D. from the University of British Columbia. His academic journey has positioned him as a leading expert in climate science, particularly in the areas of land-atmosphere interactions and urban climate systems. Professor Lee's research focuses on boundary-layer meteorology, micrometeorological instrumentation, remote sensing, and carbon cycle science. His work examines biophysical effects of land use on the climate system, greenhouse gas fluxes in terrestrial environments (including forests, cropland, and lakes), isotopic tracers in carbon dioxide and water vapor cycling, and urban climate adaptation and mitigation strategies. His lab employs diverse methodologies including field observations (eddy covariance, optical isotope instruments, and greenhouse gas analyzers), mathematical models (land surface models, large-eddy simulation, WRF, and earth system models), and environmental remote sensing (satellites and drones). The Lee Lab investigates phenomena across multiple scales from micro (urban greenspaces) to global (land wet-bulb temperature, historical deforestation). Analysis of Professor Lee's recent publications reveals a strong focus on urban climate systems, greenhouse gas emissions, and land-atmosphere interactions. His 2024-2025 work demonstrates increasing application of advanced remote sensing technologies and machine learning approaches to climate problems, with significant attention to urban heat islands, methane and CO2 emissions monitoring, and the impacts of land use change on climate systems. His research shows a clear trajectory toward more sophisticated integration of observational data with modeling approaches to address critical climate challenges. Sara Shallenberger Brown Professor of Climate Science (named professorship) Professor Lee actively mentors doctoral students and has established the Lee Lab as a hub for climate research at Yale. His lab group conducts field observations, mathematical modeling, and remote sensing analysis to advance understanding of climate systems. The lab's research infrastructure supports investigations from micro-scale urban environments to global climate patterns, with particular emphasis on urban heat mitigation and greenhouse gas monitoring. The Lee Lab at Yale, located in Room 300 of the Class of 1954 Environmental Science Center, serves as the primary research facility for Professor Lee's team. The lab deploys an array of research methodologies including field observations with eddy covariance systems and optical isotope instruments, mathematical modeling using land surface models and earth system models, and environmental remote sensing with satellites and drones. The lab's research spans multiple spatial scales from micro (urban greenspaces) to global (land wet-bulb temperature patterns), addressing critical questions about climate change impacts and mitigation strategies.
Tamara Drucks is a PreDoc Researcher at the Department of Machine Learning, Technische Universität Wien. She specializes in machine learning, with a focus on graph neural networks, bioinformatics, and optimization algorithms. Drucks teaches courses including 'Introduction to Machine Learning' and 'Theoretical Foundations and Research Topics in Machine Learning.' Her research explores expressive power of graph networks and applications in phylogenetic modeling. Key projects include the StruDL initiative (2023–2027) focusing on maximally expressive GNNs for outerplanar graphs. She has advised one PhD student, Martin Plattner, on optimization techniques in machine learning. Publications span theoretical advancements in GNNs and practical applications in computational biology. Drucks holds a Diploma in Technical Mathematics from TU Wien (2021) and is involved in interdisciplinary research at the intersection of AI and biological data analysis.
Bob Kopp is a Professor at Rutgers University's Department of Earth & Planetary Sciences and Co-Director of the University Office of Climate Action. He leads the NSF-funded Megalopolitan Coastal Transformation Hub (MACH), focusing on climate risk management in the Northeast U.S. and advancing understanding of coastal climate interactions. He co-directs the Climate Impact Lab, a multidisciplinary collaboration assessing climate economic risks. His research spans climate uncertainty, sea-level dynamics, and climate policy, with leadership roles in IPCC assessments and U.S. National Climate Assessments. Education: Ph.D. in Geobiology from Caltech (2000s) and B.S. in Geophysical Sciences from the University of Chicago. Prior to Rutgers, he served as AAAS Science & Technology Policy Fellow at the U.S. Department of Energy and postdoctoral researcher at Princeton University. Affiliations include Rutgers Climate Institute, Energy Institute, and graduate programs in Atmospheric Sciences, Geological Sciences, Oceanography, Statistics, and Planning & Public Policy. Research interests emphasize climate change impacts, sea-level projections, and policy integration. Key contributions include frameworks for probabilistic sea-level assessments (e.g., PaleoSTeHM) and adaptive strategies for coastal resilience. His work bridges scientific analysis with actionable policy, emphasizing stakeholder engagement in megaregions like the New York–Philadelphia urban corridor. Grants include NSF-funded projects totaling millions, supporting interdisciplinary climate solutions. Awards: Not explicitly listed, but recognized for leadership in IPCC and U.S. climate reports. Grants: Includes NSF support for MACH and Climate Impact Lab. Labs/Teams: Directs MACH, Climate Impact Lab, and collaborates with Rutgers' EOAS and Climate Institute.
