Yee Whye Teh is a Professor at the Department of Statistics, University of Oxford, and a research scientist at DeepMind. His work focuses on statistical machine learning, including probabilistic learning, Bayesian nonparametrics, deep learning, and Monte Carlo methods. He co-directs the ELLIS programme on Robust Machine Learning and has held roles such as Programme Co-chair for ICML 2017. Teh has delivered keynotes at UAI 2019, an IMS Medallion Lecture at JSM 2019, and the Breiman Lecture in 2017. His research emphasizes scalable inference algorithms, hierarchical models, and applications in genetics and natural language processing. Teh's educational background includes a PhD from the University of Toronto (2003) and a Master's from the same institution (2000). He has contributed to widely used software tools like the Sequence Memoizer and has been recognized for his work through prestigious lectureships. Research interests span Bayesian nonparametric models, MCMC methods, and their applications in genetics and data compression. His lab collaborates on projects like fragmentation-coagulation processes for genetic variation modeling and Mondrian forests for online learning. Teh advises students through Oxford's graduate programs, though he notes high demand for mentorship. His work often bridges theory and practice, addressing challenges in big data learning and small data problems.
Prof. Walter Leal Filho is a distinguished academic and researcher holding professorial positions at Hamburg University of Applied Sciences (Germany) and Manchester Metropolitan University (UK). He is the founding director of the European School of Sustainability Science and Research (ESSSR) and the Inter-University Sustainable Development Research Programme (IUSDRP). With over 30 years of editorial experience, he has authored over 500 publications, focusing on sustainability, climate change, and environmental management. His research interests span Climate Change, Urban Resilience, Natural Resource Management, and Sustainability Education. He emphasizes interdisciplinary approaches to address global challenges, such as space debris mitigation and bio-based materials for sustainable packaging. His work bridges policy, education, and practical solutions for sustainable development. Prof. Leal Filho’s recent articles highlight trends in sustainable urban planning, space sustainability, and ecosystem conservation in the Amazon. He has been recognized as a Top Cited Scholar 2024, reflecting his impactful contributions. With 1,200+ co-authors and a global network, he collaborates widely, fostering international research and education initiatives. As director of ESSSR and IUSDRP, he leads programs advancing sustainability science and interdisciplinary research. His academic leadership and prolific publications underscore his role as a pivotal figure in global sustainability efforts.
Peter Bühlmann is a Professor at ETH Zürich within the Seminar für Statistik , focusing on high-dimensional statistics, causal inference, and machine learning. His work bridges theoretical advancements with practical software implementations in R packages like pcalg , mboost , and glmmlasso , impacting fields such as genomics, proteomics, and intensive care analytics. Key Contributions : Causal structure learning, stability selection, anchor regression, and deconfounding. Software : Developed widely used R packages for statistical modeling and causal inference. Teaching : Courses on high-dimensional statistics at ETH Zürich and international institutions. Research Trends : Recent articles emphasize causal robustness, domain adaptation, and applications in medicine. His work addresses challenges in heterogeneous data, missing values, and covariate shifts using methods like spectral deconfounding and residual prediction tests. Scientific Recognition : Co-author of a paper designated as a New Hot Paper (Meinshausen and Bühlmann, 2006) by Essential Science Indicators, indicating significant impact in high-dimensional multiple testing.
Dr. Amin Keramati is an Assistant Professor of Supply Chain Management at Widener University’s School of Business Administration. He holds a PhD in Transportation & Logistics from North Dakota State University and previously served as a graduate research assistant at the Upper Great Plains Transportation Institute. His work includes federally funded projects like the Mountain-Plains Consortium’s MPC-550 project, focusing on highway-rail grade crossing safety. Dr. Keramati teaches courses in enterprise resource planning, decision analytics, database management, transportation/logistics, project management, and data analytics. Education: PhD in Transportation & Logistics, North Dakota State University Graduate Research Assistant at Upper Great Plains Transportation Institute Research Focus: Dr. Keramati develops mathematical, statistical, and machine learning approaches to solve complex problems in transportation, supply chain, and logistics. Key areas include data mining, big data decision support, transportation network analytics, project scheduling, smart manufacturing, and accident analysis. His interdisciplinary work bridges supply chain optimization with emerging technologies like blockchain for healthcare and clinical trials. Awards & Recognition: Student Paper Award, American Association of State Highway and Transportation Officials (2017) Grants & Projects: Lead researcher on the Mountain-Plains Consortium’s MPC-550 project, which expanded his dissertation work on safety systems for highway-rail crossings. Collaborates on federally funded transportation safety initiatives and supply chain optimization for bioethanol and pharmaceutical industries. Labs/Teams: Active in Widener’s School of Business research groups focusing on supply chain innovation and interdisciplinary projects combining logistics with emerging technologies.
Prof. Stefan Leutenegger is a tenure-track Assistant Professor at Technische Universität München (TUM), leading the Machine Learning for Robotics group within the TUM School of Computation, Information, and Technology. Previously, he held roles as Senior Lecturer (2018–2021) and Lecturer (2014–2018) at Imperial College London's Dyson Robotics Lab, where he founded the Smart Robotics Lab. He earned his PhD (2014) from ETH Zurich, focusing on autonomous solar-powered aircraft navigation, and holds BSc (2006) and MSc (2009) in Mechanical Engineering from ETH Zurich. His research centers on mobile robotics, particularly enabling robots (e.g., drones) to perceive and navigate complex environments using machine learning and sensor data fusion. Key focus areas include SLAM, event-based vision, 3D reconstruction, and autonomous exploration. He has pioneered algorithms like BRISK (2011), OKVIS (2014), and ElasticFusion (2016), advancing real-time robotics perception. Notable Awards: Imperial College President's Award (2018), Best ECCV Paper (2016), ETH Medal for Dissertations (2015). Labs: TUM's Machine Learning for Robotics Group, Imperial's Smart Robotics Lab. Publications: Over 100 papers, including seminal works in CVPR, ECCV, and Robotics: Science and Systems. Current projects include DigiForests (forest inventory via robotics), aerial additive manufacturing, and object-centric semantic mapping. His work bridges theory and practice, with applications in autonomous drones, construction robotics, and human-robot interaction.
Jun Hyung Lee is a Visiting Assistant Professor in the Department of Environmental Biology at SUNY College of Environmental Science and Forestry (ESF). His research focuses on advancing forest tree improvement and conservation through molecular and synthetic biology approaches, with a particular emphasis on enhancing plant resilience to environmental stresses via beneficial microbial interactions. He teaches courses in plant biotechnology and tissue culture methods. Education includes a Ph.D. in Forest Genetics from Purdue University (USA), and M.S. and B.S. degrees in Plant Science from Seoul National University (South Korea). His work integrates cutting-edge genetic engineering techniques with ecological studies to address challenges in plant stress tolerance, symbiosis, and epigenetic regulation. Recent projects include identifying novel symbiosis pathways for thermotolerance and analyzing flooding tolerance in hybrid poplars. Publications highlight contributions to plant-microbe interaction research, synthetic biology applications, and genome editing epigenetic impacts. Collaborations span institutions like Oak Ridge National Laboratory and the University of Georgia, reflecting his transdisciplinary approach to plant science. Lee’s teaching emphasizes practical skills in biotechnology, bridging laboratory innovation with field applications.
Prof. Dr. Ana Bastos is a Research Professor and Group Leader at the Max Planck Institute for Biogeochemistry (MPI-BGC) in Germany, affiliated with Leipzig University's Institute for Earth System Science and Remote Sensing. She holds a PhD in Geophysical and Geoinformation Science (2015, U. Lisbon) and a BSc+MSc in Environment and Energy Engineering (2011, U. Lisbon). Her research bridges atmospheric science, ecology, and biogeochemistry to study carbon-cycle dynamics, climate extremes, and ecosystem disturbances. She leads major projects such as the ERC Starting Grant-funded ForExD initiative and contributes to global carbon cycle assessments like RECCAP-2. Key roles include membership in the World Climate Research Programme's Safe Landing Climates initiative and leadership in the ICOS-RI Drought Task Force. She has over 40 international conference presentations and organizes sessions at AGU and EGU meetings. Her awards include the EGU Outstanding Early Career Scientist Award (2022) and the Beutenberg Campus Award (2021). She actively mentors early-career researchers through PhD and postdoc programs focused on forest disturbance modeling and remote sensing applications.
Michael A Osborne is Professor of Machine Learning at the University of Oxford and leads the Bayesian Exploration Lab . He serves as Director of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems and co-directs the Oxford Martin AI Governance Initiative. His research focuses on Bayesian optimization, Gaussian processes, and probabilistic numerics with applications in quantum devices, battery modeling, and AI governance. Key Positions: Professor of Machine Learning, University of Oxford Official Fellow, Exeter College Co-founder of Mind Foundry Lead Researcher, Oxford Martin Programme on Technology and Employment Research Themes: Probabilistic modeling for quantum systems Uncertainty quantification in energy storage AI safety and societal impact analysis Automated experimental design Quantum device calibration Probabilistic numerical methods Technical Contributions: Bridging reality gap in quantum devices Efficient Bayesian quadrature techniques Personalized neurostimulation algorithms Automated measurement protocols Quantum-classical hybrid ML
John Holmes is Professor of Victorian Literature and Culture at the University of Birmingham, affiliated with the Birmingham Institute of Forest Research (BIFoR). His work bridges literary studies and scientific inquiry, focusing on interdisciplinary connections from 1800 to the present through extensive collaborations with institutions like the Royal Society and major natural history museums across Europe. His academic credentials include a D.Phil. in English Literature from Oxford (2001), an M.A. in Renaissance Studies from Queen Mary and Westfield College, London (1997), and a B.A. in English Language and Literature from Oxford (1994). D.Phil. English Literature, University of Oxford, 2001 M.A. Renaissance Studies, Queen Mary and Westfield College, University of London, 1997 B.A. English Language and Literature, University of Oxford, 1994 Professor Holmes specializes in literature-science intersections, particularly Victorian and modern poetry, Pre-Raphaelite studies, and natural history museums. His current research examines arts architecture within museum spaces and mythic literature's dialogue with evolutionary science. He has authored foundational works on Darwinism in poetry and Pre-Raphaelite scientific engagements while directing major collaborative projects with scientific institutions. Recent publications reveal consistent exploration of poetic form within scientific contexts, with growing emphasis on digital humanities applications and environmental education. His 2023-2024 outputs demonstrate expanded interdisciplinary scope, integrating virtual reality tools for forest education and deepening analysis of myth-science intersections in canonical poetic works. His distinguished honors include: AHRC Collaborative Doctoral Award (2011) British Society for Literature and Science Book Prize (2018) Chair of the British Society for Literature and Science (2012) Honorary Associate of Oxford University Museum of Natural History (2016) President of the Commission on Science and Literature (2023) Professor Holmes leads significant research initiatives including the AHRC-funded Interdisciplinary Forest Education project (2024) and the long-term 'Building the Book of Nature' study (2015-2023). As an active PhD supervisor, he mentors students in literature-science intersections while maintaining robust public engagement through museum collaborations, media appearances, and educational outreach programs that translate academic research for broader audiences. He directs BIFoR-affiliated initiatives connecting literary scholarship with forest research, partnering with natural history museums in Oxford, London, Berlin, and Vienna to develop interdisciplinary frameworks examining how literary traditions shape environmental understanding and scientific communication.
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Ronald McGarvey is a Full Professor at IÉSEG School of Management since 2022, with prior roles including Associate Professor with Tenure at the University of Missouri (2013-2022) and Senior Operations Researcher at RAND Corporation (2002-2022). He holds a Ph.D. in Industrial Engineering and Operations Research from Pennsylvania State University and an H.D.R. in Industrial Engineering from the University of Paul Sabatier, France. Education : H.D.R. (2024), Industrial Engineering, University of Paul Sabatier Ph.D. (2002), Industrial Engineering and Operations Research, Pennsylvania State University His research focuses on Operations Research and Robust Optimization applied to diverse domains: Healthcare Logistics : Modeling access disparities in rural obstetric care for American Indian populations Environmental Sustainability : Analyzing biomass energy systems, forest carbon impacts, and waste management frameworks Network Design : Developing optimization models for supply chain resilience, military logistics, and urban transit safety Policy Analysis : Evaluating multi-state environmental collaborations and localized food systems His publications demonstrate strong interdisciplinary applications of mathematical programming and spatial optimization to real-world challenges in healthcare access, energy sustainability, and transportation systems. Key Collaborations : Working with researchers in public health (Thorsen, Noble), environmental science (Aguilar), and engineering (Mirzaee, Gutierrez-Lopez)
Dragan Huterer is a Professor of Physics and Associate Chair for the Graduate Program at the University of Michigan. His research focuses on cosmology, particularly dark energy and large-scale structure, utilizing data from the Dark Energy Survey (DES) and the Dark Energy Spectroscopic Instrument (DESI) collaborations. He earned his Ph.D. from the University of Chicago (2001) and B.S. from MIT (1996). His work explores the nature of dark energy through cosmological probes like Type Ia supernovae, galaxy clustering, and cosmic microwave background anisotropies. Key contributions include co-leading DESI's first-year cosmological analysis, revealing unprecedented constraints on dark energy and neutrino masses. He also investigates the statistical isotropy of the universe and authored the textbook A Course in Cosmology: From Theory to Practice . Awards include the Friedrich Wilhelm Bessel Research Award (2019) and the Chambliss Astronomical Writing Award (2025). He has advised numerous graduate and undergraduate students, and his funding includes DOE, NSF, and NASA grants. Current projects include the Michigan Cosmology Summer School and leadership in the DESI Collaboration.
B. L. Turner II is a Regents' Professor and Gilbert F. White Professor of Environment and Society at Arizona State University, affiliated with the School of Geographical Sciences and Urban Planning and the School of Sustainability. His work focuses on human-environment relationships, land system science, urban sustainability, and ancient Maya studies. Education: PhD in Geography from the University of Wisconsin-Madison (1974), MA and BS from the University of Texas at Austin. Research Interests: Land system architecture, tropical deforestation, urban heat islands, and sustainability science. His research has been supported by NSF, NASA, USDA, and others. Key contributions include studies on land change in the Southern Yucatán, vulnerability frameworks, and urban climate adaptation. Major Awards: Preston E. James Award, Sustainability Science Award, Fellowships from AAAS and NAS. Turner has advised over 50 doctoral students and contributed to interdisciplinary initiatives like the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) and the Global Land Project.
Christopher Turbill is an Associate Professor in Animal Science at Western Sydney University's School of Science, where he maintains an active research program focused on animal physiological ecology. He is affiliated with the Hawkesbury Institute for the Environment and serves as a Principal Investigator on multiple research projects while accepting HDR candidates for supervision. PhD from University of New England (2006) Thesis: Thermoregulatory Ecology of Tree-roosting Bats Supervised by Prof. Fritz Geiser Postdoctoral fellowships from Austrian Science Fund and Australian Research Council (DECRA) Former ecologist with NSW Government Professor Turbill's research integrates thermal and metabolic physiology with behavioral ecology to understand animal-environment interactions. His work has revealed significant ecological consequences of controlled body temperature variation in mammals and birds, linking these processes with metabolic energy expenditure, activity patterns, and life-history strategies. He specializes in bat biology and investigates conflicts between human environmental change and animal conservation requirements. His research keywords include ecophysiology, thermoregulation, energy expenditure, life-history ecology, body temperature, torpor, hibernation, and wildlife conservation. Analysis of Turbill's recent publications reveals a strong focus on thermal biology and conservation physiology, particularly regarding bats and birds. His work examines how animals manage energy through torpor, respond to climate change through thermal regulation, and adapt to anthropogenic disturbances. The research spans field studies of flying-foxes, microbats, and passerine birds across Australian ecosystems, with increasing emphasis on conservation applications related to white-nose syndrome, fire impacts, and wind energy development. Turbill leads significant research projects including the Ecology of the eastern horseshoe bat and its sensitivity to fire impacts (2024-2027), Vulnerability of Australian bats to white-nose syndrome (2021-2026), and Torpor use and burrowing behaviour in an arid zone passerine (2024). His work attracts funding from diverse sources including the Australian Research Council, Department of Planning and Environment, and various conservation organizations. Professor Turbill directs the BatsLab research group, which maintains a virtual hub for bat research at Western Sydney University. His team employs advanced methodologies including thermal imaging, GPS tracking, and physiological monitoring to study animal responses to environmental challenges. Current work focuses on developing conservation interventions for heat-stressed flying-foxes and assessing vulnerabilities of Australian bat species to emerging diseases.
Yin Bao is an Assistant Professor in Plant and Soil Sciences and Mechanical Engineering at the University of Delaware since 2023, previously holding the same position at Auburn University's Department of Biosystems Engineering (2019-2023). He holds a BE in Mechanical Engineering from China Agricultural University (2012) and a PhD in Agricultural and Biosystems Engineering from Iowa State University (2018), followed by postdoctoral research there until 2019. His research focuses on automation technology for agriculture and forestry, leveraging robotics, machine learning, and sensing systems to develop tools for precision farming and plant phenotyping. Key areas include unmanned systems (UGVs/UAVs), spectral imaging, and AI-driven predictive models for crop and livestock management. Recent work emphasizes automated inventory systems for forest nurseries, UAV-based vegetation assessment, and machine learning applications in crop yield prediction. His publications span robotic guidance systems, root segmentation in X-ray CT scans, and equine gait analysis using deep learning. Notable projects include the Robotic Assay for Drought (RoAD) system and the 'smart canopy' sorghum initiative. Collaborative efforts involve integrating multifrequency microwave sensing and electronic nose technologies for crop quality analysis.
