Darren Dahl is a Professor at the University of British Columbia (UBC) Sauder School of Business , holding the RBC Financial Group Professor of Entrepreneurship chair. His research focuses on new product development , creativity , consumer emotions , social influence , and social marketing . Education: BCom from the University of Alberta, PhD from UBC Leadership: Dean of the Sauder School of Business Research Trends: Recent work emphasizes innovation strategies , consumer identity dynamics , ethical marketing , and social impact . He explores how organizational structures influence perceptions, the role of identity in consumption, and the psychological drivers of prosocial behavior. Contact: Office HA 769, Tel: 604-822-8556, Email: darren.dahl@sauder.ubc.ca
Aaron Tohuvavohu is a Research Fellow in the Division of Physics, Mathematics, and Astronomy at the California Institute of Technology. His work focuses on high-energy astrophysics, particularly gamma-ray bursts (GRBs) and multi-messenger astronomy. He is deeply involved in the Neil Gehrels Swift Observatory mission, specializing in real-time localization of transient events using the BAT-GUANO pipeline and collaborating with gravitational-wave detectors like LIGO/Virgo/KAGRA. His research emphasizes rapid-response observations of GRBs and gravitational-wave events, leveraging the Interplanetary Network (IPN) for precise localization. He has contributed to studies of short-hard GRBs associated with compact object mergers and long-duration GRBs linked to hypernovae. Notable projects include the CASTOR mission concept for UV photometry and detector characterization for next-generation astronomical instruments. Aaron's recent work includes analyzing Swift/XRT and UVOT observations of GRB afterglows, setting upper limits for electromagnetic counterparts to gravitational-wave triggers, and improving IPN triangulation algorithms. His publications reflect a systematic approach to transient astronomy, integrating data from multiple observatories for comprehensive event characterization.
Volodymyr Kuleshov is an Assistant Professor at Cornell Tech and Cornell University's Department of Computer Science. His research focuses on machine learning, particularly generative models, probabilistic methods, and applications in health and sustainability. He co-founded Afresh, an AI startup reducing food waste, and has commercialized genome sequencing work via Moleculo (now part of Illumina). Kuleshov earned his PhD from Stanford University, advised by prominent figures like Stefano Ermon and Serafim Batzoglou. He teaches courses like CS 5785 (Applied Machine Learning) and CS 6785 (Advanced Topics in Machine Learning). His awards include the NSF CAREER Award and Arthur Samuel Best Thesis Award. Education: PhD in Computer Science from Stanford University (2018), advised by Stefano Ermon, Serafim Batzoglou, Michael Snyder, Christopher Re, and Percy Liang. Research Interests: Core ML (generative models, approximate inference), health tech (genome sequencing, clinical decision support), sustainability (AI-driven food waste reduction). Notable projects include Caduceus for DNA sequence modeling and Diffusion Duality theory. Awards: Google Research Scholar Award (2025), Outstanding Paper Award (EMNLP 2023), NIH MIRA Award (2023). Students/Advising: Over 20 advisees across PhD, Master’s, and undergraduate programs, including Edgar Marroquin (PhD) and Charlie Marx (Stanford). Alumni include Allan Bishop (Bloomberg) and Yong Huang (UCI PhD). Labs/Teams: Leads research groups at Cornell Tech focusing on generative AI and its real-world applications. Collaborates with institutions like MILA (Montreal) and DeepMind.
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
Jim Hall is a Professor of Climate and Environmental Risk at the University of Oxford's School of Geography and the Environment, and serves as Director of Research there. He is also a Visiting Fellow at Linacre College and holds leadership roles including Chair of the Science Advisory Committee at IIASA, and Expert Advisor to the UK's National Infrastructure Commission. His work focuses on systemic risk analysis, infrastructure resilience, and policy implications of climate change adaptation. Prof Hall has pioneered methodologies like the National Infrastructure Systems Model (NISMOD) and chairs the Data and Analytics Facility for National Infrastructure (DAFNI). His research spans flood risk management, energy systems decarbonization, and transboundary water resource conflicts in regions such as the Eastern Nile Basin and the Caribbean. Key research areas include robust decision making under uncertainty, info-gap theory applications, and integrated assessments of human-environmental systems. He has contributed to major international assessments, including the IPCC's Fourth Assessment Report, and developed frameworks for multi-hazard stress testing of infrastructure networks. Scientific Awards: George Stephenson Medal (2001), Prince Sultan Prize for Water (2018), Royal Academy of Engineering Fellowship (2010) His advising and grants work includes mentoring a DPhil student Erin Canning and leading projects like MARIUS and ENHANCE. He has also developed innovative modeling tools for coastal erosion prediction and probabilistic assessments of global shipping fuel transitions. Prof Hall’s research groups actively engage in interdisciplinary projects, including the Oxford Martin Programme on Resource Stewardship and the UK Infrastructure Transitions Research Consortium. His work emphasizes bridging scientific analysis with actionable policy solutions for climate adaptation.
Karoline Faust is an Associate Professor at KU Leuven, affiliated with the Laboratory of Molecular Bacteriology (Rega Institute) and the Faculty of Medicine . She contributes to the iSi Health and Leuven One Health institutes, and serves on senior academic councils. Her research spans microbial systems biology, focusing on community dynamics and network analysis. Education: PhD in bioinformatics (2010, KU Leuven) Affiliations: KU Leuven, ISME Journal editorial board, Belgian Society for Microbiology Her research investigates microbial community dynamics , systems biology approaches to microbiomes, and bioinformatics tool development . She specializes in modeling human gut microbiota , synthetic microbial communities , and environmental microbiomes (e.g., microplastic impacts on Daphnia microbiomes). Her work integrates metabolic modeling , network analysis , and experimental systems to understand microbial interactions. Recent publications highlight her contributions to microbial network inference , 16S rRNA sequencing protocols , microfluidics , and ecological modeling of microbiomes. She develops tools like manta , miaSim , and CoNet to analyze community structures. Teaching: Karoline co-teaches courses in microbiology, bioinformatics, and network analysis at KU Leuven, and has contributed to international workshops on microbial network inference. Scientific Engagement: She serves as Senior Editor at ISME Journal and Secretary of the Belgian Society for Microbiology .
Bertrand Schneider is an Associate Professor of Education at Harvard University's Graduate School of Education (GSE). He holds a Ph.D. in Learning Sciences and Technology Design from Stanford University (2015) and previously served as a postdoctoral researcher at Stanford's Transformative Learning Technologies Laboratory. His research focuses on educational interfaces (e.g., augmented reality, tangible tools) and multimodal learning analytics, particularly in collaborative and informal learning environments. He investigates how technologies like gaze-tracking and motion sensors can assess student learning trajectories and improve instructional strategies in makerspaces and remote teaching contexts. Education : Ph.D., Learning Sciences and Technology Design, Stanford University (2015) Postdoctoral Researcher, Transformative Learning Technologies Laboratory, Stanford University Research Interests : Educational technologies (AR, tangible interfaces, multitouch) Multimodal data analysis (gaze, body movement, speech) Collaborative learning in formal/informal settings Remote teaching strategies using shared gaze visualizations AI applications in personalized feedback and misinformation discernment Key Contributions : Developed methodologies for capturing joint visual attention in collaborative learning Advocated for ethical implementation of multimodal learning analytics Explored AR's dual-edged impact on student engagement and collaboration Labs/Teams : Current research aligns with GSE's focus on innovative learning technologies Prior affiliation with Stanford's Transformative Learning Technologies Lab
Dr. Andrea R. English is a Senior Lecturer in Philosophy of Education at the Moray House School of Education and Sport, University of Edinburgh. She holds significant academic leadership roles, including President-Elect of the John Dewey Society and Editor-in-Chief of IMPACT: Philosophical Perspectives on Education Policy . Her research focuses on productive struggle in learning, dialogic pedagogy, and decolonizing education. She earned her doctorate from Humboldt University Berlin and has taught globally, including at Mount Saint Vincent University and Humboldt University Berlin. Dr. English leads the Productive Struggle Lab and the Listening Study Group, emphasizing anti-oppressive and democratic educational approaches. She coordinates teacher education initiatives and supervises PhD students exploring critical thinking, inclusive education, and decolonization. Her work bridges philosophy and practice, addressing how teachers foster student resilience through pedagogical listening, particularly in STEM education. She actively contributes to Scotland’s anti-racist curriculum project and collaborates internationally on transformative learning and ethical teaching practices. Dr. English’s teaching spans undergraduate and postgraduate programs, including courses on critical thinking, inclusive pedagogy, and John Dewey’s educational philosophy. Her funded research explores AI tools for identifying student struggle and the role of negativity in transformative learning. She frequently presents at global conferences, advocating for dialogic teaching and moral education reform.
Associate Professor David Jeffery is affiliated with the University of Adelaide's School of Agriculture, Food and Wine, within the Faculty of Sciences, Engineering and Technology. He holds an academic rank of Associate Professor/Reader and is based at Wine Innovation Central in the Waite campus. His research focuses on grape and wine chemistry, particularly aroma, flavor, and polyphenol analysis using advanced techniques like HPLC-MS/MS and GC-MS. He investigates the impact of vineyard and winemaking conditions on wine composition, including studies on tannin behavior, sulfur compounds, and oxidative processes. Jeffery co-authored the textbook *Understanding Wine Chemistry*, a global resource in wine science education. His work also explores machine learning applications for predicting sensory traits and authenticating wine origins. Active in mentoring, he supervises Masters and PhD students in topics spanning analytical method development, compound synthesis, and wine quality enhancement. Research highlights include studies on wildfire smoke mitigation in wine production, fluorescence spectroscopy for quality control, and mathematical modeling of anthocyanin interactions. He collaborates with industry partners like Wine Australia and leads projects funded by the ARC Training Centre for Innovative Wine Production. His contributions bridge fundamental chemical research with practical applications in the wine industry, addressing challenges like climate change impacts and sustainable winemaking practices.
H.-S. Philip Wong is the Willard R. and Inez Kerr Bell Professor in the School of Engineering at Stanford University, where he has been since 2004. He holds the rank of Professor in the Department of Electrical Engineering and serves as the Director of the Stanford Nanofabrication Facility. Prior to Stanford, he spent 16 years at IBM’s T.J. Watson Research Center and served as Vice President of Corporate Research at TSMC (2018–2020), remaining as Chief Scientist in an advisory role thereafter. Leadership roles include founding the Stanford SystemX Alliance and leading the Microelectronics Commons AI Hardware Hub funded by the CHIPS Act. Research focuses on nanotechnology, semiconductor devices, and next-generation computing architectures, including carbon nanotube electronics, 3D integration (N3XT/MOSAIC), and neuromorphic computing. Awarded IEEE Fellow (2001), the IEEE Andrew S. Grove Award, and the J.J. Ebers Award for contributions to electron devices. His work spans device physics, fabrication, and system integration, with over 600 publications. Key contributions include advancements in phase-change memory, carbon nanotube transistors, and compute-in-memory systems. He advises numerous students and collaborates with industry through initiatives like the Stanford Non-Volatile Memory Technology Research Initiative. Recent efforts emphasize AI hardware acceleration, cryo-CMOS for quantum computing, and scalable memory architectures. His lab innovations include CellChips for synthetic biology and hyperdimensional computing using 3D RRAM.
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.
Andrew D. White is an Associate Professor of Chemical Engineering at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from the University of Washington (2013). His research focuses on automating scientific discovery through AI, particularly leveraging large language models (LLMs) and deep learning techniques in chemistry. His lab develops agents that integrate literature analysis, hypothesis generation, and experimental design to advance fields like molecular dynamics and drug discovery. Education: PhD in Chemical Engineering, University of Washington, 2013 BS/MS (not explicitly stated in text, inferred from career timeline) Research Interests: Large language models for scientific automation Deep learning applications in chemistry and materials science Molecular dynamics simulations Scientific agents and autonomous systems Publications: His work includes groundbreaking studies on closed-loop AI systems for chemistry, federated learning in molecular property prediction, and multi-agent systems for drug discovery. Recent highlights include the Robin system and ChemCrow tools. Awards: Recipient of the NSF Career Award (2018), NIH Outstanding Investigator Award (2020), and the Curtis Teaching Award (2019). He also advises biotech companies and serves on the National Academy of Sciences' Chemical Sciences Roundtable. Grants & Funding: Supported by DOE, NSF (multiple grants including CBET-1751471), NIH (R35GM137966), and LLNL projects. Collaborates with institutions like Argonne National Lab and Qubit Pharmaceuticals. Labs & Teams: Leads the White Lab at Rochester and co-founded FutureHouse, a nonprofit advancing AI-driven scientific discovery. Supervises a multidisciplinary team of PhD students and postdocs in computational chemistry, AI, and biophysics.
Associate Professor Mohsen Kalantari is a Geospatial Engineering academic at the University of New South Wales (UNSW) School of Civil and Environmental Engineering , with concurrent roles as co-founder of the startup Faramoon . His career spans roles at the University of Melbourne's Department of Infrastructure Engineering and Victorian government's land administration initiatives through DELWP. Education : PhD in Geomatics Engineering (2008, University of Melbourne), Master of GIS Engineering (2004), Bachelor of Surveying Engineering (2001) His research bridges geospatial engineering with construction automation , focusing on 3D cadastre , BIM-GIS integration , and smart cities . Recent publications show trends in underground land administration , digital twins , and LADM standard implementations . Scientific Awards : National educational recognition (2019), Victorian educational grants (2018), and prestigious fellowships (2012) As a supervisor , he guides PhD candidates in topics ranging from BIM for waste management to underground cadastral systems . His industry engagement includes partnerships with the United Nations , Open Geospatial Consortium , and Singapore Land Authority .
Chao Liu is an Associate Professor at the Department of Biomedical Engineering , Southern University of Science and Technology (2024.11–present). Previously, he served as an Assistant Professor at the same institution (2019–2024.11) and completed a Postdoctoral Fellowship at New York University (2016–2019) with joint appointments in the Department of Biomedical Engineering and Orthopedics at NYU Langone Health . He holds a PhD in Biomedical Engineering (2016) and MASc in Mechanical Engineering (2010) from University of Toronto , following a BASc in Engineering Science (2008). Education : PhD (IBBME, U of Toronto, 2016), MASc (Mechanical Engineering, U of Toronto, 2010), BASc (Engineering Science, U of Toronto, 2008) His research focuses on mechanobiology of stem cells , bone tissue engineering , and functional implants . He investigates how mechanical forces modulate osteogenic and angiogenic stem cells, designs implants with micro-geometry to enhance cellular activity, and develops 3D real-time imaging modalities for bone repair processes. His work spans biomechanics , regenerative medicine , and cellular mechanotransduction . The selected publications from 2022 to 2010 reveal trends in mechanical force applications for bone regeneration, pharmacological impairments in healing, nanostructured biomaterials for stem cell differentiation, and microfluidic platforms for osteocyte studies. These works are published in journals like Bone , FASEB Journal , and ACS Applied Materials & Interfaces . Scientific Awards : International Conference BME Young Investigator Award (2019), IFMRS Travel Grant (2017), ASBMR Young Investigator Grant (2016), CIHR Travel Awards (2010–2014), Ontario Graduate Scholarship (2011–2013), Barbara and Frank Milligan Fellowship (2008, 2010) Chao Liu mentors graduate students, including Zhang Jianing (2022 Master’s graduate). His lab ( https://abtrl.bme.sustech.edu.cn/ ) recruits postdocs and research assistants for projects in mechanical force applications , micro-geometric implants , and 3D imaging . He has contributed to 14 journal articles with 714 citations and presented at 6 international conferences in the past three years.
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.
