Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration
Dr. Matloob Khushi serves as a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 25 years of combined academic and industry experience, his work bridges theoretical AI advancements with practical applications in finance, healthcare, and public health domains. His research has established significant collaborations with international banks, healthcare institutions, and technology startups. Dr. Khushi earned his PhD in AI and Data Science from the University of Sydney, developing novel algorithms for genomic data analysis. His postdoctoral research at the Children's Medical Research Institute (2014-2017) pioneered AI-based diagnostic tools for medical condition detection. More recently, he developed bioinformatics tools for environmental assessment under a UKRI NEC grant. Research Focus FinTech Innovation : Creator of the SS Ratio (incorporating volatility and drawdown sensitivities), advanced portfolio optimization models, and synthetic data generation techniques for fraud detection and credit risk assessment Bioinformatics Leadership : Developer of AI tools for genomic analysis and early cancer detection, featured in SBS News and The Daily Telegraph Public Health NLP : Architect of systems for vaccine misinformation detection, mental health monitoring, and health surveillance on social media His publication portfolio shows consistent growth from foundational bioinformatics work to current multimodal AI applications, with increasing interdisciplinary collaboration across finance and healthcare sectors. Awards and Recognition Ranked among Stanford/Elsevier's top 2% of global AI scientists Recipient of Best Paper Awards from IEEE Transactions on Computational Social Systems and PeerJ Media recognition for cancer detection research by major news outlets Mentorship and Teaching Dr. Khushi has supervised six PhD candidates to completion and over 100 postgraduate dissertations. He teaches CS3002 Artificial Intelligence and mentors students in Final Year Projects. His supervision focuses on Deep Learning/NLP for FinTech prediction and Public Health Surveillance applications, emphasizing practical implementation of theoretical concepts.
Cyrille Artho is an Associate Professor in the Division of Theoretical Computer Science at KTH Royal Institute of Technology, actively contributing to research in formal methods, software testing, and cybersecurity. His work spans model checking, smart contract security, and concurrent systems verification, with significant contributions to tools like Java Pathfinder and Modbat. PhD from ETH Zurich (2005) with dissertation on multi-threading fault detection Teaches Software Safety and Security, Software Engineering Fundamentals, and supervises degree projects His research focuses on developing formal techniques for safety-critical systems, particularly in blockchain security and distributed applications. Recent work emphasizes smart contract verification, anomaly detection in microservices, and trusted execution environments for secure cloud analytics. The 15 most recent publications reveal a strong trend toward blockchain security (6 articles), formal verification of distributed systems (5), and novel testing methodologies (4), with increasing integration of machine learning for vulnerability detection. As chair of the FTSCS workshop series and contributor to major conferences like ASE and ICST, Artho has significantly shaped the formal methods community. His leadership in organizing workshops demonstrates commitment to advancing safety-critical systems research. Principal investigator for C3.ai DTI Cyber Safety Cage for Networks project Develops Modbat framework for model-based API testing Active in Digital Futures research initiative at KTH
Brice Kuhl is a Professor in the Department of Psychology at the University of Oregon , where he leads the Kuhl Lab. His research focuses on the cognitive neuroscience of memory formation, retrieval, and forgetting , utilizing advanced neuroimaging techniques like fMRI and EEG combined with machine learning algorithms to analyze distributed neural activity patterns. His work explores mechanisms of memory interference resolution , forgetting , and neural representation transformation . Recent publications emphasize spaced learning , temporal memory dynamics , and memory-cognitive control interactions . The lab has received attention for decoding perceptual content from neural activity and reconstructing face images based on brain states. Current lab members include graduate students Anisha Babu , Tongle Cai , and America Romero , alongside postdocs like Soroush Mirjalili and Yoonjung Lee . The lab frequently presents at conferences like CNS and SFN , and maintains active collaborations in memory research and neuroimaging methodology . Notable projects include investigations into hippocampal pattern differentiation and parietal cortex roles in memory . The lab also contributes to open science initiatives with publicly available experimental codes and data .
Paul Pu Liang is an Assistant Professor at the Massachusetts Institute of Technology (MIT) Media Lab and Department of Electrical Engineering and Computer Science (EECS). He directs the Multisensory Intelligence research group, focusing on building AI systems that integrate diverse sensory inputs to enhance human-AI symbiosis. His work spans theoretical foundations, large-scale resources, and neural architectures for multisensory learning. Education: PhD in Machine Learning (Carnegie Mellon University), MS in Machine Learning (Carnegie Mellon), BS with University Honors in Computer Science and Neural Computation (Carnegie Mellon) Research Interests: Multimodal machine learning, human-AI interaction, clinical AI, generative models, and responsible deployment of AI systems Key Contributions: MultiBench, HEMM evaluation framework, CLIMB clinical data foundations, and multimodal transformer architectures Recent publications emphasize multimodal foundation models , clinical applications , and socially responsible AI . His work has been recognized with multiple best paper awards and fellowships from Siebel, Facebook, and other institutions. Scientific Awards Siebel Scholars Award Waibel Presidential Fellowship Facebook PhD Fellowship Center for ML and Health Fellowship Rising Stars in Data Science Four best paper awards Paul teaches courses on machine learning and multimodal AI at MIT and CMU. He mentors students across multiple programs including Media Arts & Sciences, EECS, and IDSS, with former advisees now at institutions like OpenAI, UC Berkeley, and Princeton.
Alexandra Papoutsaki is an Associate Professor of Computer Science at Pomona College since 2017. Her research focuses on Human-Computer Interaction , particularly in webcam-based eye tracking and shared gaze for remote collaboration . Ph.D. in Computer Science from Brown University M.Sc. in Computer Science from Brown University B.Sc. in Computer Science from Athens University of Economics and Business Her work spans personal informatics , crowdsourcing methodologies , and remote usability testing , with recent projects examining collaborative drawing interfaces, baby tracking reflection, and digital health communities. Earlier contributions include computational biology research in genome-wide survival analysis and pan-cancer mutation networks. Key trends in her publications include: Remote collaboration tools enhanced by eye tracking Personal data systems for health and creative domains Foundational work in crowdsourcing quality control Interdisciplinary approaches combining computer science with psychology and medicine Scientific recognition includes: NSF CRII Grant (2020-2022) Wig Distinguished Professor Award (2020) Best Paper at RECOMB (2013) She has developed multiple open-source platforms including WebGazer for scalable eye tracking and Remotion for mobile usability testing. Her research team has published extensively in top venues like CHI, IMWUT, and IJCAI.
Florian 'Floyd' Mueller is a Professor of Future Interfaces at Monash University in Melbourne, Australia, where he directs the award-winning Exertion Games Lab within the Department of Human-Centred Computing (ranked among the top 20 HCI departments globally). Previously, he held positions at RMIT University, Stanford, University of Melbourne, Microsoft Research, MIT Media Lab, Fuji-Xerox Palo Alto Labs, Xerox Parc, and Australia's CSIRO. Mueller is a member of the prestigious ACM SIGCHI Academy, an honorary group recognizing leaders who have made substantial contributions to Human-Computer Interaction (HCI). Professor Mueller's research focuses on the intersections between technology, the human body, and play. He originated the concept of "Exertion Interface," arguing that we should not just design "easy-to-use" interactions when "hard-to-use" interactions can also be beneficial. His work spans movement-based interactions, whole-body interfaces, uncomfortable interactions, somaesthetics, and exertion games. Mueller's research methodology often employs research through design, design ethnography, and autoethnography to explore these novel interaction paradigms, incorporating mixed-reality, augmented reality, virtual reality, electronic muscle stimulation, biosensors, wearables, and drones. His recent publications demonstrate a continued focus on bodily interactions and human-computer integration, with particular emphasis on emerging subfields like WaterHCI and SportsHCI, brain-computer interfaces, and gustosonic (taste and sound) experiences. Mueller's work has evolved from foundational exertion game concepts to more sophisticated explorations of human-computer integration where technology becomes seamlessly woven into the fabric of human experience. Professor Mueller's contributions have been widely recognized with numerous awards including: Inaugural honouree of the Australian Design Centre's Design Honours Tall Poppy award for "intellectual and scientific excellence" 10 "Best Paper Honorable Mentions" (top 5%) from premier HCI conferences 2 "Best Paper" awards (top 1%) at CHI PLAY and CHI Shortlisted for the European Innovation Games Award (alongside Nintendo's WiiFit) Nokia Mindtrek Ubimedia Award Mueller has successfully secured some of Australia's largest and most competitive research grants, achieving a remarkable 14% success rate on Australian Research Council Discovery Project applications. He has served as General co-Chair for CHI PLAY'18 and CHI'20, becoming the first Australian-based researcher to spearhead HCI's highest-ranked publication outlet, and is currently General co-Chair for CHI'24. He is Associate Editor for tier A journals including Elsevier's IJHCS (International Journal of Human-Computer Studies) and ACM's IMWUT (Interactive, Mobile, Wearable and Ubiquitous Technologies). As director of the Exertion Games Lab, Mueller leads a research team whose innovations have been experienced by over 20,000 users across 3 continents and featured on the BBC, ABC, Discovery Science Channel, and Wired magazine. The lab has produced groundbreaking work in bodily interfaces, co-founding the CHI PLAY conference series and establishing new research directions in SportsHCI and WaterHCI through recent "Grand Challenges" papers. Mueller's lab continues to push boundaries with projects exploring brain-to-brain interfaces, lucid dreaming induction, and novel gustosonic experiences.
Camillo J. Taylor is the Raymond S. Markowitz President’s Distinguished Professor in the Department of Computer and Information Science at the University of Pennsylvania , where he has been a faculty member since 1997. He also serves as Associate Dean for Diversity, Equity, and Inclusion at the School of Engineering and Applied Science. His research focuses on Computer Vision and Robotics , particularly in 3D reconstruction, semantic mapping, and autonomous navigation. Education: A.B. in Electrical Computer and Systems Engineering, Harvard College (1988) M.S. and Ph.D. in Computer Science, Yale University (1990, 1994) Research Interests: Dr. Taylor’s work bridges Computer Vision and Robotics to enable autonomous systems to perceive and navigate complex environments. Key themes include semantic SLAM, event camera applications, and meta-learning for adaptive controllers. His projects often integrate vision, physics, and multi-agent collaboration, as seen in systems like EvMAPPER and OCCAM . Recent Article Trends: His 2024–2025 publications focus on semantic mapping , event-based vision , and multi-agent LLM systems , reflecting his lab’s emphasis on real-time perception, physics-informed reconstruction, and rational decision-making in robotics. These works span applications from solar eclipse imaging to wildfire analysis and natural hazard resilience. Awards: NSF CAREER Award (1998) Lindback Minority Junior Faculty Award (2001) IEEE WACV Best Paper Award (2012) Lindback Distinguished Teaching Award (2012) Advising and Service: Dr. Taylor has advised numerous PhD students, including Jason Hughes and Bowen Jiang. He has served as a Program Chair for CVPR (2006, 2017) and General Chair for ICCV (2021). His contributions to the GRASP Laboratory have advanced autonomous micro-UAVs and semantic SLAM.
Xuan Liang is a Lecturer in Statistics at the Research School of Finance, Actuarial Studies and Statistics (RSFAS), Australian National University. With a PhD from Peking University and postdoctoral experience at Monash University, his research focuses on spatial statistics, nonparametric modeling, and environmental data analysis. Education: PhD in Statistics (Peking University, 2017), BSc in Statistics (Zhejiang University, 2012) His work addresses methodological challenges in spatial panel data analysis, network modeling, and air pollution quantification. He has developed novel techniques for meteorological confounder adjustment in air quality assessments and contributed to distributed data analysis methods. Recent research trends include: Advancing quasi-score matching for spatial econometric models Improving subbagging algorithms for big data Creating robust distributed data aggregation frameworks Refining spatial autoregressive panel data methodologies Scientific contributions include: ANU Vice-Chancellor’s Citation for Outstanding Contribution to Student Learning (Early Career), 2022 CBE Teaching Commendation for Outstanding Teaching, 2020 Co-development of the ggmatplot R package for matrix visualization Co-inventor of Chinese patent 201811183512.0 for air quality assessment He teaches advanced courses in time series analysis, regression modeling, and mathematical statistics at ANU, while maintaining active research collaborations in econometrics and environmental statistics.
Emad Oveisi serves as a Research and Teaching Associate at École Polytechnique Fédérale de Lausanne (EPFL), primarily affiliated with the Interdisciplinary Centre for Electron Microscopy (CIME) at the EPFL Valais Wallis campus in Sion. He simultaneously holds roles in EDCH-ENS (Teaching), EDMX-ENS (Teaching), the Teachers Council (CCE), and the EPFL Assembly (AE), reflecting his multifaceted contributions to research, education, and academic governance. His academic foundation includes a PhD in Materials Science and Engineering from EPFL (2014), an MSc from the University of Tehran (2008), and a BSc in Metallurgy and Materials Engineering from the University of Tehran (2005). PhD: Materials Science and Engineering, EPFL (2014) MSc: Materials Science and Engineering, University of Tehran (2008) BSc: Metallurgy and Materials Engineering, University of Tehran (2005) Oveisi pioneers advanced electron microscopy techniques with emphasis on real-time 3D imaging of crystal defects and precision measurement of materials properties using aberration-corrected S/TEM. His work bridges fundamental materials science with practical applications in nanotechnology and in situ dynamic analysis, enabling breakthroughs in visualizing atomic-scale structural evolution. His research directly supports over 250 researchers across 12 interdisciplinary groups at EPFL-Valais. His scientific excellence is recognized through prestigious awards: Rodolphe and Renée Haenny Prize (2022) for contributions to electron microscopy techniques and teaching dedication Microscopy Today Innovation Award (2018) for inventing "Single-shot three-dimensional electron imaging" Oveisi actively mentors the next generation of scientists as evidenced by his supervision of PhD student Gulnaz Ganeeva. His research program receives substantial support from major funding bodies including the Swiss National Science Foundation (SNSF), European Research Council (ERC), Horizon 2020, and the Research Council of Norway. Beyond the lab, he shapes institutional policy as an elected member of EPFL's Teachers Council Bureau and the School Assembly. As manager of EPFL-Valais' electron microscopy platform, Oveisi leads a critical infrastructure hub serving diverse research teams. His operational framework integrates cutting-edge instrumentation with rigorous safety protocols, while his collaborative approach fosters cross-departmental innovation in materials characterization across physics, chemistry, and engineering disciplines.
Christine Clark, MD, MSc is an attending laryngologist at Weill Cornell Medicine’s Sean Parker Institute for the Voice and Assistant Professor in the Department of Otolaryngology-Head and Neck Surgery at Weill Cornell Medical College. She earned her B.A. from the University of Pittsburgh (2011) and her M.D. from Pennsylvania State University College of Medicine (2017), followed by residency at Georgetown University Medical Center and a fellowship in Laryngology at Weill Cornell, where she also obtained a master’s degree in Clinical and Translational Science. B.A. - University of Pittsburgh (2011) M.D. - Pennsylvania State University College of Medicine (2017) Residency - Georgetown University Medical Center Fellowship - Sean Parker Institute for the Voice (Laryngology) Master’s - Clinical and Translational Science at Weill Cornell Dr. Clark specializes in evaluating and treating swallowing, voice, and airway disorders. Her research focuses on chronic cough, laryngeal hypersensitivity, and benign phonotraumatic vocal fold lesions. She has developed clinical tools like the 3D-printed injection laryngoplasty simulator and quality improvement initiatives for surgical airway management. Her clinical work and research span topics such as vocal fold hemorrhage management, pharyngeal residue quantification in dysphagia, and granuloma as markers of malignancy. Recent publications emphasize global otolaryngology capacity building and performer-specific voice injury care. Scientific awards include: Teaching awards for excellence in medical student education during residency Dr. Clark is affiliated with the Sean Parker Institute for the Voice at Weill Cornell Medicine and serves as an Assistant Professor of Otolaryngology.
Maureen Kendrick is a Professor and Deputy Department Head in the Department of Language & Literacy Education at the University of British Columbia's Faculty of Education. Her research examines literacy and multimodality as integrated communicative practices, addressing social and cultural issues in diverse contexts with particular emphasis on visual communication and refugee/migrant education. Her research interests span digital literacies, multiliteracy and multimodality, and international perspectives on literacy education. She investigates how youth from refugee backgrounds use multimodal approaches to construct identities and engage with learning, often through digital storytelling and visual methodologies. Her work extends to health literacy in Ugandan contexts and the role of play in early childhood literacy development across Canada, Kenya, and Uganda. Analysis of her recent publications reveals consistent focus on refugee/migrant education, digital storytelling, and multimodal literacy. She examines how digital tools empower marginalized youth to express identities while addressing challenges in language learning and cultural integration. Her research also explores HIV/AIDS education through makerspaces and the intersection of arts-based practices with science literacy. Dr. Kendrick's scientific recognition includes: Canadian Committee for Graduate Students in Education (CCGSE) Mentorship Award (2024) Killam Teaching Prize (2012-13) Alan C. Purves Award (2013) She actively supervises graduate students across doctoral and master's programs, with current research focusing on refugee education and multilingual learners. Her SSHRC-funded projects include the 2025-2029 grant 'Digital Multimodal Composing-To-Learn' and the 'Language and Literacy Learning Among Refugee and Migrant Background Children' initiative, involving collaborators from UBC, York, and Western universities. Dr. Kendrick leads international research teams across Canada, Uganda, and Kenya, developing community-engaged approaches to literacy education that bridge academic research and classroom practice.
Dhruv Shah is an Incoming Assistant Professor of Electrical and Computer Engineering at Princeton University starting January 2026 and currently serves as a Senior Research Scientist at Google DeepMind. He is also an Associated Faculty member in Princeton's Center for Statistics and Machine Learning, focusing on the convergence of machine learning and robotics for real-world deployment. His academic credentials include a Ph.D. and M.S. in Electrical Engineering and Computer Sciences from the University of California, Berkeley (2024) and a B.Tech. (Honors) in Computer Science and Engineering from the Indian Institute of Technology, Bombay (2019). Shah's research pioneers foundation models for robotics, emphasizing large-scale robot learning, out-of-distribution generalization, and long-horizon reasoning. His group adopts a full-stack methodology spanning algorithmic innovation to system design, drawing from cognitive science to develop physical AI systems at the perception-learning-control interface. Key focus areas include reinforcement learning, human-robot interaction, and continual learning for challenging environments. Analysis of his 15 most recent publications reveals dominant trends in foundation models for visual navigation, language-conditioned policies, and multi-agent systems. His work increasingly integrates multimodal inputs (vision, language) while addressing generalization gaps in real-world settings, with strong emphasis on efficient data curation and scalable robot learning frameworks. His accolades feature the Microsoft Future Leaders in Robotics & AI Fellowship (2024), two IEEE ICRA Best Conference Paper Awards (2024), multiple ICRA finalist awards across cognitive robotics and manipulation categories, and the Berkeley Fellowship (2019-2024). Shah will recruit PhD students for Princeton's upcoming admissions cycle, establishing a research group dedicated to full-stack robotics development. While specific grant details aren't provided, his trajectory indicates significant funding for AI-robotics convergence projects, particularly in foundation model development and real-world deployment challenges. His laboratory at Princeton will integrate algorithmic innovation with system design, focusing on physical AI systems that bridge perception, learning, and control while maintaining strong ties to cognitive science principles for human-aligned robotic intelligence.
Steven Chung is an Associate Professor at the Department of East Asian Studies and affiliated faculty in Comparative Literature at Princeton University. He currently serves as Director of Graduate Studies and Acting Chair of the University Committee for Film Studies. Education : Ph.D. in East Asian Languages and Literatures (University of California, Irvine), M.A. in English Literature (University of British Columbia), B.A. in English Literature (University of Toronto) Research Interests span Korean and East Asian film/media, Cold War cultural histories, political/religious conversion, and film/critical theory. His work examines transnational media flows, postcolonial cinema, and ideological representations. Recent Courses : Cinematic Translation, Contemporary Korean Media Cultures, North Korean Imaginaries, Conversion Media in Asia, and graduate seminars in East Asian Film Studies. Awards : Association for Asian Studies Prize for Best Book in Korean Studies (2014)
Dan Lizotte is an Associate Professor jointly appointed to the Department of Computer Science in the Faculty of Science and the Department of Epidemiology and Biostatistics in the Schulich School of Medicine & Dentistry at Western University. Additional affiliations include the Schulich Interfaculty Program in Public Health and a cross-appointment to the Department of Statistics and Actuarial Sciences. Based in Middlesex College, London, Ontario, his contact email is dlizotte@uwo.ca. His research centers on machine learning and biostatistics for health decision support, with emphasis on sequential decision-making in chronic disease management where evolving patient health status and preferences inform adaptive interventions. Core contributions involve adapting reinforcement learning frameworks to model dynamic health decisions in public health and primary care settings, addressing methodological challenges in personalized medicine and risk prediction. Analysis of his publication record reveals consistent focus on healthcare applications of machine learning, particularly in chronic disease risk modeling using electronic medical records, intersectionality frameworks in public health AI, and Bayesian methods for dose personalization. His work bridges reinforcement learning with clinical decision support systems, advancing dynamic treatment regimes and statistical methodologies for evolving patient data. No scientific awards were mentioned in the provided text. The text does not specify any advisees, grant funding, or educational background details. Lizotte leads a research laboratory focused on machine learning applications in health, as evidenced by the dedicated lab site referenced in his contact information. His team likely explores intersections of statistical methodology, AI ethics, and clinical implementation for personalized health interventions.
