Simon Arthur is a Professor of Immune Signalling at the University of Dundee, School of Life Sciences, within the Department of Cell Signalling and Immunology. His research focuses on understanding inflammatory processes, particularly the role of innate immune cells in coordinating inflammation and resolving immune responses. He holds a PhD from the University of Oxford (1995) and a BSc from Durham University (1990). Arthur is a Fellow of the Royal Society of Biology (2015) and serves on the editorial board of the Journal of Biological Chemistry . His teaching includes courses on Genetics, Cell Signalling, Immunology, and advanced topics in immunology and cell signalling. He supervises PhD projects on microglial phenotypes in brain ageing and immunomodulatory factors in helminth-host interactions. Arthur leads research projects funded by the Medical Research Council and other agencies, including studies on liver fibrosis, bile acid diarrhoea, and pulmonary fibrosis. Key research themes include cytokine regulation, macrophage function, and the molecular mechanisms underlying chronic inflammation. His work spans from fundamental biology to translational research, aiming to develop therapies for autoimmune and inflammatory diseases. Arthur collaborates internationally and has over 180 publications in high-impact journals.
Roger Tam is an Associate Professor in the School of Biomedical Engineering (SBME) at the University of British Columbia (UBC), with a joint appointment in the Department of Radiology. He is also the Associate Director of Graduate Studies. His research focuses on machine learning and computer vision applied to medical imaging, particularly in personalized medicine and quantitative image analysis. Tam earned his PhD in computer science from UBC in 2004, specializing in computational geometry and visualization. Education: PhD in Computer Science, UBC (2004) MSc in Computer Science BSc (Honors) Research Interests: Medical imaging biomarkers Machine learning applications in healthcare Quantitative image analysis Personalized medicine His work bridges computer science and clinical medicine, emphasizing translational approaches to improve diagnostic accuracy and patient outcomes. Recent Research Trends: Focus on myelin content analysis in neurological disorders (e.g., multiple sclerosis) Development of efficient machine learning models for medical image classification Impact of physical activity on white matter health Labs & Programs: Directs the Engineers in Scrubs program, which integrates engineering principles into biomedical education. Active in collaborative research initiatives like the Centre for Brain Health and the Canadian Prospective Cohort Study (CanProCo).
Sarah Carton is a Teaching Professor in the Psychology Department at Rutgers University, part of the School of Arts and Sciences. She joined Rutgers in Fall 2019 after earning her Ph.D. in the Cognition & Perception Program at New York University (2008). Her research focuses on developmental psychology, visual perception, and cognitive development in infants and young children. She teaches courses such as Introductory Psychology, Drugs & Behavior, Sensation & Perception, and Cognition, with upcoming courses like Perception of Color (PSY 2xx). Dr. Carton’s research interests include object recognition, visual illusions, perceptual categorization, infant development, and eye-tracking methodologies. Her work explores how infants perceive impossible figures, haptic exploration of objects, and transitional saccades in response to visual stimuli. She investigates foundational questions about how infants distinguish possible from impossible objects and develop spatial and dimensional understanding through multisensory interactions. Her teaching portfolio includes undergraduate courses at both Livingston and New Brunswick campuses. She actively contributes to educational initiatives in psychology, emphasizing evidence-based pedagogy. Dr. Carton’s current research trends span perceptual development, cognitive differentiation in infants, and the role of visual and haptic modalities in forming conceptual categories. Dr. Carton’s work has been published in leading journals, with recent studies examining young children’s understanding of object coherence and infants’ visual responses to paradoxical stimuli. Her research integrates behavioral experiments and eye-tracking technology to unravel early perceptual and cognitive processes.
Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.
Stacy Holman Jones is a Professor of Theatre and Performance in the School of Languages, Literatures, Cultures and Linguistics at Monash University. With over 23 years of academic experience, she has developed an international reputation for leadership in performance studies, particularly in feminist and queer theory, new materialist research, and critical arts-based methodologies. Her educational background includes a PhD in Communication/Performance Studies from the University of Texas at Austin (2001), an MA in Communication from California State University Sacramento (1996), and a BA in Humanities (1988). Professor Jones's research focuses on performance as socially, culturally, and politically resistive and transformative activity. She is a recognized leader in critical autoethnography and has published over 100 articles, book chapters, and editorials, as well as authored, co-authored, and edited 14 books including the influential Handbook of Autoethnography (2013, 2021) and Queering Autoethnography (2018). Her work spans cultural critique, social inclusion, education, resilience building, designing for social impact, and enhancing health and wellbeing among minoritarian communities. Analysis of her recent publications reveals a strong trajectory toward creative ecological approaches to mental health, collaborative autoethnographic methods, and innovative design for social impact. Her research increasingly integrates performance studies with mental health applications, particularly in educational settings, while maintaining strong connections to queer theory, new materialisms, and critical autoethnography. International Congress of Qualitative Inquiry's Special Career Award National Communication Association's Distinguished Service Award in Performance Studies Janice Hocker Rushing Early Career Research Award Organization for the Study of Communication, Language, and Gender Feminist Teacher/Mentor Award Over the Rainbow Recommended Book List for Queering Autoethnography (2019) International Congress of Qualitative Inquiry Qualitative Book Award, Honourable Mention (2020) Multiple Good Design Awards for 'The Tomorrow Party' (2024) Professor Jones has been part of 3 successful ARC applications totaling $1,353,604, including as Lead CI for DP200102876 Staging Australian Women's Lives (2020-2023). She is currently accepting PhD students with supervision interests in theatre and performance studies, social change and social justice, and health and wellbeing research. She serves as the founding editor of Departures in Critical Qualitative Research and has been actively involved in professional organizations including serving as President of the International Congress of Qualitative Inquiry (2015-2018). Her current research activities include multiple collaborative projects such as 'Playing Transitions - Settling and Belonging in School together' (2024-2027), 'Learning Creates: Tomorrow Party' (2024), and 'Canopy: Creative partnerships for policy advocacy in Climate and Health' (2024), demonstrating her commitment to interdisciplinary, impact-focused research that bridges theory and creative practice.
Dr. Chenhao Chu is a Professor at ETH Zürich, holding the Professur für Elektronik (Professorship for Electronics). He specializes in RF/mm-Wave circuits, AI-driven design methods, and advanced power amplification technologies. His research focuses on energy-efficient, wideband systems, antenna-in-package solutions, and GaN-based applications for 6G and beyond. Education: Ph.D. in Electronic Engineering, University College Dublin (2022) M.Sc. in Electronic Information Engineering, City University of Hong Kong (2017) Research Interests: His work bridges AI and hardware design, emphasizing reconfigurable circuits , high-linearity power amplifiers , and mm-Wave phased arrays . Key areas include: AI-assisted rapid design synthesis III-V/Si co-design for mm-Wave Efficient antenna integration Dynamic load modulation techniques Awards: Award-winning researcher with distinctions including the First Place Best Student Paper Award (2022 Royal Irish Academy Colloquium) and multiple HEPA-SDC Competition Awards (2021-2022). Recognized for innovations in PA efficiency and design automation. Advising & Grants: Leading projects on 6G PA architectures and AI-driven RF design. Active in IEEE with contributions to conferences like IMS and ARFTG. No explicitly stated grants mentioned but widely cited in industry-academia collaborations. Labs & Teams: Associated with ETH Zürich's Electronics Laboratory, focusing on next-generation wireless systems. Collaborates internationally on 5G/6G infrastructure and mm-Wave innovations.
Hossein Valavi is a Lecturer and Assistant Director of Undergraduate Studies at Princeton University, contributing to advancements in computer architecture and hardware acceleration. His research focuses on in-memory computing, neural networks, and energy-efficient systems, with notable work in reconfigurable architectures and mixed-signal processing. He has received multiple teaching awards, including recognition for innovative pandemic-era Car Lab courses and collaborative work honored by the Edison Patent Award. His academic contributions span academic positions since 2018, emphasizing both research and pedagogical excellence. Key technical areas include scalable in-memory computing systems, analog neural network accelerators, and low-power matrix factorization algorithms. His work addresses critical challenges in data movement reduction and hardware-software co-design for modern computing systems. Awards: Teaching Excellence Awards (2021, 2023), Edison Patent Award (2023) Grants & Projects: Leading developments in in-memory computing accelerators and embedded microprocessor designs Research teams under his guidance have produced impactful IP in semiconductor layouts, CNN accelerators, and programmable architectures, aiming to bridge theoretical computer science with practical hardware implementations.
Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.
Dr. Rani Moran is a Lecturer in Psychology at Queen Mary University of London's School of Biological and Behavioural Sciences. She is affiliated with the Centre for Brain and Behaviour. Her research focuses on decision-making, memory, and learning mechanisms, employing methods like computational modeling, neuroimaging, and pharmacological interventions. Key interests include reinforcement learning, cognitive maps, and exploration-exploitation dilemmas. Her work integrates experimental designs with advanced statistical analysis to understand flexible behavioral control. Recent studies explore model-based vs. model-free learning, credit assignment mechanisms, and disinformation's impact on learning biases. She has published in top journals such as Psychological Review and Nature Communications . Dr. Moran collaborates on projects involving neurocomputational models of confidence, meta-cognition, and social learning. Her research aims to develop interventions for optimizing cognitive processes, with applications in mental health and decision-making contexts.
Nikos Hardavellas is a Professor of Computer Science and Electrical and Computer Engineering at Northwestern University, affiliated with the McCormick School of Engineering. He leads the Parallel Architecture Group at Northwestern (PARAG@N), focusing on energy-efficient parallel computing and quantum systems. His research spans quantum computing systems, fault-tolerant quantum error management, memory-centric architectures, and photonics-based interconnects. Education: Ph.D. Computer Science, Carnegie Mellon University (2009) M.S. Computer Science, Carnegie Mellon University (2006) M.S. Computer Science, University of Rochester (1997) B.S. Computer Science, University of Crete (1995) Research Interests: Quantum system software stack and error mitigation Memory-centric computing and programmable memory systems Energy-efficient architectures and dark silicon Photonics and optical interconnects Parallel systems and compiler-hardware co-design Key Contributions: Developed SupermarQ, a scalable quantum benchmark suite Pioneered optical cache hierarchies (Pho$) and energy-proportional photonic networks Advanced compiler-driven virtual memory systems (CARAT) and MPI autotuning (ACCLAiM) Awards & Honors: NSF CAREER Award (2015) Future CRA Leader (2024) Best Paper Awards at HPCA (2022) and ISLPED (2021 nomination) Test-of-Time Award at EDBT (2019) Grants & Service: Secured $4.8M in research funding from NSF, industry partners, and university initiatives Executive Committee member of Northwestern’s INQUIRE Institute for Quantum Research General Co-chair of IEEE/ACM MICRO 2022 Extensive service on departmental committees and thesis advisory boards Labs & Teams: Directs PARAG@N, collaborating on quantum computing, photonics, and energy-efficient architectures. Engages with industry partners like AMD, Intel, and Synopsys.
Paul O'Gorman is a Professor at the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at the Massachusetts Institute of Technology. He currently serves as the Faculty Chair of the EAPS Committee on Education and as the EAPS Graduate Officer. His research focuses on understanding how climate change affects atmospheric circulation and precipitation patterns, particularly extreme events. Education: BA in Theoretical Physics, Trinity College Dublin MSc in High-Performance Computing, Trinity College Dublin PhD in Aeronautics with Minor in Applied Mathematics, California Institute of Technology Research Interests include atmospheric dynamics, hydrological cycle responses to climate change, moist convection, and the application of machine learning to climate modeling. His work addresses regional variability in extreme precipitation, vertical warming profiles in the tropics, and the fluid dynamics of land-ocean warming contrasts. Scientific Awards : Bernhard Haurwitz Memorial Lectureship (2023), American Meteorological Society MIT School of Science Graduate Teaching Prize (2018) Recent Contributions include co-leading the MIT Climate Grand Challenges flagship project "Preparing for a new world of weather and climate extremes" , which develops tools for predicting climate extremes and transitioning to low-carbon resources. He has also explored the asymmetrical generalization capabilities of machine learning algorithms in climate models under warming versus cooling scenarios.
Professor Michael Naef is the Head of the Department of Economics and a Professor at Durham University's Business School. His research focuses on Experimental and Behavioral Economics and Neuroeconomics , exploring topics such as trust dynamics, cultural influences on cooperation, and neurochemical effects on decision-making. He leads the Department of Economics within a triple-accredited business school, emphasizing academic excellence and global connections. Key research interests include investigating how dopamine receptors modulate trust behavior, the origins of cooperative behavior in rice-farming cultures, and the role of testosterone in social interactions. His work combines experimental economics with neuroscience and psychology, often employing pharmacological interventions and neuroimaging techniques. Publications highlight contributions to understanding volatility in trust beliefs (2023), the neurobiological basis of social learning (2019), and testosterone's influence on competitiveness (2017). He advises PhD students Angel Li and Zekun Lin, focusing on advancing behavioral economic theory and applications. Prof. Naef's research has implications for understanding cultural economic differences, mental health impacts on decision-making, and the biological underpinnings of social preferences. His work bridges disciplines, fostering interdisciplinary collaborations in economics, neuroscience, and endocrinology.
Jennifer A. Sandlin is an Associate Professor of Justice and Social Inquiry in the School of Social Transformation at Arizona State University (ASU). Her work focuses on public pedagogy, popular culture, and the intersections of education with consumption. She teaches courses on consumption and education, social justice, and cultural pedagogy. Sandlin holds a Ph.D. in Adult Education from the University of Georgia (2001), with a dissertation on educational programs for welfare recipients. She has authored/co-edited numerous books, including Paranoid Pedagogies (2018) and Critical Pedagogies of Consumption (2010), and has published widely in journals such as Journal of Consumer Culture and Adult Education Quarterly . Her research explores anti-consumerism activism, informal learning through popular culture, and the theory/practice of public pedagogy. She co-edits the Journal of Curriculum and Pedagogy and serves on editorial boards for multiple academic journals. Sandlin has received awards including the Early Career Award from the Commission of Professors of Adult Education (2005) and recognition as an Emerging Scholar by the American Association of University Women (2005). Her recent work addresses conspirituality, eco-horror, and pandemic pedagogies, reflecting her commitment to critically examining cultural and social structures. She actively engages in public scholarship through co-edited volumes and research on topics like Disney’s cultural curriculum and the political economy of consumption.
Md Sakib Hasan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Mississippi. He holds a Ph.D. in Electrical Engineering from the University of Tennessee-Knoxville (2017). His research focuses on hardware acceleration, neuromorphic computing, and memristor-based systems. Research interests span: AI hardware accelerators and energy-efficient computing Biomimetic systems and bio-inspired electronics Hardware security through chaotic systems and PUFs Recent publications demonstrate strong emphasis on: Neuromorphic architectures for computer vision and temporal processing Biomembrane-based computing systems Chaotic cryptography and secure hardware design
Xinya Du is an Assistant Professor in the Department of Computer Science at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. She holds a Ph.D. in Computer Science from Cornell University and completed a postdoctoral fellowship at the University of Illinois at Urbana-Champaign. Her research focuses on advancing trustworthy and impactful AI systems, particularly in Natural Language Processing (NLP), Large Language Models (LLMs), and Vision-Language Models (VLMs). Key research areas include Document understanding and knowledge acquisition Trustworthy reasoning and hallucination detection in LLMs Applications of NLP in scientific research and multimodal systems Alignment of AI systems with human values Dr. Du has received notable awards such as the NSF CAREER Award (2024), Amazon Research Award (2023), and recognition as a Spotlight Rising Star in Data Science. She has authored over 30 papers in top venues like ACL, EMNLP, NeurIPS, and CVPR, contributing to foundational work in multimodal reasoning, LLM evaluation, and automated scientific hypothesis generation. She teaches advanced courses including CS 6301: Special Topics in Computer Science - Deep Learning for NLP and actively mentors students in research projects. Her work has been highlighted in major media and led to impactful open-source contributions, including repositories for event extraction and LLM benchmarking.
