Douglas W. Diamond is the Merton H. Miller Distinguished Service Professor of Finance at the University of Chicago's Booth School of Business, where he has been on the faculty since 1979. He received the Nobel Memorial Prize in Economic Sciences in 2022 for his groundbreaking research on banks and financial crises. Diamond is also a research associate of the National Bureau of Economic Research and a visiting scholar at the Federal Reserve Bank of Richmond. His research focuses on financial intermediaries, financial crises, and liquidity. Diamond's work has established the theoretical foundations for understanding why banks exist, how they create liquidity, and why they are vulnerable to runs. His seminal papers with Philip Dybvig on bank runs and deposit insurance form the basis of modern bank regulation. Diamond's extensive publication record shows a consistent focus on banking theory, financial intermediation, and financial stability. His research has evolved from foundational theoretical work to more recent analyses of liquidity, pledgeability, and the role of banks in the financial system. His work has become increasingly relevant following the 2008 financial crisis and the more recent banking turmoil. Nobel Memorial Prize in Economic Sciences (2022) Onassis Prize in Finance (2018) CME Group-Mathematical Sciences Research Institute Prize (2016) Morgan Stanley-American Finance Association Award (2012) Member of the National Academy of Sciences Fellow of the Econometric Society Fellow of the American Academy of Arts and Sciences Diamond has served as president of both the American Finance Association and the Western Finance Association. He has advised policymakers during financial crises, including providing analysis of the Silicon Valley Bank collapse in 2023. His research has directly influenced financial regulation and central bank policy regarding bank stability and liquidity requirements.
Jessica Straley is an Associate Professor in the Department of English at the University of Utah, where she has served since 2005 (Visiting Assistant Professor 2005-2007, Assistant Professor 2007-2016, Associate Professor 2016-present). She holds a PhD in English from Stanford University, an MA in Literature, Culture, and Modernity from Queen Mary and Westfield College, University of London, and a BA in English from Cornell University. Education: PhD, English - Stanford University MA, Literature, Culture, and Modernity - Queen Mary and Westfield College BA, English - Cornell University Her research focuses on intersections between Victorian literature, children's literature, animal studies, disability studies, and ecocriticism. She explores how literary imagination interacts with scientific and moral discourses, particularly in 19th-century contexts. Recent publications analyze feral child narratives, zoo representations, and evolutionary theory in children's texts. Her work bridges historical literary analysis with contemporary critical frameworks like disability rights and environmental ethics. Scientific Awards: Faculty Fellowship Award (University Research Council, 2017) Ramona W. Cannon Award for Teaching Excellence (2016) Tanner Humanities Center Fellowship (2016) University Research Committee Faculty Fellowship (2011) Newberry Library Short-Term Library Research Fellowship (2008) She teaches courses in 19th-Century British Literature, Intellectual Movements, and Honors Thesis/Project supervision. Her external grant (Animal Testing URC, 2017-2018) demonstrates institutional support for her interdisciplinary work.
Haibin Ling is the SUNY Empire Innovation Professor in the Department of Computer Science at Stony Brook University, part of the College of Engineering and Applied Sciences. His research focuses on computer vision, medical image analysis, augmented reality, and AI applications in science. He holds a Ph.D. from the University of Maryland (2006) and prior degrees from Peking University. Previously, he worked at Temple University (2008–2019) and held roles at Siemens Corporate Research, UCLA, and Microsoft Research Asia. Professor Ling's work spans biomedical imaging, AI for science, and human-computer interaction. He leads the CV Lab and collaborates with the AI Institute at Stony Brook. Awards include the NSF CAREER Award (2014), Best Student Paper (ACM UIST 2003), and IEEE Fellow (2020). He serves on editorial boards for IEEE Trans. PAMI, Pattern Recognition, and CVIU, and chairs major conferences like CVPR. His research group includes over 50 students and alumni, with active projects in tracking benchmarks (LaSOT), Leafsnap, and medical imaging tools. Notable publications address OCTA flow estimation, backdoor attacks on vision models, and topology-guided medical learning. Collaborations involve institutions like Temple University and Stony Brook's Department of Applied Mathematics and Statistics.
Zhonghai Lu is a Professor of Electronic Systems Design (specializing in Dependable and Autonomous Systems) at KTH Royal Institute of Technology, part of the Department of Electrical Engineering in the School of Electrical Engineering and Computer Science (EECS). He serves as Program Director for KTH's Embedded Systems master's program and Director of Studies at the Division of Electronics and Embedded Systems. His research focuses on Network-on-Chip (NoC), computer architecture, embedded systems, and Prognostics and Health Management (PHM) of power electronics. He leads a research group exploring in-network processing and embedded intelligence, transforming passive networks into active computational frameworks. Lu holds a BSc from Beijing Normal University (1989), MSc and PhD from KTH (2002, 2007), and an MBA in Innovation and Growth from the University of Turku (2012). He has authored over 240 scientific papers, including journal articles and peer-reviewed conferences, with notable recognitions such as Best Paper Awards at NOCS’2015 and EU HiPEAC, and a Featured Paper in IEEE Transactions on Computers (2020). He serves as Associate Editor for ACM Transactions on Architecture and Code Optimization (TACO) and has chaired major conferences like HiPEAC’2017 and NOCS’2018. His research group’s recent work includes integrating AI into hardware acceleration, fault-tolerant neural networks, and RUL estimation for power electronics using recurrent neural networks. Lu has secured grants from the Swedish Research Council and Intel Corporation and developed courses like IL2230 (Hardware Architectures for Deep Learning) and IL2233 (Embedded Intelligence), pioneering embedded AI education at KTH. Education: BSc (Beijing Normal University), MSc/PhD (KTH), MBA (University of Turku) Awards: Best Paper Awards (NOCS, EU HiPEAC), Swedish Research Council Grants, Intel Research Gifts Labs/Teams: Research Group on In-Network Processing and Embedded Intelligence
Dr. Jiaqi Gong serves as Associate Professor in Computer Science and Adjunct Associate Professor in Mechanical Engineering at The University of Alabama's College of Engineering, while directing the Alabama Center for the Advancement of Artificial Intelligence. His academic foundation includes: B.S. in Engineering, China University of Geoscience (2004) Ph.D. in Engineering, Huazhong University of Science and Technology (2010) Dr. Gong's research pioneers human-AI convergence through cyber-physical systems and smart health technologies, developing mobile/wearable platforms to enhance human perceptual, cognitive, and physical capabilities. His work spans artificial intelligence, machine learning, computer vision, and IoT with applications in healthcare, environmental monitoring, and education. The Sensor-Accelerated Intelligent Learning (SAIL) laboratory he founded drives innovation in behavior change interventions, human movement modeling, and educational data mining. Recent publications reveal strong interdisciplinary trends: healthcare AI dominates with medication adherence prediction and surgical classification systems, while environmental applications feature flood-risk communication and drought analysis. His work increasingly integrates generative AI and LLMs across domains, demonstrating methodological innovation in federated learning, knowledge graphs, and explainable storytelling frameworks. Notable recognitions include: Best Student Paper Award, IEEE/ACM Connected Health Conference (2022) Best Student Paper Award, Body Sensor Networks Conference (2019) Data Challenge Win, IEEE Biomedical Health Informatics (2018) Best Paper Award, Body Area Networks Conference (2014) Best Demonstration Award, IEEE Wireless Health Conference (2014) Dr. Gong leads significant funded projects including a $2M CDC/NIOSH grant for first responder safety and $3M NSF funding for hydrologic research. As SAIL laboratory director, he mentors students in developing clinically deployed technologies for multiple sclerosis, dementia, and mental health. Future work focuses on scaling AI applications in chronic disease management and climate resilience through the Alabama AI Center. The SAIL laboratory (founded 2017) operates as a multidisciplinary hub developing wearable/mobile systems for health applications, with active collaborations across medical clinics and engineering departments for real-world deployment of behavior change interventions and movement analysis tools.
Yang Liu is a tenured Associate Professor at the Department of Management and Engineering , Linköping University, Sweden, and an Adjunct Professor at the University of Oulu, Finland. His expertise spans smart manufacturing, clean energy transition, and Industry 4.0 applications. He holds an M.Sc. and D.Sc. from the University of Vaasa, Finland. Research & Awards: Liu's work focuses on sustainable systems, decision support systems, and AI-driven energy efficiency. He has authored over 140 Web of Science publications, including top 0.1% ESI Hot Papers. He is ranked among the world's top 2% scientists (Stanford-Elsevier) and leads globally in 'big data analytics in manufacturing' and 'Industry 4.0-driven circular economy' research. Leadership & Projects: He leads projects like FlexSUS (EU Horizon 2020) and PERSEUS, developing tools for smart urban energy planning and 15-minute city models. He serves as Editor-in-Chief of Cleaner Engineering and Technology and Guest Editor for multiple journals. His research emphasizes bridging data science with sustainability challenges in manufacturing and energy systems. Key Achievements: Top-ranked in global citations, ESI Highly Cited Papers, and industry-driven sustainability frameworks. Grants: Leads EU-funded projects and collaborates with Siemens Energy on energy transition solutions. Labs & Teams: Part of the Environmental Technology and Management (MILJÖ) division and Unit for Product Service Innovation (MILJOPSI) at Linköping.
Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.
Daniel Wolpert is a Professor of Neuroscience at Columbia University , where he is also Vice-Chair of the Department of Neuroscience and a key member of the Zuckerman Mind Brain and Behavior Institute . Additionally, he holds a part-time position as Director of Research at the Department of Engineering, University of Cambridge, and is a Fellow of the Royal Society and the Academy of Medical Sciences . Education: Medical Doctor (1989), D.Phil. in Physiology from the University of Oxford (1992) Previous Positions: Lecturer at Sobell Department of Motor Neuroscience (Institute of Neurology), Professor of Engineering at University of Cambridge (2005–2018) Wolpert is a world leader in sensorimotor control , combining computational neuroscience , Bayesian inference , and robotic/virtual reality technologies to reverse-engineer how the brain generates movements. His work emphasizes the brain's role in reducing sensorimotor uncertainty through predictive modeling and has implications for understanding disorders like autism and Parkinson’s disease. His awards include: Royal Society Ferrier Medal (2020) Minerva Foundation Golden Brain Award (2010) Royal Society Francis Crick Prize Lecture (2005) Daniel Wolpert actively contributes to public science communication, including a 2011 TED Talk on the computational role of the brain in movement, and leads the Wolpert Lab at Columbia, which investigates the neural basis of decision-making , motor learning , and reinforcement learning in both healthy and clinical populations.
Suresh Krishna is an Associate Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on the neurophysiological and computational basis of sensory processing, attention, and eye movements, with applications to brain-machine interfaces and human health. He works with human subjects, non-human primates, and open datasets using in-vivo electrophysiology, eye-tracking, and computational modeling. Research interests include visual attention mechanisms, saccadic eye movement control, neural coding of motion perception, and the interplay between attention and decision-making. His work bridges basic neuroscience with translational applications such as improving neural prosthetics and understanding perceptual disorders. Recent work highlights how neural remapping processes during saccades underlie spatial perception, and how attention modulates neural activity patterns in visual cortex. The lab's publications reveal critical insights into the temporal dynamics of attentional shifts and their neural substrates, particularly in areas MT and MST. Dr. Krishna's team also investigates auditory temporal processing in the inferior colliculus, exploring correlations between neuronal responses to sound modulation. Their findings contribute to understanding how sensory systems encode temporal information across modalities. Research is conducted in the M2B3 Lab (http://m2b3.lab.mcgill.ca), which integrates experimental and computational approaches to study brain mechanisms underlying perception and action. No specific awards are listed, but ongoing work involves major contributions to primate neurophysiology and translational neuroscience.
Nathan W. Hudson is an Associate Professor in the Department of Psychology at Southern Methodist University (SMU) in Dallas, Texas. Previously, he received his Ph.D. in Psychology from the University of Illinois at Urbana-Champaign in 2016. His research focuses on personality psychology, particularly how people's personalities change across time and how individuals function in romantic relationships. He leads the Δ Lab at SMU, which investigates individual differences in human personality. Education: 2016 – Ph.D., Psychology, University of Illinois at Urbana-Champaign 2011 – M.A., Psychology, University of Illinois at Urbana-Champaign 2009 – B.A., Purdue University Nathan Hudson's primary research area is volitional personality change—people's desires and attempts to change their own personality traits. His groundbreaking research has shown that approximately 90% of people want to change aspects of their personality traits, and moreover, they may be able to find some degree of success in doing so. He also studies adult attachment styles and how people function in close relationships. Hudson's work suggests that attachment anxiety is linked to false memories, and that people's attachment styles can change over time. His research integrates both theoretical and applied perspectives, with implications for therapeutic interventions and personal development. Hudson's recent publications demonstrate a clear trajectory toward understanding the mechanisms of personality change and developing effective interventions. His work spans across multiple domains of personality psychology, with a particular emphasis on the Big Five personality traits, attachment theory, and well-being. A consistent theme throughout his research is examining how people's desires for change translate into actual personality growth. His work has increasingly focused on the practical applications of personality science, including developing measures and interventions that can help people achieve their desired personality changes. Scientific Awards: Goss-Lucas Award for Excellence in Teaching James Davis Fellowship Foundation for Personality and Social Psychology Heritage Dissertation Award Hudson actively mentors students in the Δ Lab at SMU, where they conduct research on personality change, attachment, and well-being. He has secured multiple grants to support his research on volitional personality change and the development of personality assessment tools. His lab has developed several psychological measures, including the Change Goals Big Five Inventory (C-BFI2) and its variants, which are freely available for academic research. Hudson also engages with the public through his TEDx talk "You Can Change Your Personality" and has been featured in Olga Khazan's book "Me, But Better," which applies his research to real-life settings. The Δ Lab, led by Hudson, is dedicated to understanding individual differences in personality and how people can intentionally change aspects of themselves. The lab values all individual differences among humans, recognizing that variance in human thoughts, feelings, and behaviors is adaptive and makes humanity resilient. The lab wholeheartedly supports the LGBTQ+ community and emphasizes that individual differences between humans are what personality science is all about.
David Armitage is the Lloyd C. Blankfein Professor of History at Harvard University, where he serves as Chair of the Committee on Degrees in Social Studies and teaches intellectual history and international history. He also holds affiliations with the Harvard Department of Government, Harvard Law School, and is an Honorary Professor at the University of Sydney and Queen's University Belfast. Previously, he chaired Harvard's Department of History (2012-14, 2015-16) and taught at Columbia University for eleven years before joining Harvard in 2004. Armitage was born in Britain and educated at the University of Cambridge and Princeton University. His academic journey includes: Undergraduate studies at University of Cambridge PhD at Princeton University Teaching position at Columbia University (1993-2004) Professorship at Harvard University (2004-present) Honorary positions at University of Sydney, Queen's University Belfast, and St Catharine's College, Cambridge Professor Armitage specializes in intellectual history, international history, and global history, with particular expertise in the history of political thought, empires, and international law. His scholarly approach emphasizes the longue durée perspective, seeking to understand historical phenomena across extended time periods rather than narrow chronological frames. He has been a leading voice in advocating for historians to engage with "big history" that spans centuries, arguing that contemporary challenges like climate change and economic inequality require historical understanding that transcends the short-term thinking prevalent in modern politics and policy. His extensive publication record demonstrates consistent engagement with foundational texts and concepts in political theory, declarations of independence, civil wars, and oceanic history. Armitage's work shows a clear trajectory toward increasingly global and interdisciplinary approaches, connecting intellectual history with legal, political, and environmental frameworks. His scholarship bridges early modern and contemporary history, examining how historical concepts continue to shape modern international relations and political thought. Armitage's significant contributions to historical scholarship have been recognized with prestigious awards: Caird Medal from the National Maritime Museum (2006) for "conspicuously important work ... of a nature that involves communicating with the public" Walter Channing Cabot Fellow from Harvard (2008) for "achievements and scholarly eminence in the fields of literature, history or art" LittD from Cambridge University (2015), the university's highest degree, for "distinction by some original contribution to the advancement of science or of learning" As an advisor and mentor, Armitage has guided numerous graduate students through doctoral programs at Harvard and previously at Columbia. His scholarly leadership extends to co-editing two major book series with Cambridge University Press ( Ideas in Context and Cambridge Oceanic Histories ), serving on the Steering Committee of the Center for Early Modern Political Thought at the Folger Shakespeare Library, and contributing to various academic organizations. His work has attracted significant research funding supporting his global historical investigations. Professor Armitage is deeply involved in collaborative scholarly initiatives, particularly through his work with the Harvard Academy for International and Area Studies, where he serves as a Senior Scholar. His research often involves interdisciplinary teams examining oceanic histories, international law, and global political thought. He has been instrumental in developing the "Cambridge Oceanic Histories" series, which brings together scholars from multiple disciplines to explore the historical significance of oceans as connective spaces rather than barriers.
Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.
Juergen Schmidhuber is Associate Professor at the Faculty of Informatics of Università della Svizzera italiana and a leading researcher at the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). He is also Chief Scientist at NNAISENSE, a company dedicated to building practical general-purpose AI. His work has profoundly influenced modern artificial intelligence, particularly through the development of Long Short-Term Memory (LSTM) networks in 1991, now deployed across billions of devices for speech recognition, machine translation, and virtual assistants. His research interests span Artificial Intelligence, Deep Learning, Recurrent Neural Networks, Universal AI, Meta-Learning, Algorithmic Information Theory, Artificial Curiosity, Robotics , and Low-Complexity Art . He has pioneered mathematically rigorous frameworks for self-improving AI systems and formal theories of creativity and beauty. His work bridges theoretical foundations with real-world applications in computer vision, natural language processing, and autonomous robotics. The recent articles reflect a consistent trajectory of innovation, combining deep theoretical insights with scalable machine learning architectures. His publications emphasize sequence modeling, universal learning, intrinsic motivation, and computational creativity , demonstrating both foundational contributions and industrial impact. From LSTM to Goedel machines, his work consistently targets the long-term goal of self-improving general AI. Scientific Awards: Numerous awards in AI and machine learning (specific names not listed) Schmidhuber leads a research group at IDSIA, where he mentors students and researchers in advancing the frontiers of AI. His lab has secured significant recognition and industrial collaboration, though specific grants are not detailed. He promotes the 'New AI'—general, sound, and relevant to physics—and continues to explore the convergence of intelligence, computation, and the universe. Labs and Teams: Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) NNAISENSE (as Chief Scientist)
John Serences is a Professor in the Department of Psychology at the University of California, San Diego (UCSD). He leads the Perception and Cognition Lab, which participates in the Neuroscience Graduate Program. His research focuses on how behavioral goals and attention influence perception, memory, and decision-making, employing techniques like psychophysics, computational modeling, EEG, and fMRI. Key projects explore serial dependence, neural adaptation in visual cortex, and the interplay between sensory processing and mnemonic storage. Recent work highlights mechanisms reconciling repulsive neuronal adaptation with attractive behavioral biases. Affiliations: Department of Psychology, UCSD; Neuroscience Graduate Program. Research Themes: Visual perception, working memory, decision-making, neuroimaging. His lab investigates neural dynamics underlying cognitive processes, with particular emphasis on how attentional modulations and stimulus history shape neural representations. Notable contributions include studies on adaptive sensory coding and the role of top-down signals in perceptual stability.
Prof. Torsten Wolfgang Kuhlen serves as a Universitätsprofessor at RWTH Aachen University, leading the Teaching and Research Area for Virtual Reality and Immersive Visualization within the Department of Computer Science. He is affiliated with Chair of Computer Science 12 (High Performance Computing), the Visual Computing Institute, and remains an integral part of the RWTH IT Center where his research group operates one of the world's largest Virtual Reality laboratories including the 30 sqm aixCAVE visualization chamber. The group maintains strong connections with Computational Science & Engineering Division, National High Performance Computing Center for Computational Engineering Science (NHR4CES), and VR in Science and Industry Network NRW e.V. Prof. Kuhlen's research spans virtual reality, immersive visualization, and multimodal 3D user interfaces with applications across simulation science, production technology, neuroscience, and medicine. His work combines basic research on advanced methods and algorithms with interdisciplinary collaborations involving RWTH Aachen institutes, Forschungszentrum Jülich, and industry partners. Recent publications demonstrate strong focus on audiovisual perception, immersive analytics, collaborative virtual environments, and practical VR applications in education and manufacturing. His research group has produced significant work on listening effort in virtual environments, immersive authoring techniques, and VR applications for scientific visualization. Notable projects include VRScenarioBuilder for automated vehicle testing and applications in monitoring additive manufacturing processes. The group actively participates in major conferences including IEEE VIS and EuroVis, with several award-winning contributions. Prof. Kuhlen has advised PhD students including Martin Bellgardt who recently completed his doctoral degree on "Increasing Immersion in Machine Learning Pipelines for Mechanical Engineering". The research group maintains state-of-the-art VR infrastructure including the aixCAVE facility which is open to all RWTH research groups.
