Andy Hargreaves is an internationally recognized scholar and advisor in education, holding dual roles as Adjunct Professor at Boston College and Visiting Professor at the University of Ottawa. He advises governments including Ontario, Scotland, and New Brunswick on educational policy and system reform. His work focuses on leadership, well-being, student engagement, and systemic educational change. Hargreaves co-leads the ARC Education Project and founded CHENINE, a Canadian research initiative advancing pedagogical innovation. Research Interests: Leadership from the Middle Teacher Well-Being and Professional Capital Identity Development in Schools Play-Based Learning Crisis Management in Education Awards: 2023 Canadian EdTech Awards Educator of the Year 2023 RHSU Edu-Scholar #16 2022 National Academy of Education Member 2015 Grawemeyer Award Key Projects: ARC Education Project (7 nations collaboration) CHENINE (Canadian educational innovation hub) Canadian Playful Schools Network Labs/Teams: Directs CHENINE, collaborates through ARC networks, and leads research on global educational transformation.
Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.
Martha Stiegman is an Associate Professor at the Faculty of Environmental and Urban Change, York University. Her research integrates Indigenous knowledge, food sovereignty, and arts-based methodologies to address issues of social, environmental, and disability justice. She is actively engaged in community-based research and public scholarship in Toronto and Mi’kma’ki (Nova Scotia). Her educational background includes a PhD from Concordia University’s Special Individualized Program and a BA in English Literature & Political Science from McGill University. This interdisciplinary foundation supports her work at the intersection of activism, research, and art. Stiegman’s research focuses on three interconnected domains: Indigenous/settler treaty relations, food sovereignty and justice movements, and participatory video and arts-based research. She emphasizes decolonizing methodologies and community-led knowledge production. Her work explores how arts-based approaches can deepen dialogues across communities and strengthen collective action for justice. Her recent publications and multimedia projects demonstrate a strong trend toward interdisciplinary, community-engaged scholarship that bridges Indigenous epistemologies, environmental justice, and disability justice. She frequently uses film, digital storytelling, and public art to mobilize knowledge and challenge colonial narratives. Co-creator of A Treaty Guide for Torontonians (2022) Lead on the Polishing the Chain project exploring Toronto’s treaty relationships Editor of the forthcoming Anti Colonial Food Systems (Routledge) Active collaborator with Indigenous scholars and artists including Dr. Sherry Pictou, Ange Loft, and Elder Kerry Prosper Stiegman has been involved in significant research grants such as the Atlantic Aboriginal Health Research Program. While specific advisees are not listed, her collaborative projects suggest active mentorship and supervision. She does not appear to lead a formal lab but works within research collectives and community partnerships.
Carolyn Parkinson is an Associate Professor at the University of California, Los Angeles (UCLA), holding the Bernice Wenzel and Wendell Jeffrey Term Endowed Chair in Cognitive Neuroscience. Her research integrates social psychology with computational neuroscience to explore how the human brain represents, navigates, and shapes social environments. University: University of California, Los Angeles (UCLA) Academic Rank: Associate Professor Research Focus: Social and Affective Neuroscience, Social Network Analysis, Neural Mechanisms of Psychological Distance At the Computational Social Neuroscience Lab , Parkinson investigates: Neural encoding of social network structures Shared mechanisms for spatial, temporal, and social distance perception Computational modeling of social cognition Functional MRI analysis of social relationships Her work reveals that: Resting-state brain connectivity predicts social proximity Multivoxel patterns decode social knowledge representations Old cortical structures repurpose spatial processing for social cognition Neural population coding transcends historical phrenology-based approaches Notable awards include the Bernice Wenzel and Wendell Jeffrey Term Endowed Chair. She employs machine learning and social network theory to analyze distributed brain activity patterns, advancing understanding of human social behavior and cognition.
Nathan Youngblood is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh , with a secondary appointment in the Department of Physics and Astronomy . His research focuses on reconfigurable photonic materials and devices for energy-efficient artificial intelligence applications. Educational Background: PhD in Electrical Engineering from the University of Minnesota Postdoctoral research at the University of Oxford (2017–2019) His work explores photonic in-memory computing, neuromorphic systems, and phase-change materials to minimize computing latency and energy consumption. Recent publications highlight advancements in magneto-optical non-reciprocity, coherent crossbar arrays, and plasmonic-enhanced phase-change devices. Scientific Awards: NSF CAREER Award (2024) AFOSR Young Investigator Award (2024) William Kepler Whiteford Faculty Fellowship (2024) Dr. Youngblood's lab develops photonic accelerators like LightML and LightBulb for machine learning, emphasizing scalable integration and novel material applications in silicon photonics.
Ethan Mollick is the Ralph J. Roberts Distinguished Faculty Scholar, Rowan Fellow, and Associate Professor of Management at the Wharton School of the University of Pennsylvania. He serves as Co-Director of the Generative AI Labs at Wharton, where he researches AI's impact on work, entrepreneurship, and education. His academic background includes a PhD and MBA from MIT's Sloan School of Management and a bachelor's degree from Harvard University. Mollick's research spans artificial intelligence applications in business and education, entrepreneurship dynamics, and innovation management. He explores how generative AI transforms classroom education through simulations like PitchQuest, and investigates startup funding disparities with a focus on gender representation. His work on the 'jagged technological frontier' demonstrates how humans integrate AI capabilities through Centaur and Cyborg approaches. His publications reveal consistent focus on practical AI implementation, with recent work examining prompt engineering for diverse idea generation, AI-assisted teaching strategies, and gender representation tipping points in venture capital. The research shows increasing emphasis on educational applications since 2022, coinciding with the ChatGPT breakthrough. MBA Professor of the Year Award, Poets & Quants (2024) Named to TIME Magazine's Most Influential People in Artificial Intelligence ASQ Award for Scholarly Contribution (2024) Greif Research Impact Award (2020) McGraw-Hill/Academy of Management Innovation in Entrepreneurship Pedagogy Award (2016) As Co-Director of Wharton's Generative AI Labs, Mollick leads prototype development and research on human-AI collaboration. His teaching includes Technology Strategy, Entrepreneurship, and Innovation courses where he implements AI simulations. He has advised numerous organizations and co-founded a startup prior to academia, bringing practical experience to his research on solo versus team ventures. Mollick directs Wharton Interactive's game development initiatives, creating educational simulations including PitchQuest (AI-powered VC simulator), The Saturn Parable (crisis management), and The Entrepreneurship Game. His lab work focuses on creating scalable AI educational tools that provide personalized learning experiences through simulated practice environments.
Marco Pedersoli serves as an Assistant Professor at École de technologie supérieure (ETS) in Montreal since February 2017, where he leads research in computer vision and machine learning. His work focuses on reducing computational costs and annotation requirements for deploying vision algorithms on embedded devices, positioning ETS at the forefront of Montreal's AI ecosystem. His academic journey includes: Ph.D. from Autonomous University of Barcelona (UAB) under Jordi Gonzàlez and Juan José Villanueva Post-doctoral research at INRIA Grenoble with Cordelia Schmid and Jakob Verbeek (2015-2016) Research at KU Leuven with Tinne Tuytelaars (2012-2015) Dr. Pedersoli's research tackles deep learning bottlenecks through weakly-supervised methodologies and computational efficiency innovations . His three core projects address: Reduced Supervision : Developing weakly/semi-supervised learning for images, video, audio and text Exploration Learning : Optimizing data selection in unstructured environments Efficient Computation : Accelerating deep learning training and inference These efforts enable vision algorithms to run on resource-constrained portable devices. Publication trends (2014-2022) reveal consistent focus on weak supervision (60% of works) and computational efficiency (30%), with recent expansion into medical imaging and multimodal emotion recognition. Key venues include CVPR, ICCV, NeurIPS and ECCV. His accolades include: Best Paper Award at ICIAR 2019 NVIDIA Titan X Pascal hardware donation Dr. Pedersoli actively mentors 18 graduate students across PhD and MSc programs, with notable placements at Huawei and Radio Canada. His lab secures competitive tax-free funding for projects with international collaborations, including Element AI and European institutions. Current openings emphasize Python/C++ proficiency and deep learning expertise. He leads a dynamic research group at ETS developing open-source tools for Roi-Pooling, weakly-supervised detection, and 3D object recognition, maintaining active GitHub repositories with community contributions. Recent WACV 2023 acceptances demonstrate ongoing productivity following medical leave.
Jenny Kao-Kniffin is a Professor in the Horticulture Section of the School of Integrative Plant Science at Cornell University. Her research focuses on the belowground ecology of horticultural landscapes, particularly the ecology and management of invasive plants and weeds in horticultural landscapes, wetlands, and urban ecosystems. She applies concepts from microbial ecology to understand how soil microorganisms impact plant populations both beneficially (aiding in plant growth and fitness) and negatively (keeping populations in check). Dr. Kao-Kniffin's research interests include: Weed science and ecological management of weeds Urban ecology and urban agriculture Rhizosphere biology and plant-microbe interactions Soil microbiome selection and manipulation Ecological approaches to sustainable agriculture Her work centers on three main research areas: selection of rhizosphere microbiomes that modulate plant traits, identifying functional roles of microbiomes that mediate plant growth, and assembly of plant-microbial communities that enhance ecosystem services. She has demonstrated that microbiomes can be manipulated to alter flowering time in plants and has developed ecological approaches for weed management through soil carbon amendments. Her recent publications reveal a strong focus on urban soil microbiomes, nitrogen cycling in agroecosystems, and the application of microbial ecology to sustainable agriculture. The research spans from fundamental plant-microbe interaction studies to practical applications in urban agriculture and weed management, with particular emphasis on how soil amendments and microbial communities can be leveraged for ecological management of plant systems. Notable scientific achievements include: The White House Presidential Early Career Award for Scientists and Engineers (PECASE), 2019 Weihenstephan Science Award, International Collaboration for Early Career Scientists 2017 Cornell University CALS Award for Excellence in Mentoring Undergraduate Students in Independent Research 2013 Dr. Kao-Kniffin actively mentors graduate students and has developed extension programs focused on assisting public and private audiences with methods to manage weedy and invasive plants in horticultural landscapes. Her lab has developed a web-based software program that allows users to select weed management methods based on conventional or organic preferences. She teaches PLSCI 4900: Reflection on Plant Sciences Experiential Learning and maintains an active research program with several ongoing projects in urban agriculture, particularly working with New York City farmers to construct clean soil from local materials.
Tariq Iqbal is an Assistant Professor at the University of Virginia , with joint appointments in the Department of Systems and Information Engineering and Department of Computer Science . He leads the Collaborative Robotics Lab (CRL) , specializing in human-robot teams and embodied AI . Previously, he was a Postdoctoral Associate at MIT's CSAIL , advised by Prof. Julie Shah , and earned his Ph.D. in Computer Science from University of California San Diego (UCSD) under Prof. Laurel Riek . Ph.D. in Computer Science, University of California San Diego (2017) M.S. in Computer Science, University of Texas at El Paso (2012) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2007) His research lies at the intersection of artificial intelligence and robotics , focusing on human-robot collaboration in dynamic environments. Key areas include motion prediction , multimodal fusion , trust modeling , and collaborative learning . His work integrates cognitive science and deep learning to enhance robotic fluency in naturalistic settings. Recent publications (2023–2025) highlight advancements in human-robot team dynamics , multimodal dataset creation , and motion prediction algorithms . Notable works include Energy-Based Transformers for scalable AI, PoseTron for motion prediction, and Accessible Navigation Mapping for assistive robotics. These contributions span trust modeling , cloud robotic infrastructure , and safety in close-proximity collaboration . National Science Foundation (NSF) CAREER Award Air Force Office of Scientific Research (AFOSR) Young Investigator Program (YIP) Award Commonwealth Center for Advanced Manufacturing (CCAM) Innovation Award As faculty, he has secured grants from NSF and AFOSR , mentored research students, and taught courses like Stochastic Modeling I (SYS 6005) and Robots and Humans (SYS 4582/6465, ECE 4502/6465, CS 6465) . His prior industry roles at IBM Watson Lab and Grameenphone Ltd. inform his applied research in telecom infrastructure and cognitive robotics . He leads the Collaborative Robotics Lab (CRL) at UVA, which develops multimodal datasets , real-time coordination algorithms , and adaptive pathfinding systems . Current projects explore human motion prediction , team synchrony , and embodied question-answering , reflecting his commitment to advancing human-robot fluency and contextual AI .
Ziran Wang is an Assistant Professor in the Department of Civil Engineering at Purdue University's College of Engineering, appointed as new faculty in 2022. His research bridges digital twin technologies, autonomous driving systems, and human-machine interaction to advance intelligent transportation solutions. Ph.D. in Mechanical Engineering, University of California, Riverside Prior role: Principal Researcher at Toyota North America His work focuses on creating personalized autonomous driving experiences through machine learning, emphasizing safety and efficiency in real-world applications. Key areas include multimodal large language model integration, federated learning for privacy-preserving data sharing, and cooperative perception frameworks. He develops novel approaches for digital twin-based traffic simulation, medical emergency detection in vehicles, and human behavior modeling in complex urban environments. Analysis of his 2024-2025 publications reveals a dominant trend toward generative AI applications in autonomous driving, particularly for perception-prediction-planning integration and real-world validation. His research increasingly incorporates digital twins for safety-critical testing and explores medical applications through in-vehicle health monitoring systems. Dr. Wang advises graduate students including Wenhui Huang and leads the Purdue Digital Twin Lab, which develops advanced simulation and testing platforms for autonomous systems. His lab maintains strong industry partnerships with Toyota for real-world deployment and validation of research成果.
Dr. Matthias Gruber is a Reader (Associate Professor) in Cognitive Neuroscience at Cardiff University's School of Psychology. He leads the Cardiff University Motivation and Memory Lab at CUBRIC, where his research investigates the neuroscience of motivation and its effects on memory using multimodal neuroimaging techniques (structural/functional MRI, M/EEG). His work focuses on how intrinsic motivational states like curiosity enhance learning and memory consolidation. Education includes: PhD in Cognitive Neuroscience, University College London (2007-2011) Research Assistant position at University of Regensburg (2003-2006) Research explores: Neural mechanisms of curiosity and motivation Effects of reward anticipation on memory encoding Hippocampal-prefrontal interactions during learning Developmental aspects of curiosity from childhood to adulthood Real-world applications of motivation research His publications consistently demonstrate how motivational states modulate memory systems, with recent work focusing on spatial exploration dynamics and educational applications. Awards and honors: Sir Henry Dale Fellowship (Wellcome/Royal Society, 2019-2024) Laird Cermak Award (2016) Michael S. Gazzaniga Prize for Cognitive Neuroscience (2015) Elected to Memory Disorders Research Society (2017) Research funding includes major grants from Wellcome Trust, Royal Society, and European Commission. He leads the Motivation and Memory Lab at CUBRIC and is currently accepting expressions of interest from potential research trainees.
Ralph Jimenez is an Adjunct Professor of Chemistry and Institute Fellow at JILA, University of Colorado Boulder. He holds a Ph.D. from the University of Chicago (1996) and completed postdoctoral work at the University of California, San Diego (1997-1998), followed by research at The Scripps Research Institute (1998-2003). His research focuses on quantum spectroscopy and photophysics of fluorescent proteins, leveraging quantum optics to enhance spectroscopic sensitivity and developing genetically encoded biomarkers with improved photophysical properties. Key achievements include fluorescence-lifetime-based methods to engineer brighter fluorescent proteins and machine-learning approaches to improve photostability. His awards include the Arthur S. Flemming Award (2017) and U.S. Department of Commerce Gold Medal (2017). His group's work integrates quantum engineering with biophysical studies, targeting real-world applications in molecular imaging and materials science. The Jimenez Group operates labs at JILA (B117, B119, B121) and collaborates on projects involving entangled photons, two-photon absorption, and ultrafast spectroscopy. Research themes include quantum-enhanced spectroscopy for complex systems and overcoming limitations in fluorescent protein imaging through physical chemistry strategies. His lab develops novel instrumentation, including microfluidic sorting systems and tabletop X-ray spectroscopy platforms, to advance biomarker engineering and environmental monitoring.
Dr. Sander Los is an Associate Professor at the Faculty of Behavioural and Movement Sciences (Department of Cognitive Psychology), Vrije Universiteit Amsterdam. He earned his PhD in 1994 with a thesis on 'On the origin of mixing costs: Exploring information processing in pure and mixed blocks of trials' under Prof. Andries Sanders. His research focuses on temporal dynamics of preparatory processes, co-developing the formalized Multiple Trace Theory (fMTP) to explain temporal preparation across time scales (seconds to days). His work integrates cognitive psychology, neuroscience, and computational modeling to explore attentional mechanisms, statistical learning, and spatiotemporal dynamics. Education: PhD in Cognitive Psychology (VU Amsterdam, 1994), postdoctoral research at VU Amsterdam, progressing to Assistant Professor before his current role. Key research areas include visual attention, response inhibition, and long-term memory. He has published over 40 peer-reviewed articles and serves on editorial boards for journals like Attention, Perception, and Psychophysics and Acta Psychologica . Research Interests: His studies investigate how humans prepare for upcoming events temporally and spatially, with recent work on statistical learning guiding visual attention and computational frameworks for temporal preparation. Collaborations emphasize interdisciplinary approaches to understanding attention allocation and neural underpinnings of timing. Grants & Advising: No explicit grants listed, but active in training students (1 supervised PhD thesis). His courses include Methodology, Research Methods, and Practical Skills for Researchers at VU Amsterdam. Labs/Teams: Works closely with colleagues on the fMTP model and statistical learning projects, emphasizing team-based computational and experimental psychology.
James Tung is an Associate Professor at the University of Waterloo’s Faculty of Engineering, Department of Mechanical and Mechatronics Engineering. His research focuses on assistive technology, rehabilitation engineering, and mobility solutions for individuals with disabilities. He leads the Neural and Rehabilitation Engineering (NRE) Lab, which develops wearable sensors, robotics, and machine learning tools to enhance mobility and monitor motor rehabilitation. He teaches courses including BME 355 (Physiological Systems Modelling), BME 540 (Neural and Rehabilitation Engineering), and ME/MTE engineering modules. The lab collaborates with clinical and industry partners to translate research into practical solutions, addressing real-world mobility challenges and aging demographics. His research spans real-world gait analysis, fall risk assessment, and prosthetic design, with a focus on pediatric neurodevelopmental disorders and elderly mobility. The NRE Lab emphasizes interdisciplinary work, combining biomechanics, robotics, and data science to improve healthcare outcomes. Lab Alumni: Includes researchers like Robin Murdock (Myant Inc.), Andrew Hart, and Raj Senthilkumar, contributing to prosthetics and gait analysis. Partnerships: Engages clinical and industry stakeholders for knowledge translation and commercialization. Current projects include developing smart rollators, biofeedback prosthetics, and sensor-based assessment tools to address mobility limitations in aging populations and individuals with disabilities.
Radu Iovita is an Associate Professor in the Department of Anthropology at New York University. Previously, he held positions at the University of Tübingen (until 2023) and the Leibniz Research Institute for Archaeology in Germany. His research focuses on Paleolithic archaeology, human-environmental interactions, and stone tool technology, with a specific emphasis on the Eurasian loess steppe. He leads the EU-funded PALAEOSILKROAD project in Kazakhstan, investigating human dispersals during the Late Pleistocene. His Anthrotopography lab combines microscopic analysis of tool use and remote sensing to reconstruct past landscapes. Education: PhD in Anthropology (University of Pennsylvania, 2008), MPhil in Archaeology (University of Cambridge, 2002), AB in Anthropology (Harvard University, 2001). Key grants include an ERC Starting Grant (2017–2022). Research interests span lithic technology, experimental archaeology, and geoarchaeological methods. Recent work includes discoveries of Paleolithic sites in Kazakhstan, studies on Neanderthal adhesive use, and AI-driven analysis of use-wear patterns. Collaborations involve institutions like ETH Zurich and the University of Tübingen. He is actively involved in field projects in Central Asia and lab-based experimental studies.
