Aishwarya Ganesan is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign. Her research focuses on distributed systems, storage systems, and fault tolerance mechanisms, with emphasis on high-performance computing and datacenter infrastructure. She leads projects addressing challenges in replicated storage, consensus protocols, and system resilience. Her work explores fault tolerance in disaggregated datacenters, log abstractions for low-latency applications, and novel replication strategies for modern storage systems. She has developed frameworks like LazyLog and IONIA to improve system efficiency and reliability. Her research also extends to automatic reliability testing for cluster management controllers and analyzing distributed storage vulnerabilities. Key contributions include demonstrating how redundancy alone does not guarantee fault tolerance, and proposing consistency-aware durability mechanisms for storage systems. She received the NSF CAREER Award in 2024 for her research on storage-aware fault tolerance. Her work spans 21 peer-reviewed publications, with notable contributions in conferences like SOSP, EuroSys, and FAST. Current projects investigate fault tolerance in emerging memory technologies and system recovery protocols for consensus-based storage.
Ju Hui Judy Han is an Associate Professor in Gender Studies at the University of California, Los Angeles, with additional affiliations at the Center for Korean Studies, Center for the Study of Women, and Asia Pacific Center. Her office is located in 1117 Rolfe Hall at UCLA. As a cultural geographer, Professor Han is committed to building critical and transnational conversations concerning gender, sexuality, and activism, regularly contributing to community-based projects and public events both on campus and beyond. Professor Han received her Ph.D. in Geography from UC Berkeley and her B.A. in English and Women's Studies from UC Berkeley. Her educational background bridges humanities and social sciences, providing a strong foundation for her interdisciplinary research. Her research interests span (Im)mobilities, Religion and difference, conservatism, LGBTQ/queer politics and activism, Comics and graphic novels, Korean studies, and Cultural geography. Professor Han approaches these topics through a critical lens that emphasizes transnational perspectives, particularly focusing on South Korea and the Korean diaspora. Her work often examines how power operates through spatial arrangements and how marginalized communities navigate and resist dominant structures. She has developed innovative approaches to studying activism through comics and graphic nonfiction, creating accessible yet theoretically rich analyses of complex social phenomena. Professor Han's publications reveal consistent engagement with queer politics in South Korea, religious movements, and transnational activism. Her work shows a progression from analyzing specific case studies to developing broader theoretical frameworks about resistance, solidarity, and spatial politics. The recurring themes across her publications include the intersection of religion and queer politics, the spatial dimensions of activism, and the transnational connections between social movements. UCLA Center for the Study of Women/Barbra Streisand Center, inaugural Barbra Streisand Fellowship on Truth in the Public Sphere Podcast Support Grant, University of California Humanities Research Institute (UCHRI), 2021-22 Society of Hellman Fellows Award, UCLA, 2021-22 UCLA Faculty Career Development Award, 2018-2019 Co-Applicant, 'Protesting Publics in South Korea,' SSHRC Insight Grant (PI: Jennifer Jihye Chun), 2015-2020 Co-Investigator, 'Urban Aspirations in Seoul: Religion and Megacities in Comparative Studies,' Max Planck Institute, 2011-2017 Professor Han actively contributes to public discourse through media appearances and community engagement. She has received significant research funding supporting her work on South Korean protest movements and urban religious dynamics. Her teaching portfolio is diverse, including the Gender Studies undergraduate core class on power (102), senior capstone seminars (187), elective courses on transnational feminist politics (131) and comics and graphic nonfiction (185), as well as graduate seminars on feminist geographies, queer temporalities, and research design.
Michelle Daigle is an Assistant Professor at the University of Toronto, cross-appointed with the Centre for Indigenous Studies. Her work bridges Indigenous geographies and decolonial theory through 20 years of community collaborations. PhD from the University of Washington Indigenous (Cree) scholar from Constance Lake First Nation Focus on Indigenous resurgence against colonial capitalist violence Daigle's research explores Indigenous geographies and ecologies , examining how Indigenous communities navigate colonial frameworks. Her collaborative work with Dr. Magie Ramirez develops grounded theories of decolonial geographies, emphasizing water governance, food sovereignty, and relational land-based practices. Daigle's publications reveal a trajectory analyzing spatial dimensions of Indigenous self-determination and critiques of reconciliation discourse. Her work spans journals like Environment and Planning D and The Journal of Peasant Studies , focusing on decolonial methodologies and Indigenous governance.
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
Giorgio Ascoli is a University Professor in the Department of Bioengineering at George Mason University, where he has been since 1997. He is the Founding Director of the Center for Neural Informatics, Structures, & Plasticity (CN3) and Founding Editor-in-Chief of the journal Neuroinformatics . His affiliations span computational neuroanatomy, neuroinformatics, and hippocampal modeling. Education : PhD in Biochemistry and Neuroscience (1996), Scuola Normale Superiore; MS in Chemistry and Biochemistry (1993), Pisa University; BS in Chemistry and Physics (1991), Scuola Normale Superiore. Dr. Ascoli investigates the relationship between brain structure, activity, and function from cellular to circuit levels. His research focuses on anatomically plausible neural networks to model mammalian brains, particularly the hippocampus, with implications for understanding human memory and consciousness . He pioneered computational neuroanatomy, developing tools like L-Neuron for neuronal shape modeling and curating NeuroMorpho.Org , a central repository for digitally reconstructed neurons. His recent publications emphasize neuronal classification , connectome analysis , and biologically informed machine learning . Awards include the 2012 Outstanding Faculty Award (Virginia), 2022 AIMBE fellowship , and 2023 Presidential Faculty Excellence Awards . He has mentored over 20 graduate students and postdoctoral fellows, with funding from NIH, NSF, DARPA, and private foundations. Scientific Contributions : Over 137 peer-reviewed articles, 4 patents, 2 authored/edited books, and leadership in NeuroMorpho.Org and Hippocampome. Grants : $20M+ in cumulative funding, including NIH R01s, NSF BRAIN EAGERs, and Burroughs-Wellcome Trust support. Labs : Leads the Computational Neuroanatomy Group within CN3, focusing on hippocampal modeling, neuronal morphology, and consciousness theories.
Dr. Feras Dayoub is a Senior Lecturer at the School of Computer and Mathematical Sciences (Faculty of Sciences, Engineering and Technology) at the University of Adelaide , specializing in Embodied AI and Robotic Vision within the Australian Institute for Machine Learning (AIML) . He co-directs the CROSSING French-Australian laboratory for human-autonomous agent teaming and holds an Adjunct position at the Queensland University of Technology (QUT) , serving as an Associate Investigator at its Centre for Robotics . Previously, he was a Chief Investigator at the ARC Centre of Excellence for Robotic Vision . His research focuses on advancing reliable deployment of computer vision and machine learning on mobile robots in real-world environments. Applied projects include agricultural automation , environmental conservation , and autonomous infrastructure monitoring . He has published extensively on topics like object detection , domain adaptation , 3D representation learning , and vision-language navigation , with a particular emphasis on robustness in dynamic and partially observed environments. Dr. Dayoub is also an educator specializing in programming , computer vision , and robotic perception . He contributes to open-source robotics research through tools like AARK (Autonomous Racing Toolkit) and has led teams developing solutions for precision agriculture (e.g., Deepfruits fruit detection system) and environmental monitoring (e.g., Crown-Of-Thorns starfish detection ). Key Collaborations : CROSSING Lab, QUT Centre for Robotics Research Themes : Embodied AI, Robust Perception, Domain Adaptation
Stephanie Gil is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences. Her research focuses on artificial intelligence, robotics, and distributed systems, particularly addressing challenges in multi-agent coordination, resilience to adversarial attacks, and wireless communication for autonomous systems. She leads the REACT Lab, advancing research in resilient multi-robot networks and cyber-physical systems. Her work integrates machine learning, control theory, and wireless sensing to solve problems such as whale tracking via autonomous robots, proactive multi-robot routing, and decentralized exploration without explicit information exchange. She has received prestigious awards, including the DARPA Young Faculty Award (2024) and the Amazon Research Award (2021). Key research areas include resilient distributed optimization, trust-centered coordination in multi-agent systems, and leveraging wireless signals (e.g., WiFi-CSI) for sensing and bearing estimation. Her contributions span both theoretical frameworks and practical implementations, with a focus on real-world applications like autonomous rideshare routing and environmental monitoring. Dr. Gil’s research also explores trust and cybersecurity in dynamic networks, with publications on crowd vetting, malicious robot detection, and adaptive communication strategies. She collaborates on interdisciplinary projects, such as Project CETI, combining AI and robotics for ecological studies.
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.
Keigo Kobayashi is an Associate Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, Department of Architecture. He has served in this position since 2016, previously holding the rank of Assistant Professor from 2012 to 2016. His professional journey includes significant experience at the Office for Metropolitan Architecture (OMA) in Rotterdam, where he worked as a Senior Architect and Project Architect from 2007 to 2012. His educational background includes a Master of Architecture II from Harvard University's Graduate School of Design (2005), a Master of Architecture from Waseda University's Graduate School of Science and Engineering (2003), and a Bachelor's degree in Architecture from Waseda University's School of Science and Engineering (2002). Kobayashi's research focuses on architectural planning and city planning, with particular interests in food-related architecture, spatial behavior, and sustainable design. His work explores the intersection of architecture with everyday life, examining how spatial configurations influence human behavior and community formation. Recent research has investigated food systems in urban contexts, playful approaches to spatial design, and the relationship between architectural form and environmental performance. His publications demonstrate a strong focus on practical applications of architectural theory, with projects spanning from food truck design in Shodoshima to zero-energy housing solutions and innovative approaches to architectural education. His work shows a consistent interest in how architecture can respond to contemporary social challenges while maintaining theoretical rigor. Excellence in Concrete Construction Award 2019, American Concrete Institute (ACI), Qatar National Library / OMA Kobayashi actively contributes to architectural education through various committee memberships, including serving as Chief of the Subcommittee on Strategies for International Compatibility in Architectural Education at the Architectural Institute of Japan and leading the Caberra Accord Correspondence Subcommittee at the Japan Accreditation Board for Engineering Education. His teaching portfolio at Waseda University is extensive, covering architectural design studios from undergraduate to doctoral levels. He leads several research initiatives, including the Wakusei Project in Tosa, Kochi, NPO PLAT (Platform for Architectural Thinking), and the European Thinkbelt/McDonald's Radio University project which represents an innovative approach to architectural education and community engagement, particularly in contexts of migration and cultural exchange.
Dr. Yanqing Hu is an Associate Professor at the Department of Statistics and Data Science, School of Science, Southern University of Science and Technology (SUSTech). With a Ph.D. in Systems Theory from Beijing Normal University (2011) and postdoctoral experience at the Levich Institute, City University of New York (2011-2013), his work focuses on big data analysis of complex systems, particularly in social media dynamics, network resilience, and graph neural network applications. Ph.D.: Beijing Normal University (Systems Theory, 2011) Postdoctoral: Levich Institute, CUNY (2011-2013) Research spans complex network analysis, information spreading mechanisms, and predictability of network structures. His work combines theoretical frameworks with real-world applications in social networks, infrastructure systems, and brain connectivity. Recent publications explore information percolation in social media, resilience quantification in interdependent networks, and intrinsic structure predictability. These studies appear in high-impact journals like Nature Human Behaviour (IF: 24.3), Nature Communications (IF: 17.7), and PNAS (IF: 10). World AI Conference Youth Outstanding Paper Nomination Beijing Outstanding Doctoral Dissertation Award Guangdong Special Support for Young Talents Guangdong Outstanding Youth Fund Collaborations include leading researchers from Boston University, King's College London, and Shenzhen-Hong Kong Institute of Microelectronics. His work informs network defense strategies and efficient navigation mechanisms in complex systems.
Denise Head is Professor of Psychological & Brain Sciences and Associate Chair at Washington University in St. Louis, with an additional appointment as Associate Professor in Radiology. Her research integrates cognitive neuroscience and neuroimaging to study cognitive aging and Alzheimer's disease. PhD, University of Memphis MS, University of Memphis BS, University of New Orleans Her research focuses on age-related cognitive changes and their neural underpinnings. Key areas include spatial navigation deficits in aging, the role of lifestyle factors (exercise, sleep, stress) in brain aging, and interventions to support cognitive function in older adults. She uses virtual reality, mobile eye-tracking, and neuroimaging techniques such as fMRI and DTI. The recent publications highlight a consistent trajectory in cognitive neuroscience and aging research, with emphasis on neuroimaging biomarkers, structural brain changes, and cognitive performance in normal and pathological aging. Her work bridges psychology, neurology, and radiology, contributing to early detection and understanding of Alzheimer's disease. Scientific Awards: No awards listed in the provided text. Dr. Head advises graduate students and leads a research lab focused on cognitive aging, though specific student names are not listed. Her lab investigates mediators of brain aging and develops methods to support spatial navigation in older adults. While specific grants are not mentioned, her ongoing research and recent publications suggest active external funding. She leads a research team in the Department of Psychological & Brain Sciences, utilizing advanced neuroimaging and behavioral methods to study aging and dementia. The lab integrates real-world and virtual experimental designs to understand spatial cognition and brain health in older populations.
Yang (Gilbert) Ye is an Assistant Professor in the Department of Civil and Environmental Engineering at Northeastern University, joining in January 2025. His research focuses on human-AI/robot teaming, automation in engineering, and assistive technologies, with a particular emphasis on human-centric robotics and sensorimotor processes. He holds a PhD in Civil Engineering from the University of Florida (2024), advised by Dr. Eric Jing Du. **Affiliations**: Member of ASCE, IEEE, and HFES. His work integrates VR/AR, robotics (e.g., drones, exoskeletons), and AI to enhance civil engineering workflows and workforce training. He leads the Ye Lab, actively recruiting PhD students and postdocs with coding experience (Python/C++/C#) and backgrounds in engineering or computer science. **Key Research Themes**: Human-robot interaction, construction automation, exoskeleton training, and delayed feedback mitigation in teleoperation. Over 20 peer-reviewed publications in journals like ASCE JoCEN, IEEE Access, and Advanced Engineering Informatics. **Lab Opportunities**: PhD/postdoc applicants require strong academic records (GPA ≥3.5) and coding skills. Undergrad/master students can apply for thesis/research roles. Funding covers tuition, insurance, and stipends.
Shashi Shekhar is a Professor at the University of Minnesota, holding the distinguished titles of McKnight Distinguished University Professor and Distinguished University Teaching Professor. He serves as the ADC/CSE Chair and Director of the AI-LEAF Institute within the Department of Computer Science at the College of Science and Engineering. His research interests span multiple areas of spatial computing including spatial data science, spatial data mining, spatial databases, Geo-AI, and Geographic Information Systems (GIS). His work has focused on developing scalable algorithms for eco-routing, evacuation route planning, and spatial pattern mining. He has made significant contributions to the field through his Spatial Databases textbook, the Encyclopedia of GIS which has seen over 192,918 downloads in 2017, and a spatial computing book for professionals. His research group has produced numerous PhD graduates dating back to 1993 through 2023. Analysis of his recent publications reveals a strong focus on applying spatial computing to critical societal challenges including climate change mitigation through the AI-LEAF Institute, pandemic response through mobility data analysis, and sustainable transportation through eco-routing algorithms. His work bridges theoretical advances in spatial data science with practical applications in urban planning, emergency management, and environmental sustainability. Distinguished McKnight University Professor Distinguished University Teaching Professor UCGIS Education Award (2015) Graduate Education Award (2015) President of University Consortium for GIS (2017-2018) Computing Research Association Board Member (2016-2019) Professor Shekhar has advised over 30 PhD students since 1993, with his most recent graduate in 2023. He has secured significant research funding including a $20 million AI Institute grant focused on climate-smart agriculture and forestry. His Spatial Computing Research Group maintains active collaborations with government agencies and industry partners. The group has developed practical applications featured in media outlets including FoxTV coverage of evacuation route planning algorithms. Current research directions include applying AI techniques to address climate challenges through the AI-LEAF Institute and advancing spatial data science for polar regions through NSF-funded initiatives.
Lerrel Pinto is an Assistant Professor of Computer Science at New York University's Courant Institute, where he leads the General-purpose Robotics and AI Lab (GRAIL). His research focuses on enabling robots to generalize and adapt in unstructured environments through advancements in robot learning, decision making, and multimodal sensing. Before joining NYU, he completed a postdoc at UC Berkeley, a PhD in Robotics at Carnegie Mellon University, and an undergraduate degree in Mechanical Engineering at IIT Guwahati. Key research areas include large-scale robot learning, representation learning for sensory data, reinforcement learning for adaptability, and open-source robotics hardware. Notable achievements include the Sloan Fellowship (2025), NSF CAREER Award (2024), and Best Paper Awards at multiple robotics conferences. Pinto's lab has developed influential systems such as the AnySkin tactile sensing framework and the OPEN TEACH teleoperation system. Education highlights include a PhD from CMU (2019) under Abhinav Gupta, a postdoctoral stint with Alexei Efros and Pieter Abbeel at Berkeley, and undergraduate studies at IIT Guwahati. He has authored over 65 publications in top conferences like ICRA, NeurIPS, and CVPR. Pinto teaches courses on robotics, reinforcement learning, and AI at NYU. His service contributions include roles on program committees for ICML, NeurIPS, and IROS, as well as organizing workshops on topics like Dexterous Manipulation and Vision-Language Models for Robotics. His team actively collaborates through the GRAIL lab, with current projects exploring tactile sensing, zero-shot policy deployment, and multimodal robot learning systems. Ongoing research emphasizes bridging the gap between human and robotic dexterity through novel reward structures and adaptive control frameworks.
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.
