Avi Loeb , the Frank B. Baird Jr. Professor of Science at Harvard University, is a leading astrophysicist and former Chair of Harvard's Department of Astronomy (2011-2020). He directs the Institute for Theory and Computation (ITC) and the Galileo Project (2021-present), while holding the Sackler Senior Professorship at Tel Aviv University. His research spans cosmology, black holes, interstellar objects, and the search for extraterrestrial life. Education: PhD in Physics from Hebrew University of Jerusalem (1986) Former Positions: Member of the Institute for Advanced Study, Princeton (1988-1993) Loeb's research interests include: Gravitational wave detection and interstellar object analysis Simulation hypothesis and cosmic reality Technological signatures beyond the Standard Model His recent publications focus on 3I/ATLAS , gravitational SETI, and AI alignment in space exploration. Awards include being named among TIME's 25 Most Influential People in Space (2012), 14 Most Inspiring Israelis (2020), and ranking #3 in global astronomical impact (2024). He chairs the Breakthrough Starshot Initiative and advises the National Academies' Board on Physics and Astronomy.
Xingxing Zuo is an Assistant Professor (tenure-track) in the Robotics Department at MBZUAI. He holds a PhD from Zhejiang University (2021) and a Bachelor’s from UESTC (2016). Previously, he was a Postdoctoral Scholar at Caltech (2024–2025), a Postdoc at ETH Zurich (2019–2021), and held visiting roles at TU Munich, University of Delaware, and University of Technology Sydney. His research focuses on robotics, 3D computer vision, and embodied AI, with emphasis on robot-human collaboration, state estimation, and sensor fusion. Educations: PhD in Robotics, Zhejiang University (2021, with honors) Bachelor’s in Computer Science, University of Electronic Science and Technology of China (2016, with honors) Research Highlights: Develops novel methods for LiDAR-camera-inertial fusion, neural radiance fields, and radar-cameras systems Pioneered techniques like Flying Co-Stereo (long-range aerial mapping) and FMGS (vision-language embedded 3D splatting) Focuses on real-time SLAM, robust depth estimation, and photorealistic scene reconstruction Awards & Recognition: Best Paper Finalist at ICRA 2021 (CodeVIO) Oral Presentation at ICCV 2021 (MBA-VO) Recipient of Google Visiting Faculty Researcher (2023) Grants & Labs: Organized Thermal Infrared in Robotics workshop at ICRA 2025 Leads research on embodied AI and multi-sensor SLAM systems Develops open-source tools like LIC-Fusion and Coco-LIC frameworks
Daniel Epstein is an Associate Professor in the Department of Informatics at the University of California, Irvine (UCI), where he leads the Personal Informatics Everyday (PIE) Lab. He holds a courtesy appointment in the Department of Computer Science and is affiliated with the Connected Learning Lab, Institute for Future Health, and Accessibility Research Collective. Epstein earned his Ph.D. in Computer Science & Engineering from the University of Washington and a B.S. in Computer Science from the University of Virginia. His research focuses on how personal tracking technology can better serve diverse users' needs, emphasizing ethical design, health equity, and long-term user engagement. Notable areas include pregnancy tracking, wearable technology for children and ADHD management, and AI-driven health chatbots. Epstein has received grants from NSF, Snap Inc., and UCI programs, totaling over $650k in funding. Epstein's work bridges HCI and health informatics, with over 60 peer-reviewed publications. He advises six Ph.D. students and has mentored numerous undergraduates. Awards include the ACM Senior Member distinction (2025), CHI Best Paper (2023), and NSF CAREER Award (2023). Professional service includes program committees for CHI, CSCW, and UbiComp, plus leadership roles in workshops like the Workgroup on Interactive Systems in Healthcare (WISH). Beyond academia, Epstein enjoys hiking, collecting turtle figures, and advocating for accessible technology.
Katerina Fragkiadaki is the JPMorgan Chase Associate Professor of Computer Science in the Machine Learning Department at Carnegie Mellon University. She works at the intersection of Artificial Intelligence, Computer Vision, Machine Learning, Language Understanding, and Robotics. PhD from GRASP Lab, University of Pennsylvania Postdoctoral researcher at UC Berkeley (with Jitendra Malik) and Google Research Recipient of NSF CAREER, DARPA Young Investigator, Amazon, Google, Sony, UPMC, and AFOSR awards Organizer of CoRL 2023 Workshop on Generalist Robots ICLR 2024 Program Chair, multiple area chair roles Her research group focuses on developing machines that autonomously improve world models through human-environment interactions, with specific emphasis on: Representation learning and video understanding 2D/3D unified vision-language models Generative simulation and reinforcement learning Real2Sim/Sim2Real robot learning Continual learning and spatial common sense 3D scene reconstruction and dynamics Recent publications highlight advancements in: 3D mesh generation with compositional transformers Unified 2D/3D perception frameworks Physics-aware generative models Diffusion-based robotic manipulation policies Embodied agents with memory prompting Awards include: 2024: DARPA Young Investigator Award 2023: Amazon Faculty Award 2022: Sony Faculty Research Award 2021: UPMC Faculty Research Award 2020: NSF CAREER Award 2019: Google Faculty Award Key collaborations span institutions including UC Berkeley, Google Research, Stanford, MIT, and University of Tsukuba. Her work bridges theoretical innovation with practical applications in: Autonomous robot manipulation 4D world modeling Language-grounded perception Visual dynamics prediction Embodied program synthesis Physics-based simulation engines
Sanjiv Singh is a Research Professor at the Robotics Institute within Carnegie Mellon University's School of Computer Science. His academic journey at CMU spans from Systems Scientist (1995-2001), to Senior Research Scientist (2001-2003), Associate Research Professor (2003-2007), and finally Research Professor since 2007. He also holds an adjunct faculty position in Mechanical Engineering since 2009. Singh serves as Editor-in-Chief of the Journal of Field Robotics, demonstrating his leadership in the robotics community. His educational background includes a Ph.D. and M.S. in Robotics from Carnegie Mellon University (1995, 1992), an M.S. in Electrical Engineering from Lehigh University (1985), and a B.S. in Computer Science from the University of Denver (1983). Dr. Singh's research focuses on three primary themes: Autonomous Navigation (developing motion planning and control for ground and air vehicles with applications in agriculture, exploration, and low-flying aircraft), Coordinated Multi-Robots (examining team-based tasks like structure assembly and search/rescue operations), and Forceful Interaction with the world (using physical models to enable robots to handle complex, high-force interactions). His work spans aerial robotics, agricultural and forestry robotics, mining robotics, 3D vision, sensing and perception, visual servoing, motion planning, and field service robotics. Analysis of his recent publications (2016-2020) reveals a strong focus on collision avoidance algorithms, sensor fusion techniques, and real-time navigation systems. His research demonstrates consistent advancement in SLAM (Simultaneous Localization and Mapping) technologies, particularly in GPS-denied environments, with increasing sophistication in handling complex aerial maneuvers and multi-robot coordination. Editor-in-Chief of Journal of Field Robotics Dr. Singh has advised numerous graduate students throughout his career, with current advisees including Matt Aasted (Ph.D), Andrew Chambers (M.S), Hugh Cover (M.S), Michael Dille (Ph.D), and Justin Haines (M.S). His past students include prominent researchers like Sebastian Scherer, Joe Djugash, Fred Heger, Geoff Hollinger, and Ji Zhang who have gone on to make significant contributions in robotics. His research has been supported through various projects including CASC (agricultural applications), Riverine, Transformer, Trestle, and Ember. His laboratory work focuses on developing practical robotic systems capable of operating in challenging real-world environments, with particular emphasis on agricultural applications, search and rescue operations, and coordinated multi-robot teams that can work effectively alongside humans.
Tanzeem Choudhury is a Professor at the Jacobs Technion-Cornell Institute at Cornell Tech, specializing in Information Sciences. She co-founded HealthRhythms Inc. and directs the People-Aware Computing lab, focusing on machine learning for human activity and social network analysis. Her work pioneered the 'Reality Mining' field, leveraging mobile sensors to model social interactions. Choudhury holds a Ph.D. from MIT's Media Lab and B.S. in Electrical Engineering from the University of Rochester. Her research spans wearable tech, mental health interventions, and ubiquitous computing. Notable projects include affective touch wearables for anxiety reduction, stress detection systems (e.g., StressSense), and the BeWell app for well-being monitoring. Choudhury has been recognized as an ACM Fellow and SIGCHI Academy member, with impactful contributions to healthcare technology and sensor-based behavioral analysis. Current lab initiatives include developing closed-loop interventions for mental health, equity-driven sensing systems, and exploring AI integration in psychotherapy. She advises PhD students on topics like digital biomarkers, burnout detection in healthcare workers, and smartphone-based mental health assessment. Education: Ph.D. in Media Arts & Sciences (MIT), M.S. (MIT Media Lab), B.S. in Electrical Engineering (University of Rochester) Lab Team: Includes PhD candidates (Dan Adler, Yiran Zhao) and researchers focusing on health AI, wearable devices, and clinical applications. Major Awards: ACM Fellowship (2020), SIGCHI Academy (2018), Best Paper Awards at Ubicomp and MobileHCI conferences. Key Projects: OptoBeat (skin-tone calibrated blood oxygen sensor), EmotionCheck (anxiety intervention), and Affective Touch devices.
Darryl Jones is Professor at Griffith University's Centre for Planetary Health and Food Security, specializing in behavioral ecology and human-wildlife interactions. His research examines urban ecosystems, wildlife conflict resolution, and conservation strategies, with particular emphasis on bird ecology and road infrastructure impacts. Professor Jones has authored influential books including 'Feeding the Birds at Your Table' and 'A Clouded Leopard in the Middle of the Road' that bridge scientific research and public engagement. His work explores: Wildlife responses to urbanization Bird feeding practices and consequences Road ecology and mitigation design Human dimensions of conservation Koala-vehicle collision patterns Recent publications document COVID-19's impact on global bird feeding behaviors, analyze 20-year trends in koala road mortality, and evaluate LED streetlight effects on urban wildlife. He leads research on dingo population viability in Fraser Island and develops innovative wildlife monitoring technologies like the open-source WildWID RFID system. Professor Jones collaborates extensively with government agencies on conservation policy and has secured funding for projects examining wildlife crossing infrastructure effectiveness. His research informs evidence-based approaches to human-wildlife coexistence in rapidly changing landscapes.
Jiayi Lu is a PostDoc Researcher at the University of Pennsylvania School of Arts & Sciences, working under the supervision of Dr. Julie Anne Legate. Her research focuses on syntax, psycholinguistics, and Chinese linguistics, with a particular emphasis on grammaticality judgments, satiation effects, and island phenomena. She has contributed to understanding how sentence processing and discourse factors influence syntactic structures. Her research interests encompass syntax, psycholinguistics, and formal semantics, with a focus on exploring grammaticality illusions, the role of discourse in syntactic constraints, and cross-linguistic variations in Chinese. Key areas include the study of extraction islands, coordination effects, and the cognitive mechanisms underlying sentence processing. Her recent work (2020-2024) demonstrates a strong focus on syntactic satiation, island effects, and experimental methods in syntax. Publications analyze both English and Chinese data, investigating how linguistic structures are processed and judged by speakers. Trends include exploring the generalizability of satiation across island types and the interplay between discourse and syntactic constraints. Dr. Lu has not listed any scientific awards or grants in the provided information. Dr. Lu has not listed any advisees or grants in the provided information.
Christian Rupprecht is an Associate Professor at the Department of Computer Science, University of Oxford, specializing in computer vision and machine learning. His research focuses on unsupervised learning, 3D reconstruction, and visual understanding. His work includes contributions to conferences such as GCPR'25, ICCV'25, and CVPR'25, with papers spanning topics like correspondence estimation, animal pose modeling, and synthetic data generation. He leads projects within the prestigious Visual Geometry Group (VGG). Notably, his paper VGGT received the Best Paper Award at CVPR'25. His research integrates deep learning and geometric modeling, emphasizing robustness and generalization in visual systems. Best Paper Award at CVPR'25
Robert Rohling is a Professor at the University of British Columbia's Faculty of Applied Science, affiliated with the Department of Mechanical Engineering and holding a joint appointment with the Department of Electrical and Computer Engineering. As Director of the Institute of Computing, Information and Cognitive Systems (ICICS), his research focuses on biomedical engineering, medical imaging, robotics, and computational methods. B.A.Sc. (UBC) M.Eng. (McGill) Ph.D. (Cambridge) Rohling's work spans three primary research areas: medical imaging (3D ultrasound, spatial compounding, elasticity reconstruction), medical information systems (radiologist navigation tools for large image datasets), and robotic calibration for surgical applications. His multidisciplinary approach integrates mechanical and electrical engineering principles with clinical needs. Rohling's publications (2020-2022) reveal trends in advanced ultrasound techniques (e.g., shear wave vibro-elastography), AI-driven image processing (cycleGAN translation), and computational optimization for diagnostic accuracy. Keywords across his work include Medical Imaging, Biomedical Engineering, Robotics, and Computational Modeling. As director of the Robotics and Control Laboratory , Rohling leads interdisciplinary collaborations with industry and clinical partners to address practical challenges in medical diagnostics and surgical robotics. His research emphasizes translating engineering innovations into clinical practice.
Harris H. Wang is an Associate Professor in the Department of Systems Biology and Department of Pathology and Cell Biology at Columbia University's Vagelos College of Physicians and Surgeons, where he also serves as Interim Chair of Systems Biology. He is affiliated with the Center for Computational Biology and Bioinformatics (C2B2) and the Integrated Program in Cellular, Molecular and Biomedical Studies (CMBS). B.S., Physics and Mathematics, MIT Ph.D., Biophysics, Harvard University Dr. Wang's research lies at the intersection of systems and synthetic biology, focusing on developing foundational technologies for genome engineering, microbiome manipulation, and synthetic genomics. His lab pioneers methods such as MAGE, MAGIC, CAST, and CAMII to enable high-throughput genetic manipulation, in situ microbiome engineering, and AI-driven microbial culturomics. Key research themes include understanding microbial community dynamics, engineering cellular memory systems, designing biocontained genetic circuits, and applying synthetic biology to human health challenges in personalized medicine and infectious disease. His recent publications reveal a strong trend in spatial and functional metagenomics, CRISPR-based microbiome editing, and synthetic biology tools for data storage and genetic stability. The articles span high-impact journals like Nature , Science , and Nature Biotechnology , reflecting his leadership in developing scalable, programmable biological systems. Scientific Awards: NIH Director’s Early Independence Award Forbes 30 Under 30 in Science Sloan Research Fellowship NSF CAREER Award ONR Young Investigator Award Burroughs Wellcome Fund PATH Award Schaefer Scholar Blavatnik National Award Vilcek Prize PECASE Dr. Wang has advised numerous PhD and postdoctoral researchers, many of whom have gone on to independent scientific careers. His lab is supported by major grants from NIH, NSF, DARPA, DOE, and foundations including the Bill & Melinda Gates Foundation and CZ Biohub NY. He is actively involved in educational initiatives, including organizing Columbia’s iGEM team and the Cold Spring Harbor Laboratory Synthetic Biology course. The Wang Lab is based at the Columbia University Irving Medical Center and is part of national consortia such as the Engineering Biology Research Consortium (EBRC) and the Genome Project-Write (GP-Write) initiative. The lab develops and applies cutting-edge technologies in automation, machine learning, and synthetic biology to engineer microbiomes for applications in medicine, global health, and climate change.
Dr. Kaya de Barbaro is an Associate Professor in the Department of Psychology at the University of Texas at Austin (College of Liberal Arts). She holds a Ph.D. from the University of California San Diego. Her research focuses on bridging computer science and developmental/clinical psychology, particularly maternal mental health and infant social-emotional development. She directs the Daily Activity Lab, which uses mobile/wearable sensors and machine learning to analyze real-world interactions, aiming to develop just-in-time interventions for new mothers. Key research areas include maternal-infant dynamics, physiological synchronization, and the impact of environmental chaos on development. She has pioneered methods for analyzing high-density data, such as Granger causality and machine learning algorithms to detect behaviors like crying and holding. Recent work emphasizes leveraging ecological momentary assessment surveys and 24-hour LENA audio recordings to understand proximal mechanisms of development. Dr. de Barbaro teaches Psychology 333D (Introduction to Developmental Psychology) and has developed curricula for both in-person and online formats. She is actively involved in training students through the Eureka program at UT Austin. Her lab collaborates on tools like chatbots for postpartum mental health and has published extensively on sensor-based methodologies in developmental science.
Paulami Mitra is an Assistant Professor and Academic Director of the Strategy and Sustainability track at IÉSEG School of Management in Lille, France, with prior academic experience as a Visiting Professor at the University of Southern California (2017-2018) and Teaching and Research Assistant at IÉSEG (2012-2019). Her doctoral training in Economics and Management Sciences from Université Catholique de Louvain-Mons underpins her interdisciplinary approach to business education and research. Her educational qualifications include: 2019: Ph.D. in Economics and Management Sciences, Université Catholique de Louvain-Mons, Belgium 2009: Masters in Management, Lancaster University, United Kingdom 2008: B.Tech in Information Technology (Engineering), Institute of Technology and Marine Engineering, India Dr. Mitra's research centers on entrepreneurship-sustainability intersections, with particular expertise in eco-entrepreneurship, crowdfunding dynamics for social ventures, and hybrid organizational models. Her work examines how prosocial motivations drive crowdfunding participation, the strategic advantages of hybrid structures in social enterprises, and pedagogical innovations for sustainability-focused business education. She investigates critical gaps in climate-responsive entrepreneurial frameworks and sustainable financing mechanisms. Analysis of her publication trajectory reveals a concentrated focus on social entrepreneurship evolution since 2017, with increasing emphasis on sustainability-crowdfunding synergies and educational applications. Her 2022-2024 output demonstrates methodological diversity across case studies, survey research, and conceptual frameworks, consistently targeting high-impact journals in entrepreneurship and sustainability fields. No scientific awards are documented in the provided materials. Professional activities indicate active curriculum development and executive education leadership, though specific student advisement or grant-funded research projects are not referenced in the source text. The available information does not specify laboratory affiliations, research teams, or collaborative infrastructure supporting her scholarly work.
Azizjon ALIMOV is a Full Professor at IÉSEG School of Management (University of Lille, France), specializing in Corporate Finance, Mergers and Acquisitions, and Law and Finance. He holds a Ph.D. in Finance from the University of Oregon (2007) and an MBA from Central Michigan University (2001). His HDR (Habilitation) in Management Sciences was awarded by the University of Lille in 2023. His research focuses on corporate governance, cross-border M&A dynamics, and the interplay between legal frameworks and financial decision-making. Key themes include intellectual property rights' impact on corporate debt costs, product market competition effects on corporate cash holdings, and government borrowing influences on acquisition strategies. His work frequently examines global contexts, with studies spanning North America, Asia, and Europe. Notable publications include analyses of IPO staging mechanisms (2024), managerial discipline through trade liberalization (2023), and the role of labor protection laws in loan contracting (2015). His recent work emphasizes reproducibility in management science methodology (2023) and cross-border regulatory challenges in M&A. No scientific awards are explicitly listed; however, his extensive publication record reflects sustained academic contributions. He has advised students across institutions including City University of Hong Kong and the Sauder School of Business, though specific advisee names are not documented here. His professional experience includes roles at the University of Arizona (2008–2010), California State University (2007–2008), and as an HSBC Visiting Assistant Professor at the University of British Columbia (2016–2018). He currently leads the Finance Track at IÉSEG, contributing to programs like the Grande École Master’s in Finance and MSc Corporate Finance courses.
Shweta Shinde is an Assistant Professor in the Department of Computer Science at ETH Zurich where she leads the Secure & Trustworthy Systems (SECTRS) research group. She is also a member of the Institute of Information Security and the ZISC Center at ETH Zurich. Her work bridges theoretical foundations with practical implementations in hardware and system security. Dr. Shinde's research focuses on the intersection of trusted computing, system security, and program analysis. Her group investigates both foundational aspects of security to protect phones, servers, and accelerators, as well as practical aspects of realizing these solutions through large-scale system building. Her work spans hardware security primitives, trusted execution environments, confidential computing, and secure system design across multiple platforms including mobile devices, cloud infrastructure, and blockchain systems. Her publication record demonstrates significant impact in the field, with numerous papers in top security venues including IEEE S&P, USENIX Security, CCS, and NDSS. Her research has uncovered critical vulnerabilities in major hardware security technologies like Intel SGX and AMD SEV-SNP while also proposing novel frameworks for building more secure systems. The work spans multiple domains including hardware security, cloud security, mobile security, and blockchain security, with a consistent thread of identifying and addressing fundamental security challenges in trusted computing. Among her notable achievements are multiple best paper awards including at SysTEX 2025 and nominations at DATE 2025, a Distinguished Paper Award at IEEE S&P 2024, and recognition as a Most Innovative Research Pwnie Award Nominee in 2024. Her work on WeSee received particular attention for breaking AMD SEV-SNP through novel interrupt-based attacks. Dr. Shinde actively mentors PhD students including Mark Kuhne, Supraja Sridhara, Mélisande Zonta-Roudes, Benedict Schlüter, Andrin Bertschi, and others. She teaches courses on Systems Security, Information Security Lab, Seminar on Systems Security, and Current Topics in Information Security at ETH Zurich. Her service to the community includes extensive program committee work for major security conferences including Oakland (S&P), NDSS, USENIX Security, and CCS, where she has served as track co-chair and program co-chair for several workshops.
