Laura Spitz is Dean and Professor at the University of Calgary Faculty of Law, with a concurrent Visiting Professorship at Université Paris 1 Panthéon-Sorbonne Law School. Her academic and professional journey spans multiple institutions, including Seattle University, University of New Mexico, Cornell University, and Thompson Rivers University. Educational Background: JSD, Cornell University JD, University of British Columbia BA, University of Toronto Spitz's research interrogates the legal construction of borders and identities, blending contracts, commercial law, and critical analyses of personhood in corporate and environmental contexts. Her work explores the limits of subject-object dichotomies in law and society. Notable awards include multiple Graduation Hooding Professor distinctions at the University of New Mexico and Colorado Law School, alongside teaching accolades. She contributes to constitutional pluralism debates and has co-authored influential works on legal personhood. A nonpracticing member of the Law Society of British Columbia, Spitz serves as a legal expert in contracts and business law, with experience in First Nations economic development and nonprofit law. She has advised on Supreme Court cases and held leadership roles in global engagement and international affairs.
Jiro Katto is a Professor at Waseda University's School of Fundamental Science and Engineering, where he has been conducting research and teaching since 1999. He received his Ph.D. from the University of Tokyo and has established himself as a leading researcher in multimedia signal processing and computer networks. His academic journey includes positions as Associate Professor (1999-2004), Professor (2004-present), and Director at NEDO (2004-2008), along with research experience at NEC C&C Laboratories (1992-1999) and a Visiting Scholar position at Princeton University (1996-1997). Professor Katto's research interests focus on Multimedia Signal Processing and Computer Networks, with particular expertise in video compression, 5G network performance, and learned image compression techniques. His work bridges theoretical advancements with practical implementations, as evidenced by his extensive publications in top-tier conferences and journals. His research group has made significant contributions to point cloud compression, latency compensation in remote systems, and hardware-accelerated video encoding for UHD streaming. His publication record is impressive, with 276 papers cited 3,323 times in Scopus and 6,169 times in Google Scholar, reflecting his substantial impact in the field. His recent work shows a strong trend toward applying deep learning techniques to traditional signal processing problems, particularly in the areas of image and video compression, where his team has developed novel approaches to improve compression efficiency while reducing computational complexity. Electric Telecommunications Promotion Foundation Telecommunications System Technology Award (2023) Takayanagi Kenjiro Foundation Takayanagi Kenjiro Achievement Award (2020) Institute of Image Information and Television Engineers Fellow (2020) Institute of Electronics, Information and Communication Engineers Fellow (2015) IEICE Communications Society Activity Contribution Award (2006) IEICE Academic Encouragement Award (1995) SPIE VCIP 1991, Best Student Paper Award (1991) Professor Katto has served on numerous prestigious committees including IEEE ComSoC Tech News Editorial Board, IEEE Technical Program Committees for major conferences (Globecom, ICC, ICIP), and editorial boards for several academic journals. His leadership in the academic community extends to chairing conferences like IWAIT 2011 and serving as Editor-in-Chief for journals in his field. His research has practical applications in commercial 5G networks, video streaming services, and remote monitoring systems, demonstrating the real-world impact of his work.
Arul Shankar is a Professor of Mathematics at the University of Toronto, with his primary appointment at the Mississauga campus (UTM). He holds an office at 215 Huron Street, Room 1023 and can be reached at ashankar@math.utoronto.ca. His research focuses on Number Theory and Arithmetic Statistics, with particular expertise in elliptic curves, Selmer groups, and class groups. Professor Shankar's research interests center on the arithmetic statistics of number fields and elliptic curves. His work has significantly advanced our understanding of the average rank of elliptic curves, the distribution of Selmer groups, and the statistics of class groups. He has developed innovative applications of the geometry of numbers to arithmetic problems, often in collaboration with Manjul Bhargava and other leading number theorists. His research bridges deep theoretical questions with statistical approaches to understand the behavior of arithmetic objects across families. His publications reveal a consistent focus on the statistical behavior of arithmetic invariants, with particular attention to bounding average ranks of elliptic curves and understanding the distribution of class groups. The work demonstrates sophisticated applications of geometry of numbers techniques to problems in arithmetic statistics, with results published in top journals including the Annals of Mathematics, Inventiones Mathematicae, and Journal of the American Mathematical Society. Scientific Awards: 2018 Sloan Research Fellowship from the Alfred P. Sloan Foundation Professor Shankar is currently on sabbatical as a Simons Fellow. His research has established foundational results in arithmetic statistics, particularly regarding the average rank of elliptic curves and the distribution of class groups across families of number fields. His work with Bhargava on bounding the average rank of elliptic curves represented a major breakthrough in the field. His research group focuses on extending geometry of numbers methods to new contexts in arithmetic statistics, with recent work examining coregular vector spaces and applications to class groups. The lab maintains strong collaborations with number theorists at leading institutions worldwide.
Olga Veksler is a Professor at the University of Waterloo's Department of Computer Science, part of the Faculty of Mathematics. She holds a Ph.D. and M.Sc. from Cornell University (1999) and a B.A. from New York University (1995). Her research focuses on computer vision, machine learning, and discrete optimization, with notable contributions to image segmentation, graph algorithms, and deep learning integration. Her work emphasizes semantic segmentation, salient object detection, and efficient optimization techniques for graphical models. Education: Ph.D. in Computer Science, Cornell University, 1999 M.Sc. in Computer Science, Cornell University, 1999 B.A. in Computer Science, New York University, 1995 Her research explores intersections between machine learning and traditional computer vision challenges, particularly leveraging graph-based optimization and CRF models. Recent trends in her work include weakly supervised learning, sparse non-local CRF applications, and test-time adaptation strategies for salient object detection. She has pioneered methods for shape priors in multi-object segmentation and efficient graph-cut algorithms. Her advising and grant activities are foundational to her research, though specific grant details are not listed here. She maintains a lab focused on advancing computer vision through algorithmic innovation, with contributions to both theoretical frameworks and practical applications in medical imaging and scene understanding.
Antonio De Rosa is an Associate Professor in the Department of Decision Sciences at Bocconi University, Italy. Previously, he held positions at the University of Maryland, College Park (2020–2024), and the Courant Institute of Mathematical Sciences, New York University (2017–2020). He earned his Ph.D. in Mathematics from the University of Zurich in 2017 under Camillo De Lellis and Guido De Philippis. Education: Ph.D. in Mathematics, University of Zurich (2017). His research spans Geometric Analysis , Partial Differential Equations , Calculus of Variations , Geometric Measure Theory , Optimal Transport , and Non-convex Optimization . Recent work focuses on anisotropic geometric variational problems, including existence, regularity, and uniqueness of anisotropic minimal surfaces and CMC (constant mean curvature) surfaces. He has also contributed to interdisciplinary applications in Explainable Risk Assessment and Data Analysis . The 15 most recent articles highlight advancements in anisotropic surfaces , min-max theory , optimal transport , and mathematical programming (e.g., K-means clustering, linear programming). Key trends include the intersection of geometric measure theory with nonlinear PDEs and applications in machine learning and transportation networks . Scientific Awards and Grants: 2023 Maryland Research Excellence Carlo Ciliberto Prize (2019) ERC Starting Grant ANGEVA (101076411, 2023–2028) Air Force Office of Scientific Research (AFOSR) grant (FA9550-23-1-0123) NSF CAREER Award (DMS-2143124) NSF DMS Awards (DMS-1906451, DMS-2112311) AMS Simons Travel Grant Antonio actively supervises research and teaches courses such as Optimization and Introduction to Partial Differential Equations . His work is supported by significant funding totaling approximately €3 million.
Dr. Hilde Kuehne is a Professor at the University of Tuebingen and a key researcher at the Tuebingen AI Center. She holds affiliations with MIT-IBM Watson AI Lab and Goethe University Frankfurt, with a focus on computer vision, multimodal learning, and explainable AI. Her work bridges vision-language models, audio-visual alignment, and self-supervised methods. Co-organizer of the New Frontiers in Associative Memories workshop @ ICLR 2025 Member of the Scientific Advisory Board of the Carl-Zeiss-Foundation Contributor to CVPR 2025's UTD dataset for unbiased video benchmarks Her research addresses critical challenges in: Explainability for Vision Transformers (LeGrad) Fine-grained audio-visual alignment (CAV-MAE Sync) Zero-shot visual recognition automation (Meta-Prompting) Spatio-temporal grounding without annotations Recent collaborative work spans 15+ publications across CVPR, NeurIPS, ICCV, and ICLR, with emphasis on multimodal foundation models, dataset bias mitigation, and differentiable logic networks. She actively contributes to workshop organization and peer review as evidenced by her involvement in CVPR 2025 and ICLR 2025 program committees.
About Vipul Jain: Associate Professor Vipul Jain leads Supply Chain and Logistics Management at RMIT University’s School of Accounting, Information and Supply Chain Management. With over 20 years of academic experience, he has held senior roles at institutions like Victoria University of Wellington (NZ) and IIT Delhi (India), contributing to curriculum development, research strategy, and academic-industry collaboration. His international collaborations span over 20 global institutions, emphasizing interdisciplinary research in supply chain resilience, sustainability, and Industry 4.0. Education & Academic Leadership: Previously served as Programme Director for Master of Technology (Industrial Engineering) at IIT Delhi, leading the establishment of the Modelling and Analysis of Supply Chain (MASC) Lab. Holds editorial roles for journals like International Journal of Intelligent Enterprise and Computers & Industrial Engineering . Research Focus: Specializes in supply chain design, sustainability, circular economy, and business analytics. His work integrates ICT and big data to address complex supply chain challenges, with notable contributions to vaccine distribution, blockchain adoption, and post-pandemic resilience. Over 145 peer-reviewed publications, including high-impact journals like OMEGA and International Journal of Production Economics , reflect his prolific output. Industry Impact: Conducted management training for organizations like JCB and IBM. Served as an expert assessor for New Zealand’s Ministry of Business and Industry and advised the Indian Railways. His research has been funded by the Department of Science and Technology (India) and EU initiatives like FP6 I*PROMS. Awards & Recognition: Ranked #7 in India’s top logistics academics (2018), recipient of Literati Awards (2024, 2020), and multiple editorial leadership roles. Active in global conferences, including co-chairing ANZAM 2023. Labs & Collaborations: Founded MASC Lab at IIT Delhi. Collaborates with Coventry University, Monash University, Hong Kong Polytechnic, and institutions in Switzerland, Spain, Canada, and the U.S. Focus areas include sustainable supply chains, digital transformation, and crisis resilience.
Zhiqiang Yu serves as an Associate Professor in the Department of Modern Languages and Comparative Literature at Baruch College's Weissman School of Arts and Sciences, City University of New York. With over two decades of teaching experience, he has established himself as a dedicated educator specializing in Chinese language, cinema, and civilization courses. Education: Ph.D. in Chinese, University of Washington M.A. in Asian Civilization, University of Iowa B.A. in Chinese Literature, Fudan University (Shanghai) Professor Yu's research focuses on innovative approaches to Chinese language pedagogy, with particular interest in applying economic principles and artificial intelligence to language teaching. His work bridges traditional linguistic scholarship with modern educational technology, examining how efficiency, resource allocation, and technological advancements can enhance language learning outcomes. His research spans Chinese linguistics, dialectology, cinema studies, and cultural elements in language teaching. His publication record reveals a consistent trajectory toward optimizing language instruction through systematic analysis. Recent work increasingly focuses on AI applications in language education and the economic framework of pedagogical efficiency. His scholarship demonstrates a progression from traditional linguistic analysis toward innovative teaching methodologies that incorporate modern technological and theoretical frameworks. Scientific Awards: Award of Excellent Academic Research Reviewer from Journal of International Chinese Education (2016) Graduate Teaching Fellowship from University of Washington (1993) Graduate Teaching Fellowship from University of Iowa (1989) Graduate Research Fellowship from University of Iowa (1988) Student Excellency Award from Fudan University (1984) Professor Yu has served extensively on departmental committees including as Department Assessment Coordinator and Secretary of the Asian and Asian-American Studies Committee. He has organized numerous academic events featuring prominent Chinese cultural figures and has contributed to developing Chinese language curriculum resources including online placement tests. His professional service extends to editorial work for CUNY publications and Chinese language training for the New York Police Academy. He maintains active involvement with multiple professional organizations including the American Name Society, American Oriental Society, American Society of Geolinguistics, Association for Asian Studies, and Chinese Language Teachers Association, frequently presenting at international conferences on Chinese language pedagogy.
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)
Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.
Panpan Yang is a Lecturer in Arts and Visual Cultures of Modern China at the School of Arts, SOAS University of London. She joined SOAS in 2021 after completing her joint PhD at the University of Chicago under the direction of Wu Hung, Tom Gunning, W. J. T. Mitchell, Judith Zeitlin, and Dana Polan. Her interdisciplinary work bridges art history, screen studies, East Asian studies, and digital humanities, with a focus on innovative methodologies in art historical writing. Dr. Yang earned a dual BA from Peking University, double majoring in art and philosophy, followed by an MA from Tisch School of the Arts at NYU, and a PhD from the University of Chicago. During her undergraduate studies, she served as president of the Society of Dream of the Red Chamber Studies, which informed her secondary academic interest in Redology and the visual material world of the novel Hong lou meng. Panpan Yang's research explores how minor discourses can deterritorialize the terrains of both art history and screen studies. Her work demonstrates a multimethodological approach attentive to archival research, material practices, close visual analysis, computer-aided vision, and cross-cultural theorization. She is particularly interested in Chinese animation history, calligraphic imagination in contemporary art, and the intersections between traditional Chinese art forms and new media. Her publications reveal a consistent focus on Chinese visual culture across multiple media forms, with particular attention to animation, film, and calligraphy. Yang's work demonstrates how traditional Chinese art forms engage with contemporary digital media, creating new hybrid forms that challenge disciplinary boundaries. Her research shows a trajectory from historical analysis of Chinese animation to contemporary explorations of calligraphy in digital contexts, revealing the ongoing relevance of traditional Chinese aesthetics in modern media. Dr. Yang has received several prestigious awards for her scholarly and creative work: China's National Young Screenwriter Award Domitor Essay Award Dean's Distinguished Dissertation Award Nomination Honourable Mention from the Association for Chinese Animation Studies As a Principal Investigator, Dr. Yang leads the AHRC-funded research project "Stroke by Stroke: Calligraphic imagination in contemporary Chinese art and emergent media" (2023-25) with Shane McCausland. She was also a collaborating partner on the NEH-funded "Media Ecology Project." Her research has received additional support from the Getty Foundation and the Sino-British Fellowship Trust. At SOAS, she works closely with faculty and graduate students interested in Chinese arts and cultures, art theory, cinematic arts, and digital art history. Dr. Yang is currently developing innovative research at the intersection of traditional Chinese calligraphy and contemporary digital media through her AHRC-funded project. This work explores how calligraphic imagination manifests in contemporary art and emergent media contexts, creating new pathways for understanding Chinese cultural heritage in the digital age.
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.
Douglas A. Loy is a full Professor at the University of Arizona with joint appointments in the Department of Materials Science and Engineering and the Department of Chemistry and Biochemistry, and additional affiliations with the BIO5 Institute and the School of Mining and Mineral Resources. A fifth-generation Arizonan, he earned his BS in Chemistry from the University of Arizona (1983), MS in Chemistry from Northern Arizona University (1986), and PhD in Organic Chemistry from the University of California, Irvine (1991). Before returning to academia he spent 14 years at Sandia National Laboratories and then led the Polymer and Nanomaterials Synthesis Team at Los Alamos National Laboratory. Research Interests Sol-gel & polysilsesquioxane chemistry: fundamental studies and unconventional routes to hybrid organic-inorganic materials. Tetrazine polymer chemistry: synthesis, click modification, and application in antioxidant foams and UV-stable sunscreens. 3-D printing of glasses & ceramics: additive manufacturing of micro-optics, multi-refractive-index glass objects, and transparent devices using silica and silsesquioxane resins. Energy & biomaterials: new materials for energy storage, polymer-ceramic bone scaffolds, and smart packaging films. Across more than 70 recent publications (2012-2025), the dominant themes are advanced additive manufacturing of specialty glasses and ceramics, design of photochemically stable sunscreen systems, and development of multifunctional polymer-ceramic composites for biomedical and energy applications. The work integrates molecular-level organic synthesis with macro-scale materials processing, enabling applications ranging from holographic micro-optics to lunar in-situ resource utilization. Scientific Awards & Recognition While specific honors are not listed in the provided text, Loy is described as a “distinguished member of technical staff” at Sandia National Laboratories, indicating prior recognition for his research achievements. Funding & Collaborative Teams At the University of Arizona his group pursues federally and industrially funded projects spanning NSF, DOE, and NASA programs, particularly in advanced manufacturing and energy materials. He collaborates closely with the BIO5 Institute for biomedical applications and with the School of Mining and Mineral Resources for resource-based materials research. No explicit student lists are included in the text. Laboratory & Facilities Loy’s laboratories are located in Mines and Metallurgy 338B at the University of Arizona, equipped for sol-gel synthesis, polymer processing, and state-of-the-art 3-D printing instrumentation including multi-photon lithography systems for micro-optics fabrication.
Nancy Reynolds is an Associate Professor of History at Washington University in St. Louis, with affiliate appointments in Women, Gender and Sexuality Studies and Jewish, Islamic, and Middle Eastern Studies. Her research focuses on environmental and social-cultural history of twentieth-century Egypt, examining political-material intersections in built environments from department stores to dams. Her academic background includes: PhD in History from Stanford University MA in History from Stanford University BA from Harvard University Reynolds' scholarship spans Environmental History , Social History , and Urban Studies , with emphasis on how mundane objects (socks, store floors) and monumental structures (Aswan Dam, temples) reflect nationalist struggles. Her work critically engages gender dynamics and decolonization , revealing how consumption patterns and urban spaces became sites of political contestation in semicolonial Egypt. Her 13 publications (2000-2024) demonstrate an evolution from consumer culture studies (department stores, Cairo Fire) to environmental history (Aswan Dam, desert ecologies), with recent collaborative work on Middle Eastern wastelands and sustainable architecture. The 2024 corpus particularly emphasizes political ecologies and materialized absence. Her scientific recognition includes: Roger Owen Book Award (2013) for A City Consumed American Council of Learned Societies Fellowship (2012) Bernadotte E. Schmitt Grant (2010) Stanford Humanities Center Geballe Dissertation Prize Social Science Research Council Fellowship Reynolds actively shapes graduate education as former administrator of History and JIMES PhD/MA programs. Her research is sustained by major grants including a Mellon Sawyer Seminar (2016-2018) and Mellon New Directions Fellowship (2014-2016), both supporting transregional collaborations on environmental humanities. She co-leads the Grounding the Ecocritical research collective with Dr. Anne-Marie McManus, producing the "Following Absence" symposium and CSSAAME special section on Middle Eastern wastelands.
Dr. Agnes Hsu-Tang is an Adjunct Professor at Columbia University’s Department of East Asian Languages & Cultures, specializing in archaeology and art history with a focus on cultural heritage and transnational trade routes. She holds a PhD from the University of Pennsylvania and has served in prestigious roles including Board Chair of The New York Historical Society and Co-chair of the Metropolitan Museum of Art’s Objects Conservation Committee. Her academic contributions span UNESCO missions, international film collaborations, and co-founding institutions like the Tang Center for Early China and Silk Road Studies. Education: BA (Bryn Mawr College, Classical Languages & English Literature), MA (University of Pennsylvania, East Asian & Middle Eastern Studies), PhD (University of Pennsylvania, 2004). Research interests include early Chinese cartography, Silk Road cultural exchanges, and the intersection of art history with imperial geography. Her work bridges archaeology, art, and policy, addressing illicit cultural trafficking and heritage preservation. She has produced award-winning documentaries and serves on global arts and museum boards. Her publications explore topics such as ancient mapping techniques and Silk Road heritage. Awards recognize her academic and leadership roles in cultural preservation. She co-founded the Tang Centers and Hsu-Tang Library, advocating for interdisciplinary scholarship and global cultural dialogue.
