جست‌وجوی استاد و پژوهشگر

Jessica Fjeldمشاهده پروفایل

مدرس

• Artificial Intelligence Governance
• Digital Rights and Privacy
• Freedom of Expression
• +۴ مورد دیگر

Jessica Fjeld is a Clinical Lecturer at Harvard Law School and Managing Director of the De|Center, an initiative addressing digital authoritarianism. She is affiliated with the Berkman Klein Center for Internet & Society and previously served as Assistant Director of the Cyberlaw Clinic. Her work focuses on AI governance, digital rights, and the intersection of technology with human rights and creativity. Fjeld holds a JD from Columbia Law School, an MFA in Poetry from UMass, and a BA from Columbia University. Affiliations: Harvard Law School, Berkman Klein Center, Cyberlaw Clinic Roles: Clinical Lecturer, Managing Director (De|Center), Legal Scholar Research Interests: AI ethics and governance frameworks Content moderation challenges for marginalized communities Legal aspects of AI-generated art and intellectual property Corporate accountability in tech sectors Freedom of expression in digital spaces Key Projects: Principled Artificial Intelligence Project (mapping global AI ethics principles) Online Identity Help Center (supporting marginalized users in content moderation disputes) Advocacy against facial recognition misuse in Boston Awards: Hamilton Fellow & James Kent Scholar (Columbia Law School) Poetry Society of America Recognition 92nd Street Y/Boston Review Discovery Prize

Patrick Bradleyمشاهده پروفایل

استادیار

• Human microbiome
• Bioinformatics
• Genomics
• +۴ مورد دیگر

Patrick Bradley is an Assistant Professor of Microbiology at The Ohio State University, affiliated with the College of Arts and Sciences. He is also part of the Infectious Diseases Institute and the Center of Microbiome Science. His research focuses on understanding human microbiota (particularly the gut and oral microbiomes) using computational and experimental approaches. Bradley earned his A.B. from Harvard University (2005), Ph.D. from Princeton University (2012), and completed a postdoctoral fellowship at the University of California, San Francisco (2013–2020). Education: A.B., Harvard University, 2005 Ph.D., Princeton University, 2012 Postdoc, University of California, San Francisco, 2013–2020 His research interests include microbial gene function prediction, gene regulation in adaptive environments, and the role of microbiomes in drug metabolism and disease. Current lab projects involve leveraging natural genetic variation to identify genes influencing microbial colonization, understanding regulatory mechanisms in microbial adaptation, and developing machine learning tools for functional annotation. Recent work highlights the disproportionate impact of genomic misassembly in metagenomic studies and the shared metabolic pathways between hosts and microbes in cancer drug processing. Bradley’s lab actively collaborates on projects such as PanSweep (a tool to detect pangenome contamination) and Phylogenize2 (for phylogeny-corrected gene association analysis). Advising and grants: Bradley mentors PhD students (Christian J. Quiles Pérez, Stephanie Majernik, Nghi Tran, Alexis Young) and has contributed to studies exploring microbiome-modulating therapies. The Bradley Lab is part of interdisciplinary initiatives at Ohio State, emphasizing translational research in microbiome science. Lab activities include developing computational tools for microbiome analysis and maintaining collaborations with institutions like the Center for Microbiome Science. The lab’s work has implications for precision medicine and understanding microbial contributions to human health.

Suzy Angerمشاهده پروفایل

دانشیار

• Victorian Literature
• Nineteenth-Century Literature
• Science and Technology Studies
• +۳ مورد دیگر

Suzy Anger serves as an Associate Professor and MA Advisor in the Department of English Language and Literatures within the Faculty of Arts at the University of British Columbia. Her academic work bridges literary studies with the history of science, focusing on how Victorian literature engaged with contemporary scientific thought. Dr. Anger received her BA from the University of California, Berkeley, followed by her MA and PhD from the University of Washington. Her educational background established the foundation for her interdisciplinary approach that connects literary analysis with scientific and philosophical inquiry. Her research primarily explores Victorian literature in relation to nineteenth-century science, psychology, and philosophy. Currently, she investigates Victorian fiction and nineteenth-century theories of consciousness, examining novels by Thomas Hardy, Charles Dickens, George Gissing, and Sarah Grand across genres including ghost fiction and scientific romance. Her scholarly work demonstrates how literary texts engaged with emerging scientific concepts of the period, particularly in the areas of mind sciences, hermeneutics, and technological understanding. She has particular expertise in how literary works processed scientific developments related to consciousness, automatism, and the relationship between humans and machines. Her publication record reveals a consistent trajectory of scholarship examining the intersection of Victorian literature and scientific thought, with recent work increasingly focused on theories of consciousness, literary automatism, and the philosophical implications of scientific developments in the nineteenth century. Her research demonstrates how literary works served as laboratories for exploring complex scientific concepts before they were fully developed in scientific discourse. Sonya Rudikoff Prize for the best first book in Victorian Studies (2006) Killam Teaching Prize, University of British Columbia (2018) Newhouse Center Faculty Fellowship, Wellesley College (2006-2007) SSHRC Faculty Research Grant (2005-2008) American Council of Learned Societies Fellowship (2000-2001) National Endowment for the Humanities Stipend (1999) As an academic leader, Dr. Anger has served as president of the Northeast Victorian Studies Association and was former co-chair of UBC's interdisciplinary graduate program in Science and Technology Studies. Her research has been supported by multiple prestigious fellowships and grants from major funding bodies including the American Council of Learned Societies, the National Endowment for the Humanities, and the Social Sciences and Humanities Research Council of Canada. Her editorial work on collections like 'Victorian Science as Cultural Authority' and 'Victorian Automata' has helped shape contemporary scholarship in the field. Through her editorial projects and interdisciplinary collaborations, Dr. Anger has been instrumental in developing the field of Science and Technology Studies within literary scholarship. Her work with colleagues across disciplines has created important spaces for examining how literature processes scientific and technological change, particularly in historical contexts where such changes were rapidly transforming society's understanding of itself.

Rebecca Nugentمشاهده پروفایل

استاد

• Clustering Methodology
• Record Linkage
• Educational Data Mining
• +۵ مورد دیگر

Rebecca Nugent is the Stephen E. and Joyce Fienberg Professor of Statistics & Data Science and Department Head at Carnegie Mellon University. She holds a PhD in Statistics from the University of Washington (2006), an MS in Statistics from Stanford (2006), and a BA in Mathematics, Statistics, and Spanish from Rice University (2002). Her research spans clustering methodology , record linkage , educational data mining , public health , and semantic organization , with a focus on high-dimensional data and adaptive learning environments. She leads the Integrated Statistics Learning Environment (ISLE) and Corporate Capstone programs, emphasizing low-barrier data platforms for education and industry collaboration. Academic Roles : Department Head, Carnegie Mellon; Affiliated Faculty, Block Center for Technology and Society Research Grants : NSF (2017-2019), NIH (2018), Carnegie Mellon ProSEED/Simon Initiative (2020, 2018), Berkman Fund (2014) Her 15 most recent publications focus on data science pedagogy, clustering algorithms, record linkage applications in historical and medical data, educational data mining, and semantic organization studies. Awards include the ASA Waller Education Award (2015) and the William H. and Frances S. Ryan Award (2015) . She mentors a diverse group of PhD, Master's, and undergraduate students, with alumni pursuing careers in academia, industry, and sports analytics.

• Maritime safety management and leadership
• Maritime accident and casualty analysis
• Maritime Autonomous Surface Ships (MASS)
• +۳ مورد دیگر

Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.

Yang Chengمشاهده پروفایل

دانشیار

• Supply Chain Management
• Manufacturing Strategy
• Manufacturing Network
• +۵ مورد دیگر

Yang Cheng is an Associate Professor at the Department of Materials and Production, Aalborg University, Denmark. He holds a PhD in Mechanical Engineering from the same institution (2011), focusing on manufacturing strategy and network dynamics. His research spans supply chain management, sustainability, and global operations, with a focus on integrating technology and environmental policies into manufacturing systems. He leads or participates in high-impact projects like MAASive (2024–2026) and the Sino-Danish Center Research Project (2011–present), addressing resilience in value networks and global operations innovation. Research Interests: Supply Chain Management & Integration Sustainability & Green Technologies Manufacturing Strategy & Networks Technology Policy & Digitalization Global Operations & Cross-Border Collaboration Recent Work Trends: Prof. Cheng's 2025 articles emphasize blockchain in sustainable supply chains, green technology investments under carbon policies, and digitalization's ethical implications. His 2024 research explores smart factories, EU battery regulations, and robotization in manufacturing. These studies blend quantitative models with case-based analysis to address real-world challenges. Awards: 2024 Emerald Literati Awards – Outstanding Reviewer Advising & Grants: As PI for multiple Global Operations Management PhD programs (2019–2025), he guides research on digital transformation and university-industry collaboration. His projects receive funding from Danish and international grants, focusing on innovation and resilience in manufacturing networks. Labs/Teams: Collaborates with the Center for Industrial Production at Aalborg University and engages in international partnerships through the Sino-Danish Center. Active editorial roles include Production Planning & Control and Journal of Manufacturing Technology Management .

Robert Xiaoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۴ مورد دیگر

Robert Xiao is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Designing for People research cluster. He holds a Ph.D. from Carnegie Mellon University and a BMath from the University of Waterloo. His research focuses on interactive technologies, including VR/AR interfaces, sensing systems, and cybersecurity. Notable contributions include Lumitrack (tracking system), TouchTools (touch interaction), and CVE-2023-37271 (Python sandbox exploit). Education: Ph.D., Human-Computer Interaction Institute, Carnegie Mellon University; BMath, Computer Science & Combinatorics, University of Waterloo Affiliations: Core member of UBC's Designing for People cluster Research interests span novel input modalities, mixed-reality systems, and security challenges. He actively competes in DEF CON CTF (multiple 1st places) and publishes in top venues like CHI, UIST, and ISMAR. Recent work explores VR decision-making, low-latency tracking, and collaborative AR/VR environments. Awards: SIGCHI Outstanding Dissertation Award, CHI Honorable Mention, DIS Honourable Mention Teaching includes courses on computer systems (CPSC 213), human-computer interaction (CPSC 554X), and cybersecurity (CPSC 436S). His lab develops tools like SurfShare (surface sharing) and VirtualNexus (collaborative AR).

Michael Oppenheimerمشاهده پروفایل

استاد

• Climate Science
• Environmental Policy
• Atmospheric Science
• +۳ مورد دیگر

Michael Oppenheimer is the Albert G. Milbank Professor of Geosciences and International Affairs at Princeton University, affiliated with the Princeton School of Public and International Affairs (SPIA), the Department of Geosciences, and the High Meadows Environmental Institute (HMEI). He directs the Center for Policy Research on Energy and the Environment (C-PREE) and holds roles in multiple research programs. His work bridges climate science and policy, focusing on climate impacts, adaptation, and scientific assessment frameworks. He has advised international bodies, including the IPCC, and contributed to foundational climate policies like the Kyoto Protocol. Education: Ph.D. in Chemical Physics, University of Chicago S.B. in Chemistry, MIT Research Interests: Climate change impacts, sea level rise, compound hazards (e.g., storms and heatwaves), migration dynamics, and the role of scientific assessments in policy. His work emphasizes actionable solutions for climate adaptation and mitigation. Grants & Awards: 2010 Heinz Award for the Environment AAAS Fellow Recipient of the Nobel Peace Prize (via IPCC, 2007) Advising & Labs: Leads the C-PREE, mentors over 20 graduate students, and collaborates with interdisciplinary teams on climate policy and science. Key labs/centers include C-PREE, HMEI, and the NY City Panel on Climate Change.

Bruce N. Walkerمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Auditory Displays
• Data Sonification
• +۷ مورد دیگر

Professor Bruce N. Walker holds a joint appointment in the School of Psychology and School of Interactive Computing at Georgia Institute of Technology, within the College of Sciences. His research focuses on human-centered technology design, emphasizing accessibility, auditory displays, and human-AI interaction. He leads the Sonification Lab, pioneering multimodal interfaces and inclusive technology solutions. He earned his Ph.D. in Human Factors and Human-Computer Interaction from Rice University in 2001. Research Interests: Trust in technology, accessible interfaces, sonification, AI-human collaboration, and HCI in non-traditional environments. Current projects include the AccessCORPS VIP initiative to enhance course accessibility and studies on automated vehicle interaction. Awards: Best Paper Award at AudioMostly 2014 for auditory weather reports research. Active in professional organizations like the International Community for Auditory Display and Human Factors and Ergonomics Society. Teaching: Courses include Research Methods for Human Factors, Sensation and Perception, and HCI Foundations. Supervises interdisciplinary teams in the Sonification Lab R&D Studio and AccessCORPS VIP. Labs/Teams: Sonification Lab (multimodal data exploration) and AccessCORPS (disability-inclusive course design). Collaborates on international projects like the Mwangaza initiative for learners with vision impairment in Kenya.

Yu Huangمشاهده پروفایل

استادیار

• Software Engineering
• Human-Centered AI
• Human Factors in Programming
• +۵ مورد دیگر

Yu Huang is an Assistant Professor of Computer Science at Vanderbilt University with a secondary appointment in the Department of Teaching and Learning at the Peabody School of Education. She is affiliated with the Institute for Software Integrated Systems, the Frist Center for Autism and Innovation, the Vanderbilt Lab for Immersive AI Translation (VALIANT), and the Vanderbilt LIVE Learning Innovation Incubator. Her research focuses on human-centered AI for software engineering, combining human cognition with machine intelligence to enhance software development processes. Educated at the University of Michigan (PhD, 2021), University of Virginia (MS, 2015), and Harbin Institute of Technology (BS, 2011), her work spans software engineering, human factors, AI, and medical imaging. Key projects include the MIND Lab, studying programmer expertise and cognitive processes, and the HumanAISE workshop on Human-Centered AI for Software Engineering. Huang has received significant recognition, including the 2025 ICPC Vaclav Rajlich Early Career Achievement Award and three ACM SIGSOFT Distinguished Paper Awards. Her research is supported by NSF, GitHub, and Vanderbilt initiatives. She advises numerous graduate and undergraduate students, emphasizing diversity and innovation in programming education.

• Software Engineering
• Technical Debt Management
• Software Architecture
• +۳ مورد دیگر

Paris Avgeriou is a Professor of Software Engineering at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Software Engineering and Architecture research group and serves as Editor-in-Chief of the Journal of Systems and Software . His expertise spans technical debt management, software architecture, self-adaptive systems, and embedded systems design. Avgeriou holds an office at Nijenborgh 9, Groningen, and actively advises academic institutions and funding bodies globally. Research Interests: Avgeriou's work focuses on advancing software architecture principles, technical debt lifecycle management, and the integration of AI in software engineering. His research emphasizes practical solutions for improving software quality, maintainability, and system dependability, particularly in embedded and self-adaptive contexts. Recent Contributions: Recent studies include frameworks for benefit-cost-risk decision-making in self-adaptive systems, automated technical debt management using ML, and tools for tracing architecture-related debt. He collaborates internationally, contributing to standards like the Copenhagen Manifesto for human-centered AI in software engineering. Grants & Awards: While no specific awards are listed, his editorial role and frequent conference contributions reflect recognition in the field. He chairs conference tracks and oversees workshops, fostering early-career researchers and artifact evaluation. Labs & Teams: His group is part of the Bernoulli Institute, working on platforms like SDK4ED for embedded systems and tools such as DebtViz for technical debt monitoring. The team explores intersections between systems engineering and software architecture in complex systems-of-systems.

Frank Tongمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Visual Perception
• Visual Cognition
• +۸ مورد دیگر

Frank Tong is a Professor of Psychology at Vanderbilt University in the College of Arts and Science. He leads an active research laboratory investigating the neural mechanisms of human visual perception, cognition, attention, and working memory. His work integrates behavioral experiments, high-resolution fMRI, and computational modeling to decode how visual information is represented and maintained in the brain. Department: Department of Psychology Office: Wilson Hall, Room 531 Email: frank.tong@vanderbilt.edu Phone: 615-322-1780 Education: B.S. in Psychology, Queen's University, Kingston, Canada (Advisor: Barrie Frost) Ph.D. in Psychology, Harvard University (Advisors: Ken Nakayama, Nancy Kanwisher) Postdoctoral Fellow, UCLA (McDonnell-Pew Fellowship, Advisor: Steve Engel) Frank Tong's research centers on understanding how early visual representations interact with higher cognitive functions such as attention and working memory. He has developed pioneering fMRI decoding methods to reconstruct visual features like orientation and object categories from brain activity patterns in the human visual cortex. His lab has demonstrated how these techniques can reveal the neural bases of visual working memory and object-based attentional selection. Current work includes using deep convolutional neural networks as models of human visual processing. His recent publications show a consistent focus on decoding mental states, visual features, and memory contents from brain activity, particularly using fMRI pattern analysis. The research spans visual working memory, attentional modulation, scene perception, and the application of machine learning to neural data. These studies frequently appear in top journals such as Nature , Nature Neuroscience , and Annual Review of Psychology . Scientific Awards: McDonnell-Pew Training Fellowship (1999) Robert K. Root Preceptorship, Princeton (2003) Scientific American Top 50 Award (2004) Young Investigator Award, Cognitive Neuroscience Society (2006) Chancellor's Award for Research, Vanderbilt (2008) Young Investigator Award, Vision Sciences Society (2009) Troland Research Award, National Academy of Sciences Frank Tong has advised numerous graduate students and postdoctoral fellows, many of whom have gone on to successful academic and research careers. His lab has received significant research funding to support its work in cognitive neuroscience and brain imaging. He has also served on the editorial board of the Annual Review of Psychology and as a board member of the Vision Sciences Society, reflecting his leadership in the field. He teaches undergraduate courses including Psy 3760 (Mind and Brain), Psy 3765 (Social Cognition and Neuroscience), and Psy 3780 (The Visual System). His lab continues to explore the interplay between early visual processing and higher cognition using advanced neuroimaging and computational techniques.

Zhu-Tian Chenمشاهده پروفایل

استادیار

• Data Visualization
• Human-Computer Interaction
• Augmented Reality
• +۷ مورد دیگر

Zhu-Tian Chen is an Assistant Professor in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities, where he leads research in data visualization, human-computer interaction, and augmented reality. Prior to this, he held postdoctoral positions at Harvard University and UC San Diego, working with leading researchers in visual computing and interactive design. Ph.D. in Computer Science, Hong Kong University of Science and Technology B.Eng. in Software Engineering, South China University of Technology His research focuses on augmenting human intelligence through hybrid human-AI systems, particularly in everyday and outdoor environments. He specializes in designing intelligent AR interfaces, embedded visualizations, and language-oriented interactions for applications in sports analytics, education, and data analysis. His work integrates human-centered design with applied machine learning to create intuitive and effective visualization tools. The recent trend in his publications shows a strong emphasis on intelligent AR systems for dynamic scenes, LLM-based code generation interfaces, and real-time augmentation of sports videos using natural language and gaze-based interactions. His work frequently appears in top-tier venues such as IEEE VIS, ACM CHI, and UIST. Best Paper Award, ACM CHI'23 Best Short Paper Honorable Mention, EuroVis'23 Best Paper Honorable Mention, IEEE VIS'22 (twice) Certificate of Distinction and Excellence in Teaching, Harvard University Hong Kong Ph.D. Fellowship Dr. Chen actively mentors undergraduate, master’s, and PhD students, as well as visiting scholars and interns, and is building a new research lab focused on visualization for intelligent AR systems. He has served on program committees for major conferences including ACM CHI, IEEE VIS, and EuroVis, and has been invited to speak at institutions such as Apple, JP Morgan, and multiple universities worldwide. He also contributes to the academic community through grant reviewing for NSF and the Department of Energy. He leads research projects in intelligent AR systems for sports, language-oriented interactions with LLMs, and immersive data visualization, often in collaboration with institutions like Harvard, UC San Diego, and HKUST. His lab welcomes students and collaborators interested in visualization, HCI, and applied AI.

• Federated Learning
• Optimization for Machine Learning
• Privacy-Preserving Machine Learning
• +۱۲ مورد دیگر

Sai Praneeth Karimireddy is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), with a courtesy appointment in the Ming Hsieh Department of Electrical and Computer Engineering. He previously held an SNSF postdoctoral fellowship at UC Berkeley under Michael I. Jordan and earned his PhD at EPFL advised by Martin Jaggi. He co-leads the Federated Learning and Data Quality working group at MONAI (NVIDIA) and collaborates with researchers at Apple Research. His research lies at the intersection of optimization, machine learning, statistics, and economics, with a strong focus on federated learning, privacy-preserving machine learning, data valuation, and AI for healthcare. He investigates how data quality, privacy, and incentives shape collaborative ML systems, especially in high-stakes domains like medicine. His work has been deployed at companies such as Meta, Google, OpenAI, and Owkin. His recent publications span top-tier venues including NeurIPS, ICML, ICLR, and JMLR, with influential contributions such as the SCAFFOLD algorithm for federated learning. His research shows a consistent trend toward building robust, private, and incentive-compatible collaborative learning systems, with increasing emphasis on real-world deployment in healthcare and decentralized data markets. 2023 SNSF Mobility Fellowship 2022 Patrick Denantes Memorial Prize for best thesis in computer science 2022 EPFL thesis distinction (top 8%) 2021 Chorafas Foundation Prize for exceptional applied research Capitol One Fellow (2025) He is actively mentoring PhD students and leads a research group focused on foundational and applied challenges in federated and privacy-preserving ML. He teaches graduate courses at USC, including CSCI 599 on Optimization for Machine Learning and CSCI 699 on Privacy-Preserving Machine Learning. He serves as an area chair for ICLR 2025 and co-organizes major workshops on incentives in data sharing and federated learning. His lab collaborates with institutions like NVIDIA, Apple, and Argonne National Laboratory, and he is building a research program centered on sustainable, equitable, and trustworthy AI ecosystems.

Tianyi Linمشاهده پروفایل

استادیار

• Optimization
• Game Theory
• Machine Learning
• +۳ مورد دیگر

Tianyi Lin serves as an Assistant Professor in the Department of Industrial Engineering and Operations Research (IEOR) at Columbia Engineering, Columbia University, a position he assumed in 2024. He holds dual affiliations as a verified Data Science Institute (DSI) Member and an Affiliated Member of both the Financial and Business Analytics Center and the Foundations of Data Science Center. His academic credentials include: Ph.D. in Electrical Engineering and Computer Science, UC Berkeley Postdoctoral Researcher, Laboratory for Information & Decision Systems (LIDS), MIT (2023-2024) M.S. in Operations Research, UC Berkeley M.S. in Pure Mathematics and Statistics, University of Cambridge B.S. in Mathematics, Nanjing University Dr. Lin's research spans optimization theory , game-theoretic models , and machine learning algorithms , with emphasis on nonconvex minimax problems , variational inequalities , and data science applications . His work bridges theoretical guarantees with practical implementations in high-dimensional settings, particularly focusing on convergence properties and computational efficiency in complex systems. Analysis of his 15 most recent publications (2022-2025) reveals dominant themes in high-order optimization methods , no-regret learning in games , and optimal transport algorithms . His contributions demonstrate consistent innovation in developing doubly optimal algorithms for monotone games, spectral regularization techniques for policy optimization, and structure-driven approaches for nonconvex problems, reflecting strong interdisciplinary connections between operations research, computer science, and applied mathematics. No scientific awards or honors were documented in the provided source material. Information regarding student advising and research grants remains unspecified in the current documentation, though his center affiliations suggest active participation in collaborative research initiatives. Dr. Lin maintains significant interdisciplinary engagement through his affiliations with Columbia's Data Science Institute and specialized research centers, positioning his work at the intersection of theoretical optimization and real-world data science applications.