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Haiyan LeeView profile

Professor

• Modern Chinese literature
• Chinese popular culture
• philosophy and literature
• +9 more

Haiyan Lee serves as the Walter A. Haas Professor of the Humanities and Professor of East Asian Languages and Cultures and of Comparative Literature at Stanford University. She has held these positions since joining Stanford in 2009, and currently serves as Chair of the East Asian Languages and Cultures department (2020-present). Her academic journey includes previous teaching appointments at the University of Colorado at Boulder and the University of Hong Kong, along with post-doctoral fellowships at Cornell University and Harvard University. Lee's research spans multiple interdisciplinary fields with particular focus on modern Chinese literature and cultural production. Her work bridges literary studies with law, philosophy, cognitive science, affect theory, gender studies, and environmental humanities. She has developed influential theoretical frameworks including the concept of "high justice" and "low justice" in Chinese legal imagination. Her current research explores animism, cognition, and the Chinese environmental imagination, extending her longstanding interest in human-animal relations. Lee's publications reveal a consistent trajectory examining Chinese cultural production through innovative theoretical lenses. Her recent work shows increasing engagement with legal theory, environmental humanities, and cognitive approaches to literature. She has produced significant scholarship on Chinese concepts of justice, love, and the stranger, moving across historical periods from early 20th century to contemporary China. Biennial Book Prize, Honorable Mention, International Society for Chinese Law and History (ISCLH) (2024) Humanities Seed Grant, Stanford School of Humanities and Sciences (2023-2025) Bass Fellowship in Undergraduate Education, Stanford University (2022-2027) Joseph Levenson Book Prize, The Association for Asian Studies (2009) Professor Lee actively mentors doctoral students across multiple disciplines, serving as dissertation advisor, co-advisor, and committee member for students working at the intersection of Chinese studies, law, literature, and cultural theory. Her teaching includes courses across East Asian humanities, comparative literature, and interdisciplinary environmental studies. She has received significant research support including the Frederick Burkhardt Residential Fellowship from the American Council of Learned Societies and a residency at the Center for Advanced Study in the Behavioral Sciences.

Jennifer RossView profile

Professor

• Biophysics
• Soft Matter Physics
• Biological Condensed Matter Physics
• +5 more

Jennifer Ross is a Professor of Physics and Associate Dean for Creativity, Scholarship, and Research at the College of Arts & Sciences of Syracuse University . As a biophysicist, she investigates how cells organize their interiors through self-assembly and active matter principles, focusing on the microtubule cytoskeleton and enzyme-driven systems using single-molecule imaging . Her research bridges fundamental physics with biological organization . Education: Ph.D. in Physics, University of California, Santa Barbara (2004) B.A. in Physics and Mathematics, Wellesley College (2000) Research Focus: Self-organization of cytoskeletal networks Active matter dynamics in biological systems Motor protein interactions and cargo transport Programming circadian materials via biomolecular systems Microtubule severing mechanisms Recent Article Trends: 2025 studies explore kinesin-driven cytoskeletal composites, urease-DNA origami engineering, and crosslinker-regulated network mechanics 2024-2023 work examines ionic strength effects on microtubules, programmable circadian materials, and motor-cargo dynamics Earlier studies analyze actin-microtubule composites, liquid crystal phase control, and severing enzyme mechanisms Scientific Awards: Fellow of the American Physical Society (APS) and American Association for the Advancement of Science (AAAS) Cottrell Scholar (2025) and STAR Award Margaret Oakley Dayhoff Award (Biophysical Society) Grants: Leads multiple NSF, Sloan Foundation, and Research Corporation grants for projects like "Energy and Entropy Sculpting" and "Explorations: SUPER-Tech SHIP" . Teaching: Offers courses in experimental physics, microscopy, and biophysics, including a globally adopted hands-on microscope-building curriculum. Lab: Heads the Bio-Active Matter Lab , studying how cells harness noisy systems for autonomous organization.

Ruben JuanesView profile

Professor

• Environmental Engineering
• Geophysics
• Energy Resources
• +3 more

Ruben Juanes is a Professor of Civil and Environmental Engineering and Earth, Atmospheric, and Planetary Sciences at MIT. His research focuses on multiphase flow in porous media, energy resources, and CO₂ sequestration. He holds appointments in both departments and has a strong interdisciplinary focus on geosciences and environmental engineering. His work bridges theory, simulation, and experimentation to address energy and environmental challenges. Education: Ingeniero de Caminos (Civil Engineering), University of La Coruña, Spain (1997) MS in Civil Engineering, UC Berkeley (1999) PhD in Civil Engineering, UC Berkeley (2003) Research interests emphasize fluid dynamics in geologic media, especially CO₂ storage, methane hydrates, and ecohydrology. His group develops computational models to predict large-scale Earth processes, with applications to carbon capture and storage, energy resource management, and subsurface engineering. Notable contributions include advancing understanding of fluid displacement mechanisms, capillary trapping in aquifers, and induced seismicity risks during CO₂ injection. His work has been recognized through awards like the APS Fellowship (2024), DOE Early Career Award (2010), and ARCO Energy Professorship (2008). Advising and Grants: Juanes advises graduate students in CEE and EAPS, focusing on thesis research in multiphase flow and geomechanics. His grants include NSF and DOE funding for projects on subsurface energy systems and induced seismicity. His lab, the Juanes Research Group, collaborates on experimental facilities like the FluidFlower CO₂ storage simulator. Labs/Teams: Active in MIT's Carbon Capture, Utilization, and Storage (CCUS) initiatives and the MIT Energy Initiative (MITEI). Collaborates with industry partners on field-scale CO₂ storage validation and subsurface monitoring technologies.

Arvind ParkheView profile

Professor

• Global Supply Chains
• Strategic Alliances
• International Joint Ventures
• +6 more

Arvind Parkhe is a Laura H. Carnell Professor of Strategy and International Business at Temple University’s Fox School of Business. He previously taught at Indiana University’s Kelley School of Business (1989–2003) and holds degrees from IIT Bombay (B.Tech.), Georgia State University (MBA), and Temple University (Ph.D.). His research focuses on strategic alliances, global supply chains, international joint ventures, and trust in cross-border partnerships. He has published in top journals like the Academy of Management Journal and Strategic Management Journal, earning awards such as the AIB Best Dissertation Award (1990) and JIBS Decade Award (2001). Teaching excellence spans all academic levels: recognized as outstanding faculty for Ph.D., MBA, and undergraduate programs. Service leadership includes Vice President of the Consortium for Undergraduate International Business Education (2014), Chair of Fox’s Strategic Management Department (2010–2020), and Managing Director of Fox MBA Programs (2005–2010). He received Temple’s Musser Outstanding Service Award (2012) and Faculty Service Excellence Award (2012). Key research contributions emphasize interorganizational networks, global competitive strategies, and trust mechanisms in alliances. His work bridges theory and practice, addressing challenges in global business operations and strategic collaboration.

Thomas HofmannView profile

Professor

• Machine Learning
• Deep Learning
• Natural Language Understanding
• +3 more

Prof. Dr. Thomas Hofmann is a Full Professor and Head of the Department of Computer Science at ETH Zurich since 2014. He also leads the Institute for Machine Learning. His research focuses on machine learning, deep learning, natural language understanding, and text understanding. Hofmann holds a Ph.D. from the University of Bonn (1997) and has held academic positions at Brown University (1999–2004) and TU Darmstadt. He transitioned to industry as Director of Engineering at Google (2006–2014), leading the Zurich R&D center, before returning to academia. He co-founded Recommind (2000) and 1plusX (Swiss marketing tech company), currently serving as Chief Scientist and board member at 1plusX. Education: Ph.D. in Computer Science, University of Bonn (1997) Postdoctoral Work: MIT (CBCL/AI Lab), UC Berkeley (EECS/ICSI) His research explores advanced machine learning techniques, including diffusion models, generative adversarial networks, and optimization dynamics. Hofmann’s entrepreneurial ventures reflect his focus on applying AI to real-world challenges, such as e-discovery and marketing technology. His work spans theoretical contributions (e.g., neural network training dynamics, continual learning) and applied innovations (e.g., image editing, portrait generation). Hofmann actively bridges academia and industry, influencing both research and commercial AI applications.

• Human-Computer Interaction
• Learning Sciences
• Educational Technology
• +2 more

Jennifer Olsen, PhD, is an Assistant Professor of Computer Science at the University of San Diego since 2020. She holds a PhD, MS, and BS in Human-Computer Interaction and Cognitive Science from Carnegie Mellon University, followed by postdoctoral research at the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. Her research focuses on the intersection of human-computer interaction, cognition, and education, emphasizing collaborative learning and educational technology design from both learner and instructor perspectives. Education: PhD in Human-Computer Interaction, Carnegie Mellon University MS in Human-Computer Interaction, Carnegie Mellon University BS in Cognitive Science, Carnegie Mellon University Research Interests: Dr. Olsen explores how collaboration supports learning, designs technologies to enhance educational practices, and investigates gaze-based metrics for understanding collaborative problem-solving. Her work spans gamified robotics, AI-driven orchestration systems, and virtual reality applications in vocational training. She emphasizes learner-centered design and the integration of social robots and virtual agents in pedagogical settings. Grants/Advising: While no specific grants or advisees are listed, her prolific publication record indicates active involvement in educational technology research and development. Her work addresses challenges in classroom orchestration, multimodal data analysis, and accessibility in educational robotics. Labs/Teams: Collaborates with interdisciplinary teams focused on educational technology, human-robot interaction, and adaptive learning systems. Her research leverages tools like FROG orchestration graphs and eye-tracking technologies to develop practical classroom solutions.

Peichen ZhongView profile

Assistant Professor

• Materials Science
• Machine Learning
• Computational Modeling
• +5 more

Dr. Peichen Zhong is an Assistant Professor in the Department of Materials Science and Engineering at the National University of Singapore (NUS). He leads the Applied Machine Learning and Materials Modeling (AM³) Group, focused on advancing computational methods for clean energy technologies. His research integrates machine learning with atomistic simulations to tackle challenges in battery materials, disordered materials, and sustainable energy systems. Education: B.S. in Physics from University of Science and Technology of China (2018); Ph.D. in Materials Science from UC Berkeley (2023, advised by Prof. Gerbrand Ceder); Postdoctoral training at Lawrence Berkeley National Lab and BIDMaP, co-advised by Persson, Cheng, and Krishnapriyan. Research Interests: Computational modeling of battery cathodes/electrolytes, AI-driven interatomic potentials, statistical mechanics in disordered materials, and generative models for scientific discovery. Key areas include Li/Na-ion batteries, solid-state reactions, and sustainable energy materials. Awards: BIDMaP Emerging Scholar Fellowship (UC Berkeley CDSS, 202?), 2023 Rising Stars in Materials Science (CMU/MIT/Stanford). Labs/Teams: The AM³ Group at NUS MSE focuses on interdisciplinary research combining theory, computation, and AI4Science. Current openings include PhD students and postdoctoral researchers.

Sheng ShenView profile

Professor

• Nanophotonics
• Nanoscale Energy Transport and Conversion
• Advanced Manufacturing
• +7 more

Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.

Aarti SinghView profile

Professor

• Reinforcement Learning
• Bandit Algorithms
• Active Learning
• +7 more

Aarti Singh is a Professor in the Machine Learning Department at Carnegie Mellon University and Director of the NSF AI Institute for Societal Decision Making. She leads research at the intersection of machine learning, statistics, and decision making, with applications to scientific and societal domains. Her work focuses on designing principled interactive algorithms for learning and decision making under uncertainty. Education: Ph.D. in Electrical Engineering, University of Wisconsin-Madison (2008) M.S. in Electrical Engineering, University of Wisconsin-Madison (2003) B.E. in Electronics and Communication Engineering, University of Delhi (2001) Research Interests: Professor Singh's research centers on developing interactive machine learning algorithms that go beyond finding input-output associations to make higher-level decisions about the most informative data and actions. Her work spans autonomous decision making, including active sampling, stochastic optimization, bandits, and reinforcement learning that are statistically optimal, computationally tractable, and robust. She also investigates human factors in decision making, designing algorithms that model and leverage human feedback while accounting for bias, memory effects, and calibration. Her research has applications in material science, cosmology, and peer review systems. Research Trends: Professor Singh's recent publications demonstrate a strong focus on reinforcement learning, particularly in developing more efficient and robust algorithms for decision making under uncertainty. Her work bridges theoretical foundations with practical applications, spanning from fundamental algorithm development to real-world implementation in scientific domains. There's a clear trajectory toward integrating human factors into decision-making algorithms, with significant contributions to peer review systems and preference learning. Scientific Awards: NSF Career Award United States Air Force Young Investigator Award A. Nico Habermann Faculty Chair Award Harold A. Peterson Best Dissertation Award Multiple paper awards Advising and Grants: Professor Singh has advised numerous PhD and master's students, many of whom have gone on to faculty positions or research roles at leading institutions. Her research is supported by prestigious grants from ONR, Simons Foundation, AFRL, ARL, and NSF. She serves as General Chair (2025) and Program Chair (2020) for the International Conference on Machine Learning (ICML) and has held leadership roles in multiple professional organizations. Research Team: Professor Singh leads a vibrant research group within the Machine Learning Department at CMU, with current PhD students working on topics including reinforcement learning, human-AI collaboration, and decision making under uncertainty. She also directs the NSF AI Institute for Societal Decision Making, which brings together researchers from multiple disciplines to develop AI systems that support human decision making in societal contexts.

Rhonda GoldmanView profile

Professor

• Clinical Psychology
• Emotion-Focused Therapy
• Psychotherapy
• +7 more

Rhonda Goldman is a Full Professor in the Clinical Psychology Department at The Chicago School of Professional Psychology in Chicago, Illinois. She is a licensed Clinical Psychologist in Illinois and runs her private practice, Emotion-focused Therapy, Chicago, where she sees both couples and individuals. Dr. Goldman is a founding board member of the International Society of Emotion-focused Therapy and serves as President of the Emotion-focused Therapy Institute. Dr. Goldman earned her academic credentials from York University in Toronto, Ontario, Canada, receiving her Bachelor of Arts in 1987, Master of Arts in 1991, and Doctor of Philosophy in Clinical Psychology in 1997. She taught at the Illinois School of Professional Psychology for 22 years before transitioning to her current position at The Chicago School of Professional Psychology following the closure of the Illinois School. Dr. Goldman is a leading expert in Emotion-Focused Therapy (EFT), a therapeutic approach that integrates elements of client-centered therapy, Gestalt therapy, and modern emotion theory. Her research focuses on EFT for couples, emotional processes, empathy, vulnerability, depression, case formulation, and self-soothing. She has authored six texts on EFT and two professional videos published by the American Psychological Association. Dr. Goldman teaches graduate courses in Humanistic and Experiential Psychotherapy, Psychotherapy Seminars, and Emotion-Focused Therapy, emphasizing the importance of emotional processing in therapeutic change. Dr. Goldman's publications demonstrate a consistent focus on advancing Emotion-Focused Therapy through both theoretical development and practical application. Her work spans individual therapy, couples therapy, case formulation, and therapist training, with recent emphasis on adapting EFT for online delivery. Her research shows how emotional awareness and processing serve as central mechanisms of change in psychotherapy, with applications across various clinical issues including depression and relationship distress. Dr. Goldman is actively involved in professional organizations that support the development and dissemination of Emotion-Focused Therapy. She serves as a founding board member of the International Society for Emotion-focused Therapy, past-president of the Society for the Exploration of Psychotherapy Integration, Action-Editor for the Journal of Person-centered and Experiential Psychotherapies, and member of the Society for Psychotherapy Research. As an educator and clinician, Dr. Goldman has mentored numerous professionals in the field of psychotherapy. She travels internationally conducting training workshops for mental health professionals in Emotion-focused therapy for Couples and Individuals across Europe, Asia, and North America. Her work bridges research and practice, emphasizing the importance of emotional processing in therapeutic change while maintaining a strong commitment to evidence-based practice. Dr. Goldman co-founded the Emotion-focused Therapy Institute (EFTI), which facilitates and fosters training and educational opportunities for psychologists and therapists interested in incorporating EFT into their professional practices. Through EFTI and her international workshops, she has created a global community of practitioners dedicated to advancing Emotion-Focused Therapy.

Steven JacksonView profile

Professor

• Technology Ethics
• Infrastructure Studies
• Human-Computer Interaction
• +7 more

Steven Jackson is a Professor of Information Science and Science and Technology Studies at Cornell University's Bowers College of Computing and Information Science, with additional graduate field appointments in Communication and Public Affairs. Since July 2023, he has served as Vice-Provost for Academic Innovation at Cornell, and previously held leadership positions as Chair of Information Science and Dean of William Keeton House. His work bridges academic research with significant institutional leadership in higher education innovation. Dr. Jackson's research focuses on critical intersections of technology, society, and the environment, with three primary strands: technology ethics, law and policy; maintenance, repair and sustainability; and technology, inequality and global development. His work draws from American pragmatism, political economy, and science and technology studies, integrating methods from sociology, anthropology, philosophy, and media studies. He is particularly interested in how computing practices meet social and material worlds, with implications for infrastructure, collaboration, sustainability, and cultural practice. His recent publications reveal a strong emphasis on repair as both theoretical concept and practical methodology, exploring 'ordinary hope' as a framework for technological engagement and examining unmaking as a necessary counterpart to design. The research spans diverse geographical contexts from the global North to South, addressing caste dynamics in computing, digital authoritarianism, and infrastructure challenges in developing contexts. Dr. Jackson has received significant recognition including an NSF CAREER award and more than twenty paper awards at leading computing and information science venues. His research has been supported by major organizations including the U.S. National Science Foundation, Social Science Research Council, Ford Foundation, Sloan Foundation, World Bank, Intel Research, Atkinson Center for Sustainability, and the Canadian Social Science and Humanities Research Council. As an advisor, Dr. Jackson has mentored numerous graduate students who have gone on to prominent positions at institutions worldwide. He currently advises Jen Liu, Amy Cheatle, Daniel Mwesigwa, Johan Michalove, and Ritik Batra, while his former students include Palashi Vaghela (Assistant Professor at Simon Fraser University), Samir Passi (Responsible AI Researcher at Microsoft), Maggie Jack (Assistant Professor at NYU), and Ranjit Singh (Senior Researcher at Data and Society). Dr. Jackson convenes the Computing On Earth Lab, an experimental collaboration bringing together social scientists, humanists, artists, and engineers to rethink the material and planetary foundations of computing. The lab reflects his commitment to interdisciplinary approaches that address computing's environmental impacts and sustainability challenges.

Romain LopezView profile

Assistant Professor

• Single-cell omics
• Spatial transcriptomics
• Deep generative models
• +5 more

Romain Lopez is an Assistant Professor of Computer Science and Biology at New York University, with a joint appointment in the Courant Institute of Mathematical Sciences and the Department of Biology. He will be joining NYU in September 2025, bringing expertise at the intersection of machine learning and computational biology. Prior to joining NYU, he was a Postdoctoral Fellow at Genentech and Stanford Medicine from 2021 to 2025, working with Jonathan Pritchard and Aviv Regev. Dr. Lopez received his educational training at prestigious institutions: PhD in Computer Science (2021) from the University of California, Berkeley, advised by Mike Jordan and Nir Yosef M.S. in Applied Mathematics (2016) from École polytechnique, Palaiseau, France Dr. Lopez's research focuses on developing machine learning methods to understand biological systems at the cellular level. His work bridges computational techniques with biological applications, particularly in single-cell and spatial omics analysis. He pioneered probabilistic approaches for single-cell analysis with scVI and co-developed scvi-tools, now widely adopted tools in the field. His research spans deep generative models, causal inference, perturbation modeling, and representation learning for biological data. His publication record demonstrates a consistent trajectory of innovation in computational biology, with recent work focusing on spatial biology, disentangled representations of cellular perturbations, and causal modeling of cellular responses. He has made significant contributions to the field of single-cell analysis, developing methods that help scientists interpret complex cellular data and predict how cells respond to various perturbations. Dr. Lopez has received numerous honors and awards for his research: Best Paper Award from the ICML Workshop on AI for Science (2024) Best Paper Award Honorable Mention from the AAAI Conference on Artificial Intelligence (2021) Best Student Poster Award from the ICML Workshop on Computational Biology (2019) UC Berkeley EECS Departmental Graduate Fellowship (2016) Carnot Foundation Fellowship (2016) Monahan Foundation Fellowship (2016) French National Defence Medal, Bronze Echelon (2014) At NYU, Dr. Lopez will lead the Biological Machine Learning group, which develops probabilistic machine learning methods to uncover biological mechanisms governing cellular behavior and disease. His lab focuses on creating tools that transform complex cellular data into biological insights, with applications in understanding cancer, immune responses, and fundamental cellular processes. His work has significant implications for precision medicine and drug discovery.

Timothy J. PowerView profile

Professor

• Democratization
• Political Institutions
• Comparative Politics
• +3 more

Professor Timothy J. Power is Head of the Social Sciences Division and Professor of Latin American Politics at the University of Oxford, affiliated with the Oxford School of Global and Area Studies (OSGA) and the Department of Politics. He previously directed the Latin American Centre from 2008 to 2012 and has been a leading scholar in comparative politics since 2005. Research Interests: Democratization, political institutions (parties, legislatures, elections), coalitional presidentialism, Brazil, Latin America, new democracies. Awards: None listed in provided text. Advising: No specific students mentioned. Grants: No explicit grants listed, but research involves long-term projects like the Brazilian Legislative Surveys. Labs/Teams: Co-directs the Brazilian Legislative Surveys with Fundação Getúlio Vargas and contributes to cross-regional comparative studies at OSGA. His work analyzes democratization in Latin America, particularly Brazil, focusing on legislative dynamics, coalition governments, and political institutions. Recent articles explore cabinet proportionality, portfolio allocation, and ideological shifts in post-authoritarian settings.

Emily HannumView profile

Professor

• Poverty and Child Welfare
• Gender and Ethnic Stratification
• Sociology of Education
• +4 more

Emily Hannum is a Professor of Sociology and Education at the University of Pennsylvania's College of Arts & Sciences, where she also serves as Associate Dean for Social Sciences. She is affiliated with the Population Studies Center, Center for the Study of Contemporary China, Graduate School of Education, and Penn Development Research Initiative. Education: PhD in Sociology from University of Michigan (1998) Research Focus: Poverty and child welfare, gender and ethnic stratification, sociology of education Projects: Gansu Survey of Children and Families, climate-environment-childhood inequalities in LMICs Workshops: Co-organizer of Penn Education and Inequality Workshop Her research explores childhood poverty in China, demographic impacts on education systems, and climate risks affecting children's welfare. She investigates environmental hazards, educational disparities, and family separation effects across China, India, and low/middle-income countries. Recent publications analyze educational expansion in East Asia, climate crisis impacts on child health, and gender disparities in Latin America. She directs longitudinal studies on rural poverty and collaborates on cross-national projects related to environmental and educational equity. Scientific awards include the Stanley I. Sheerr Term Professorship in Social Sciences.

David A. SmithView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Machine Translation
• +3 more

David A. Smith is an Associate Professor at the Khoury College of Computer Sciences, Northeastern University. His research focuses on Natural Language Processing (NLP) and computational linguistics, with applications in machine translation, information retrieval, digital humanities, and social sciences. He is a founding member of the NULab for Texts, Maps, and Networks, a research center focused on digital humanities and computational social sciences. Smith's work has been funded by grants from the Mellon Foundation, NEH, and IMLS, supporting projects such as the Viral Texts initiative analyzing 19th-century newspaper networks and the Oceanic Exchanges project tracking transnational information flows. He has contributed to advancements in OCR for historical texts, text reuse detection, and computational analysis of classical languages. He has advised numerous PhD students, including Shijia Liu, Si Wu, and Ryan Muther, and teaches courses like Natural Language Processing and Information Retrieval. His research has been featured in outlets like Wired and the Economist .