جستجوی استاد راهنمای دانشگاهی

Maja J Matarićمشاهده پروفایل

استاد

• Socially Assistive Robotics
• Human-Robot Interaction
• Assistive Technology
• +۷ مورد دیگر

Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.

Shahram Ghiasinejadمشاهده پروفایل

مدرس ارشد

• Education Technology
• Student Engagement
• Equity in Education
• +۳ مورد دیگر

Shahram Ghiasinejad is a Senior Lecturer in the Department of Psychology at the University of Central Florida (UCF), affiliated with the College of Sciences. He joined UCF in 2007 and specializes in education technology, student engagement, and equity in academic settings. Dr. Ghiasinejad holds a B.A. in Computer Science from the University of Texas at Austin, and an M.S. and Ph.D. in Cognition and Neuroscience from the University of Texas at Dallas. Bachelor of Arts: Computer Science, University of Texas at Austin Master of Science: Applied Cognition and Neuroscience, University of Texas at Dallas Doctor of Philosophy: Cognition and Neuroscience, University of Texas at Dallas His research focuses on leveraging experimental and computational methods to understand human language comprehension, alongside innovative approaches to support underrepresented students through multimedia tools and undergraduate research initiatives. Recent work emphasizes equity and engagement in higher education, including strategies for transfer students and first-generation learners. Publications highlight themes such as JoVE video integration for marginalized students, the role of undergraduate research in fostering equity, and creative solutions for academic challenges faced by underrepresented groups. While no formal awards are listed, his work underscores a commitment to inclusive education and student success.

• Cultural studies
• Literary studies
• Language studies
• +۳ مورد دیگر

Rachel Morley is an Associate Professor at the School of Slavonic and East European Studies (SSEES), University College London. She holds a BA in French Language and Literature from the University of Oxford (1992), followed by BA, MA, and PhD degrees from UCL (1999, 2001, 2011). Her roles include Academic Director of Education and Student Experience at SSEES (2022–2027) and Co-Convenor of the UCL SSEES Cinema Research Group. Dr. Morley's research focuses on Cinema studies Cultural studies Feminist and queer theory Literary studies with emphasis on Soviet/Russian cinema, gender representation, and film historiography. She held a Leverhulme Trust Research Fellowship (2020–2022) for her project on female subjectivity in contemporary Russian cinema. Her teaching spans Russian cinema, poetry, language, and translation. Past roles include Postgraduate Teaching Assistant at SSEES (1999–2009) and lecturer at the University of Cambridge (2006, 2008). She has also supported international students as SSEES International and Affiliate Tutor (2014–2018). Key Achievements: Leverhulme Trust Research Fellowship Fellow of the Higher Education Academy (2016) Her work bridges film, literature, and cultural history, emphasizing underrepresented narratives and feminist perspectives in Russian and Soviet cinema.

Fei-Fei Liمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Fei-Fei Li is the Sequoia Capital Professor in Computer Science at Stanford University and Founding Co-Director of the Stanford Institute for Human-Centered AI (HAI). She holds courtesy appointments in the Graduate School of Business and is a Senior Fellow at HAI. Her work bridges AI research with interdisciplinary applications in healthcare, robotics, and policy. Dr. Li pioneered the ImageNet dataset, instrumental in the AI revolution, and co-founded World Labs to advance spatial intelligence and generative AI. Education: B.A. in Physics, Princeton University (1999) Ph.D. in Electrical Engineering, Caltech (2005) Doctorate (Honorary), Harvey Mudd College (2022) Research Interests: AI ethics, computer vision, robotic learning, healthcare applications, and human-AI collaboration. Her teams developed frameworks like MOMA for activity recognition and BEHAVIOR for embodied AI benchmarks. She advocates for diversity in tech and co-founded AI4All to mentor underrepresented students. Key Contributions: ImageNet and ImageNet Challenge Stanford Vision and Learning Lab (SVL) Policy advisory roles for U.S. Senate, UN Secretary-General, and California Governor Labs & Initiatives: Leads the People, AI & Robots Group (PAIR), Partnership in AI-Assisted Care (PAC), and the Human-Centered AI Institute. Her work emphasizes ethical AI deployment and societal impact. Awards: VinFuture Prize (2024), IEEE Fellow, National Academy memberships (Engineering, Medicine, Arts & Sciences), and recognition as one of Time’s AI100 Influencers.

• Computer Vision
• Machine Learning
• Human-Computer Interaction
• +۳ مورد دیگر

Olga Russakovsky is an Associate Professor in the Computer Science Department at Princeton University, with additional affiliations at the Center for Statistics and Machine Learning and the Center for Information Technology Policy. She serves as Associate Director of the Princeton AI Lab and chairs the Board of Directors for AI4ALL, the nonprofit she co-founded in 2017. Her research integrates computer vision with machine learning, human-computer interaction, and fairness/transparency in AI systems. She leads the Visual AI Lab, focusing on developing intelligent systems that understand the visual world while addressing societal impacts of technology. Dr. Russakovsky is a prominent advocate for diversity in AI. She co-founded multiple educational initiatives including: Stanford AI4ALL (originally SAILORS, 2015) for high school girls Princeton AI4ALL (2018) for underrepresented racial/ethnic groups AI4ALL nonprofit (2017) to cultivate diverse AI leadership AI4ALL Open Learning (free K-12 AI curriculum) College Pathways program for undergraduate inclusion She has influenced policy through congressional engagement and media outreach, with featured coverage in MIT Technology Review, TheAtlantic, Wired, and EdWeek addressing AI's diversity crisis.

• Combinatorics
• Graph Theory
• Discrete Mathematics
• +۳ مورد دیگر

Sophie Spirkl is an Associate Professor (with tenure) in the Department of Combinatorics and Optimization at the University of Waterloo. Previously, she held postdoctoral positions at Princeton University (as an NSF postdoc and instructor, supervised by Maria Chudnovsky) and at Rutgers University (under Jeff Kahn). She earned her PhD from Princeton University under the guidance of Maria Chudnovsky and Paul Seymour. Her research focuses on graph theory and combinatorics, with notable contributions to induced subgraphs, tree decompositions, chromatic number properties, and structural graph theory. She is a recipient of the 2023 Sloan Research Fellowship and co-founded the diamond open-access journal Innovations in Graph Theory . Education: PhD in Mathematics, Princeton University (2016–2020) Postdoctoral Fellowships: Princeton (2020–2022), Rutgers (2018–2020) Research Interests: Dr. Spirkl’s work spans multiple areas of combinatorics, including structural graph theory, extremal graph theory, and algorithmic graph theory. She has published extensively on topics such as induced subgraph obstructions, χ-boundedness, tree decompositions, and the Erdős–Hajnal conjecture. Her research often intersects with theoretical computer science, particularly in parameterized complexity and graph colorings. Awards & Recognition: 2023 Sloan Research Fellowship Contributions to the Innovations in Graph Theory journal Academic Contributions: Her articles address foundational problems in graph theory, such as the Erdős–Hajnal conjecture for C₅, logarithmic treewidth in even-hole-free graphs, and induced saturation for cycles. She collaborates with leading researchers like Maria Chudnovsky and Paul Seymour, advancing the field through rigorous combinatorial analysis. Community Engagement: She coordinates the Women in Math Directed Reading Program at Waterloo, supporting underrepresented groups in mathematics. Her spouse, Logan Crew, is a Research Assistant Professor at the same institution.

Jana Diesnerمشاهده پروفایل

استاد

• Human-centered data science
• Computational social science
• Network science
• +۵ مورد دیگر

Jana Diesner is a Professor at the Technical University of Munich (TUM), leading the Human Centered Computing group within the School of Social Science and Technology. Previously, she held a tenured position at the University of Illinois Urbana Champaign (UIUC) School of Information Sciences. She earned her PhD in Computation, Organizations, and Society from Carnegie Mellon University's School of Computer Science. Her research focuses on human-centered data science, computational social science, network science, and ethical AI. She integrates methods from natural language processing, machine learning, and social science theories to study societal systems and responsible computing. Key areas include crisis informatics, data regulations, and impact assessment of media and research. Leadership Academy Fellow for underrepresented STEM leaders (2020) R.C. Evans Data Analytics Fellow (2018) NCSA Faculty Fellow (2015) Siebel Scholarship (2011) Recent work addresses stereotypes in large language models, reliability of crisis data extraction, and societal impact assessment of research. She advises on projects like the NCSA Faculty Fellowship and collaborates with organizations globally. Her teaching includes independent studies at TUM. Her research has been presented at venues like the International Conference on Computational Social Science (IC2S2), European Computational Social Science Symposium, and conferences on ethics in AI. She actively engages in initiatives promoting inclusive STEM leadership and responsible data science practices.

Heewon Changمشاهده پروفایل

استاد

• Autoethnography
• Organizational Leadership
• Qualitative Research Methods
• +۳ مورد دیگر

Heewon Chang, Ph.D., is a Professor and Chair in the PhD in Organizational Leadership Department at Eastern University's College of Business and Leadership. She specializes in autoethnography and qualitative research methods, with notable works including Autoethnography as Method (2008). Her research focuses on multicultural education, leadership development, and collaborative learning within marginalized communities. Dr. Chang has contributed to advancing methodologies like Collaborative Autoethnography (CAE) and the Transformative Autoethnography Model (TAM). Her academic journey includes an MA in Education and Anthropology from the University of Oregon (1984) and Pennsylvania Elementary Teaching Certification (2000). She has served in leadership roles, emphasizing equity and inclusion in higher education. Her work bridges personal narratives with sociocultural analysis, impacting fields like organizational behavior and pedagogy. Key research themes include BIPOC doctoral student experiences, online leadership program efficacy, and systems thinking in education. Dr. Chang’s publications span journals and edited volumes, reflecting her commitment to democratizing knowledge through participatory research. She has also contributed to journal editing and community service, advocating for educational equity and mentorship for underrepresented scholars.

Sandy J. Wayneمشاهده پروفایل

استاد

• Leadership
• Organizational Behavior
• Diversity and Inclusion
• +۵ مورد دیگر

Sandy J. Wayne serves as Dean of the College of Business Administration and Professor of Management at the University of Illinois Chicago (UIC), where she leads academic initiatives while maintaining an active research program. An internationally recognized expert in workplace leadership, her work focuses on developing high-performing employees through effective team leadership and organizational practices that enhance motivation and performance. She also investigates systemic barriers affecting the upward mobility of women and people of color in corporate environments. Dr. Wayne earned her academic credentials from: PhD in Management, Texas A&M University MBA, Illinois State University BS in Business Administration, Illinois State University Her research program spans leadership dynamics, organizational behavior, and diversity science. She examines how manager-employee relationships impact engagement and performance, with particular emphasis on work-family balance and career trajectory barriers for underrepresented groups. Her work bridges theoretical rigor with practical applications for organizations seeking to build inclusive, high-performance cultures through evidence-based leadership development. Analysis of her recent publications (2014-2024) reveals three dominant research streams: leader-member exchange theory (particularly LMX differentiation effects), servant leadership measurement and outcomes, and diversity dynamics in advancement pathways. Her work consistently appears in top-tier journals like Journal of Applied Psychology and Academy of Management Journal , demonstrating methodological sophistication through multi-level analyses and cross-cultural investigations. Dr. Wayne's scientific contributions have earned significant recognition: Decennial Influential Article Award for 2015 publication (2025) University Scholar, University of Illinois System (2020-2023) Faculty Impact Award, UIC Business (2019) Fellow, Academy of Management (2019) Decennial Influential Article Award for 2008 publication (2018) As Director of the Institute for Leadership Excellence and Development since 1996, she has cultivated a robust research ecosystem while leading institutional initiatives like the UIC Business Cohort Program and Business Scholars Program. Her administrative leadership extends to faculty development through her former role as Associate Dean for Faculty Affairs (2014-2022), demonstrating sustained commitment to academic excellence and organizational growth.

Flavio P. Calmonمشاهده پروفایل

دانشیار

• Information Theory
• Machine Learning
• Artificial Intelligence
• +۷ مورد دیگر

Flavio P. Calmon is the Thomas D. Cabot Associate Professor of Electrical Engineering at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS). He holds a Ph.D. in Electrical Engineering and Computer Science from MIT, an M.Sc. from the Universidade Estadual de Campinas (Brazil), and a B.Sc. from the Universidade de Brasília (Brazil). His research focuses on the intersection of information theory, machine learning, and statistics, with applications to privacy, fairness, and trustworthy AI systems. He has received prestigious awards, including the NSF CAREER Award (2018) and the James L. Massey Award (2024). Research interests include developing theoretical foundations for fair and private machine learning, understanding algorithmic bias, and designing systems with provable guarantees. His work spans information-theoretic tools for responsible AI, distributed privacy mechanisms, and understanding the limits of fairness interventions. He has advised numerous students, including Hao Wang, Hsiang Hsu, and Lucas Monteiro Paes, many of whom now hold prominent roles in academia and industry. Calmon's research is supported by grants from NSF, Amazon, Google, and IBM. He has organized workshops on AI in Brazil and leads initiatives to broaden participation in STEM from underrepresented groups. His lab collaborates with institutions globally and emphasizes both foundational theory and practical applications of machine learning.

Ximena E. Bernalمشاهده پروفایل

استاد

• Animal Communication
• Behavioral Ecology
• Sensory Ecology
• +۲ مورد دیگر

Ximena E. Bernal is a Professor of Biological Sciences at Purdue University's College of Science, where she leads the Bernal Lab. Her research focuses on animal communication systems in anurans (frogs and toads) and their interactions with eavesdropping enemies and anthropogenic environmental changes. Her lab integrates behavioral and sensory ecology to investigate how natural enemies like frog-biting midges and frog-eating bats shape signal evolution in vocal anurans. Research examines the dual pressures of predation and sexual selection, alongside human impacts including traffic noise and habitat fragmentation on threatened amphibian populations. The work combines neuroethological mechanisms with functional analyses of communication networks. Recent publications demonstrate how defensive strategies in male túngara frogs alter attractiveness to both mates and predators, revealing receiver-dependent trade-offs in signal evolution. This research highlights the vulnerability of communication systems to environmental disruption and the ecological consequences of signal interference. Dr. Bernal actively promotes inclusive excellence in STEM through mentoring and program development. She supports undergraduate and graduate education initiatives aimed at broadening participation of underrepresented groups in science. The Bernal Lab operates as a collaborative unit within Purdue University and maintains a research associate affiliation with the Smithsonian Tropical Research Institute. Field and laboratory studies focus on anuran communication networks in natural contexts, emphasizing the integration of mechanistic and functional approaches to understand signal evolution.

• Artificial Intelligence
• Natural Language Processing
• Multimodal Dialogue Processing
• +۶ مورد دیگر

Cecilia O. Alm is a Professor in the Department of Psychology within the College of Liberal Arts at Rochester Institute of Technology (RIT), where she serves as the Artificial Intelligence Program Director. She holds multiple leadership roles including Director of the Center for Human-aware AI and Director of the Computational Linguistics and Speech Processing Lab (CLaSP). Her institutional affiliations span the School of Information, Ph.D. Programs in Cognitive Science and Computing and Information Sciences, Department of Computer Science, and MS in Data Science program. Dr. Alm earned her Ph.D. from the University of Illinois at Urbana-Champaign. Her research focuses on human-centered artificial intelligence with particular emphasis on linguistic and multimodal sensing, affective computing, and natural language processing. She investigates how AI systems can better understand and respond to human communication through multimodal dialogue processing, with applications in accessibility, education, and healthcare. Her recent publications demonstrate a strong trend toward developing inclusive AI systems, particularly through projects addressing Deaf community needs (MULTICOLLAB-ASL), subtle emotion recognition (FUSE corpus), and bias mitigation in NLP. The work consistently integrates multimodal data streams (speech, gaze, gesture) to create more responsive human-AI interaction frameworks. Current research directions emphasize diversity in AI education, visual prosody in sign languages, and human-in-the-loop AI development. Dr. Alm leads several significant NSF-funded initiatives including the AWARE-AI program, IRES AI-PROWIL international research experience, and collaborative projects with Gallaudet University focused on Deaf scientist-centered AI research. She has secured over $2.5 million in external funding for her work on human-aware AI systems. She directs the CLaSP lab which provides research opportunities for PhD, MS, and undergraduate students, with graduates employed at major technology companies including Amazon, Apple, Microsoft, and Facebook. The lab focuses on real-world AI applications in accessibility, human-robot interaction, and multimodal communication systems.

Kenneth Riceمشاهده پروفایل

استاد

• Perfectionism
• Stress and Stress Management
• Psychological Assessment and Measurement
• +۵ مورد دیگر

Kenneth Rice is a Professor and holds the Ken and Mary Matheny Endowed Professorship in the Department of Counseling and Psychological Services at Georgia State University's College of Education & Human Development. He co-directs the Ken Matheny Center for the Study of Stress, Trauma, and Resilience. His research focuses on perfectionism, stress management, and psychological resilience, with studies addressing diverse populations such as STEM students, international students, and adult learners in literacy programs. He has held faculty positions at Penn State, Purdue, Michigan State, and the University of Florida. Education: B.S. with High Honors in Psychology, University of Florida (1986) Ph.D. in Counseling Psychology, University of Notre Dame (1990) His research explores how personal traits (e.g., perfectionism), emotion regulation, and relational factors influence health, mental health, and academic/work outcomes. He has developed psychometric tools for use in educational and clinical settings. His work emphasizes underrepresented groups and cross-cultural comparisons, such as sociodemographic factors impacting stress during the pandemic. Publications span journals like Journal of Counseling Psychology , Journal of Personality Assessment , and Psychotherapy . He is a Fellow of the American Psychological Association. His lab, the Personality, Stress and Adjustment Lab, investigates adaptive and maladaptive responses to stress. Collaborations include the Ken Matheny Center, focusing on trauma and resilience interventions.

Gary G. Bennettمشاهده پروفایل

استاد

• Digital Health Interventions
• Obesity Prevention
• Health Equity
• +۴ مورد دیگر

Gary G. Bennett serves as Dean of Trinity College of Arts & Sciences and Professor of Psychology & Neuroscience, Global Health, Medicine, and Nursing at Duke University. His research develops digital therapeutics for chronic disease prevention. Research programs focus on: mHealth interventions for obesity/hypertension Equity in digital health access Nutrition assistance program optimization Clinician bias mitigation strategies Behavioral trial design for underrepresented groups Recent publications (2023-2025) evaluate digital DASH diet interventions, clinician bias training, equitable trial recruitment, and WIC nutrition programs. Studies emphasize scalable solutions for underserved populations. Leadership and impact: As dean since 2023, Bennett oversees Trinity College's academic programs. Previously as Vice Provost for Undergraduate Education, he launched QuadEx and DukeLIFE initiatives. Bennett founded multiple digital health ventures acquired by Anthem and Health Dialog. His NIH-funded research has produced 200+ publications on behavioral interventions.

Iona Chengمشاهده پروفایل

استاد

• Cancer Epidemiology
• Genetic Epidemiology
• Racial/Ethnic Differences in Cancer Risk
• +۵ مورد دیگر

Iona Cheng is a Professor in the Department of Epidemiology and Biostatistics at the University of California, San Francisco (UCSF), where she conducts groundbreaking research in cancer epidemiology. She serves as co-Investigator of the SEER Greater Bay Area Cancer Registry and is Principal Investigator of multiple NIH- and foundation-funded projects examining genetics, lifestyle factors, and neighborhood characteristics in relation to cancer risk. Dr. Cheng has developed an extensive research program focused on racial/ethnic differences in cancer risk and leads population-based cancer surveillance studies that document variations in cancer incidence and mortality patterns across diverse racial and ethnic groups. University of California, Davis, BS, 1990–1994, Physiology Yale University, MPH, 1999–2001, Chronic Disease Epidemiology University of Southern California, PhD, 2001–2005, Epidemiology University of California, San Francisco, Postdoc, 2006–2008, Genetic and Molecular Epidemiology Dr. Cheng's research spans multiple disciplines within cancer epidemiology, with particular emphasis on understanding how environmental exposures, genetic factors, and social determinants interact to influence cancer risk and outcomes across different racial and ethnic populations. Her work frequently examines the impact of air pollution, endocrine-disrupting chemicals, and neighborhood characteristics on cancer development and survival. She has made significant contributions to understanding cancer disparities among Asian American, Native Hawaiian, and Pacific Islander populations, bringing attention to the unique cancer risks and outcomes within these understudied groups. Her research often leverages the Multiethnic Cohort Study, one of the largest prospective studies of cancer incidence and mortality across diverse racial/ethnic populations. Analysis of Dr. Cheng's recent publications reveals a consistent focus on environmental and social determinants of cancer risk across multiple organ sites. Her work demonstrates a sophisticated integration of epidemiological methods with environmental exposure assessment, genetic analysis, and health disparities research. Many of her studies examine the intersection of environmental exposures and racial/ethnic disparities in cancer outcomes, particularly regarding breast cancer, lung cancer, and other malignancies. She has published extensively on the impact of air pollution on cancer risk and survival, as well as the effects of endocrine-disrupting chemicals like bisphenol A, parabens, and phthalates. American Association for Cancer Research Scholar-in-Training Award (2007) National Institutes of Health Loan Repayment Award (2007) National Institutes of Health Loan Repayment Renewal Award (2009) American Association for Cancer Research Faculty Scholar Award (2011) National Institutes of Health Loan Repayment Renewal Award (2011) National Institutes of Health Loan Repayment Renewal Award (2013) American Journal of Epidemiology/Society of Epidemiology Research Top 10 manuscripts (2014) Cancer Prevention Institute of California Mentoring Award (2015) American Society of Human Genetics Top poster As Principal Investigator of multiple NIH-funded projects, Dr. Cheng oversees substantial research grants focused on cancer epidemiology and health disparities. Her work often involves large interdisciplinary collaborations with researchers across multiple institutions, including the Multiethnic Cohort Study which follows over 200,000 participants from diverse racial/ethnic backgrounds. She has demonstrated leadership in mentoring junior researchers, particularly those from underrepresented backgrounds in science, as evidenced by her Cancer Prevention Institute of California Mentoring Award. Her research program integrates data from cancer registries, electronic health records, and geospatial information to provide comprehensive insights into cancer patterns and risk factors. Dr. Cheng's research is closely connected to the UCSF Helen Diller Family Comprehensive Cancer Center and leverages collaborations with Lawrence Berkeley National Laboratory, which provides advanced technological resources for cancer research. Her work benefits from access to extensive cohort data, sophisticated exposure assessment methods, and interdisciplinary expertise in genetics, environmental science, and computational biology available through these institutional partnerships. She frequently collaborates with researchers studying the genetic and environmental determinants of cancer across multiple organ systems, contributing to a more comprehensive understanding of cancer etiology and prevention strategies.