Stanford University
Showing 401-420 of 1,602 Results
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Igor Daniel de Araujo Evangelista
Postdoctoral Scholar, Photon Science, SLAC
BioDr. Evangelista's primary research focus lies in computational modeling and theoretical analysis of semiconductor materials using advanced quantum mechanical methods, including Density Functional Theory, Quantum Monte Carlo, and ab-initio Molecular Dynamics. Evangelista investigates the electronic, structural, and mechanical properties of materials, collaborating closely with experimental groups to bridge theoretical predictions with empirical results. He is also interested in the development of empirical potentials and enhancing materials modeling through the application of machine learning techniques.
Evangelista entered the Department of Materials Science and Engineering at the University of Delaware as a Ph.D. candidate in 2018, after completing an master degree in Physics 2016-2018 at Federal Fluminense University (Brazil). Recent work includes collaborations with experimental groups to bridge theoretical predictions with empirical results, as well as applying machine learning to creating of empirical potentials to accelerate materials modeling. Evangelista has also contributed to understanding electron mobility in metal-oxide semiconductors and strain effects in two-dimensional materials. These studies showcase his expertise in electronic structure and materials design for next-generation semiconductor technologies. -
Luis Fabiano de Assis, Ph.D.
Affiliate, Center for Human Rights and International Justice
BioDr. Luis Fabiano de Assis is a Brazilian Federal Prosecutor and data scientist whose work bridges law, public policy, and computational science. He is a Research Fellow at Stanford University's Center for Human Rights and International Justice, a founding member of the Stanford Human Trafficking Data Lab, and the founder of the SmartLab Initiative in Brazil - a public-interest platform that turns open data and knowledge-management tools into evidence for stronger labor rights and public policy.
For more than two decades, his work has centered on a single question: how can public institutions convert scattered administrative data into intelligence that actually changes outcomes on the ground? In his hands, the answer has taken the form of compliance strategies, enforcement plans, and frontline interventions targeting forced labor, human trafficking, child labor, occupational health risks, and workplace inequality.
He is internationally recognized as an expert on data technologies for decent work and human rights, and has advised United Nations University, the International Labour Organization (in Brazil, across Latin America, and in Geneva), and the World Bank (Washington/DC). As an expert member of the Alliance 8.7 Knowledge Platform Reference Group, hosted by United Nations University in New York, he contributes to global efforts aligned with SDG Target 8.7: ending modern slavery, forced labor, child labor, and human trafficking.
As Chief Research and Data Officer at the Brazilian Federal Labor Prosecution Office, Dr. Assis led the development of SmartLab in partnership with the ILO and a wide network of public and private collaborators. Since 2016, the platform has grown into a national public-good infrastructure for evidence-based labor policy, serving all 5,570 Brazilian municipalities through digital observatories that support policymaking, monitoring, evaluation, and enforcement. In its first decade, SmartLab drew more than two million page views from users in 95 countries, generated over 60,000 media references, and was cited in 854 academic works, including doctoral dissertations and master's theses. He also coordinates Monitora 8.7, a regional network supporting projects across Latin America and the Caribbean in cooperation with the ILO.
Dr. Assis has helped design and deploy human-centered AI tools for frontline anti-trafficking work, such as decision support tools with satellite imagery, machine learning, geospatial intelligence, administrative records, and user-centered design to prioritize trafficking tips and flag high-risk labor sites, helping task forces plan smarter, intervene earlier, and operate more effectively in remote, resource-constrained areas.
At the National School of Public Prosecutors in Brazil, he teaches law and public policy, with courses spanning AI, big data, evidence-based programs, behavioral science, accountability systems, data-driven investigations, collective litigation, and data protection law. His current research examines human trafficking, forced labor, social protection and health outcomes among trafficking survivors, supply-chain due diligence, AI-based risk prediction, vulnerability mapping, and decision-support systems.
From 2019 to 2022 he was a Visiting Scholar at Stanford University, working with the Center for Human Rights and International Justice, the Center for Health Policy, the King Center on Global Development, and the Graduate School of Business.
Education and Affiliations
LL.B., University of São Paulo, 2002
LL.M., University of São Paulo, 2008
Ph.D. in Law, University of São Paulo, 2011
Research Fellow, Stanford University, 2018–present
Visiting Scholar, Stanford University, 2019–2022
Founding Member, Stanford Human Trafficking Data Lab
Professor, National School of Public Prosecutors, Brazil
Federal Prosecutor, Brazilian Federal Labor Prosecution Office -
Aglaia Kaissa de Boer
Clinical Assistant Professor, Medicine - Pulmonary, Allergy & Critical Care Medicine
BioKaïssa de Boer, MD is a board certified pulmonologist who specializes in the care of patients with interstitial lung disease. She completed her Internal Medicine and Pulmonary training at the University of Ottawa, Ottawa, Canada where her initial interest in caring for patients with fibrotic lung disease first developed. Subsequently she completed a fellowship in Interstitial Lung Disease at the University of California, San Francisco under the direction of Dr. Harold Collard. Dr. de Boer has a special interest in patients with connective tissue disease associated lung disease and those with drug induced pneumonitis. In addition she is actively involved in the ILD training and program development of Stanford's Pulmonary Allergy and Critical Care Fellows.
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Walter De Brouwer
Adjunct Professor, Medicine - Primary Care and Population Health
BioWalter A. De Brouwer, Ph.D., is an Adjunct Professor at the Stanford School of Medicine. As a core faculty member at CERC DICE, he is the course director for “Innovation in Healthcare: from idea to incorporation,” which includes a bi-weekly presentation. He also serves on the advisory committee focused on the strategic direction for the program and is part of the leadership team developing the program curriculum and practicum. He is the founder of doc.ai, a Palo-Alto-based Federated Edge Learning company for the payers/pharma industry which merged in January 2020 with Sharecare Inc.
Professional Education
Bachelor’s degree in Philology (University of Ghent, Belgium)
Master’s degree in Formal Linguistics (University of Ghent, Belgium)
Post-graduate: Epistemology (University of Ghent, Belgium)
Ph.D. Computational Semiotics (Catholic University of Tilburg, the Netherlands). -
Korina De Bruyne
Clinical Assistant Professor, Medicine - Primary Care and Population Health
Current Research and Scholarly InterestsThe EMPOWER study (PI: Dr Beth Darnall) is looking at how to best support patients with chronic pain on long-term opioid therapy through a slow taper (maximal duration of 1 year). Patients are randomized to taper only versus taper plus community-based pain self-management group sessions versus taper plus psychologist-led cognitive behavioral therapy for pain group sessions. Along the way alternative measures to control pain are also explored. Enrollment is open until 10/2021.
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Mateus Gheorghe De Castro Ribeiro
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2022
Ph.D. Minor, Computer ScienceBioMateus Gheorghe de Castro Ribeiro is a PhD candidate in the Stanford Sustainable Systems Lab. He has worked on various topics at the intersection of engineering applications and artificial intelligence (AI). His main area of research focuses on AI applied to sustainable energy systems, specifically using data-driven methods to accelerate the electrification of bus fleets, ensure reliable operations with minimal costs, and achieve 24/7 carbon-free operations. Mateus obtained his bachelor's and master's degrees in mechanical engineering from the Federal University of Juiz de Fora and the Pontifical Catholic University of Rio de Janeiro, respectively. In 2022, he was awarded the CAPES/Fulbright Scholarship to pursue his PhD in the Department of Civil and Environmental Engineering at Stanford University.
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Sallie De Golia
Clinical Professor, Psychiatry and Behavioral Sciences
BioDr. De Golia specializes in the treatment of mood and anxiety disorders with an expertise in time-limited dynamic psychotherapy. She is Section Chief of the Assessment Clinics and Director of the Evaluation Clinic. Dr. De Golia is Director of Coaching and Senior Faculty Educational Consultant in Stanford's Department of Psychiatry and Behavioral Sciences. She is a Peer Teaching Coach and Fellow in the Stanford Teaching and Mentoring Academy, has taught regularly with the Stanford Center for Faculty Development, and is a Senior Fellow at Stanford's Center for Innovation in Global Health. She currently serves on the Executive Committee of the American Association of Directors of Psychiatry Residency Training.
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Greta de Groat
Metadata Librarian for Electronic and Visual Resources, Metadata Department
Current Role at StanfordI catalog digital materials (CD-ROMs, online monographs, websites, databases, video games, etc.) as well as videos, spoken word sound recordings, and general oddball stuff. If you can show it to me, i can catalog it! I also serve as a metadata consultant for digital projects. I have expertise in MARC, MODS, RDA, AACR2, Library of Congress Subject Headings, Library of Congress Classification, and an interest in the application of linked data to library metadata practices and infrastructure.
