Stanford University
Showing 1-10 of 10 Results
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Melissa Valentine
Associate Professor of Management Science and Engineering and Senior Fellow at the Stanford Institute for Human-Centered AI
Current Research and Scholarly InterestsAs societies develop and adopt new technologies, they fundamentally change how work is organized. The intertwined relationship between technology and organizing has played out time and again, and scholars predict that new internet and data analytic technologies will spur disruptive transformations to work and organizing.
These changes are already well-documented in the construction of new market arrangements by companies such as Upwork and TaskRabbit, which defined new categories of “gig workers.” Yet less is known about how internet and data analytic technologies are transforming the design of large, complex organizations, which confront and solve much different coordination problems than gig platform companies.
Questions related to the structuring of work in bureaucratic organizations have been explored for over a century in the industrial engineering and organizational design fields. Some of these concepts are now so commonplace as to be taken for granted. Yet there was a time when researchers, workers, managers, and policymakers defined and constructed concepts including jobs, careers, teams, managers, or functions.
My research program argues that some of these fundamental concepts need to be revisited in light of advances in internet and data analytic technologies, which are changing how work is divided and integrated in organizations and broader societies. I study how our prior notions of jobs, teams, departments, and bureaucracy itself are evolving in the age of crowdsourcing, algorithms, and increasing technical specialization. In particular, my research is untangling how data analytic technologies and hyper-specialization shape the division and integration of labor in complex, collaborative production efforts characteristic of organizations. -
Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering and, by courtesy, of Computer Science
BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department's Graduate Teaching Award, and the Lanchester Prize. He was the plenary speaker at the 2019 Allerton Conference on Communications, Control, and Computing. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen. -
King (Vivek) Vanga
Masters Student in Management Science and Engineering, admitted Autumn 2020
BioKing Vanga is a Stanford-trained AI researcher and the founder of CivicSentinel AI, a public-interest initiative focused on developing ethical tools to detect and neutralize harmful uses of artificial intelligence.
His work spans adversarial AI, misinformation detection, and algorithmic accountability. King previously founded AEGIS (Applied Ethics, Governance, and Institutional Systems) and has worked at the intersection of civic institutions and machine learning.
His research is rooted in Stanford’s interdisciplinary approach to ethical technology and has informed open-source frameworks and public-interest platforms.
King’s academic background includes computer science (AI Track) and Management Science & Engineering, with published research in both graph theory and social systems.
Education & Affiliation
King holds a B.S. in Computer Science (Artificial Intelligence track) from Stanford University and is currently pursuing an M.S. in Management Science & Engineering (Technology and Engineering Management) at Stanford. His training in computer science offers foundational technical fluency, while his advanced work in MS&E underscores his commitment to leadership and the managerial side of technology.
Professional & Research Focus
As Founder and Chief Executive Officer of CivicSentinel AI, King leads the development of transparent, ethical platforms for early threat detection, misinformation triage, and algorithmic accountability—tools designed to empower civic institutions, journalists, and technologists before AI-driven risks escalate.
His research contributions include peer-reviewed studies on AI safety, alignment, adversarial risk modelling, computational approaches to misinformation mitigation, and decision-making under uncertainty. In particular, he has produced quantitative models of AI existential risk and frameworks for algorithmic governance.
King’s career blends deep technical expertise with leadership in technology management, positioning him to bridge innovation and responsible deployment.
Community Service & Civic Engagement
Beyond his academic and professional work, King has a sustained record of community-oriented efforts. He co-founded the nonprofit Kare Packages, which distributed over 1,000 COVID-19 protection kits and 1,500 face masks to unhoused populations across California during the pandemic.
He also co-founded the student-led initiative AEGIS at Stanford, which advanced algorithmic ethics, civic tech oversight, and institutional resilience. His public-facing mission emphasizes that smarter AI must be paired with accountability—and that technology should defend, rather than undermine, public trust.
Key Projects & Impact
• CivicSentinel AI: Founder & CEO, leading a platform for AI-based misinformation detection and threat analysis with transparency and civic purpose.
• Engineering risk analysis of AI existential risk: Peer-reviewed study at Stanford MS&E connecting decision-making under uncertainty to AI governance models.
• Kare Packages: Co-founder of a nonprofit delivering COVID-19 protection kits and masks to unhoused communities across California.
• AEGIS (Applied Ethics, Governance, and Institutional Systems): Co-founded while at Stanford; a student initiative advancing ethics in civic technology and institutional oversight.
Awards & Recognition
• Commended for community service during COVID-19 relief efforts.
• Selected for the Stanford MS&E Leadership Fellowship, recognizing leadership and technical-managerial excellence.
• Published peer-reviewed research cited in academic and policy discussions on AI risk, governance and misinformation. -
Luca Vendraminelli
Postdoctoral Scholar, Management Science and Engineering
BioLuca Vendraminelli is a Postdoctoral Researcher at the Digital Economy Lab and the Stanford Institute for Human-Centered AI (HAI) at Stanford University. He is also a research affiliate at the Center for Work, Technology & Organization (WTO) in the Department of Management Science and Engineering at Stanford University, and at the Data Science and AI Operations Lab in the Digital Data Design Institute at Harvard.
Within the context of large organizations, his research examines how AI transforms job tasks, expertise, and, more broadly, organizational design and the division of labor. He also investigates investments into AI and why AI projects fail, focusing on how the interplay between internal organizational factors and vendor strategies may be roadblocks at various stages of the technology innovation lifecycle.
His work has appeared in scientific journals such as the Journal of Product Innovation Management. He was awarded the 2020 Albert Page Award for Outstanding Professional Contribution.
