Stanford University
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Carlos Valencia
Undergraduate, Mechanical Engineering
BioBorn in Camarillo, California, Carlos Valencia learned early that challenges forge resilience. As the son of a hard-working immigrant family, he spent summers working in the avocado and lemon industry—a childhood that taught him the value of grit and the power of opportunity. Today, as a Mechanical Engineering student at Stanford University, he channels that determination into robotics, education advocacy, and uplifting communities.
Carlos loves learning about robotic technology and has worked on numerous projects related to the field. Carlos’s passion for engineering took root in high school. As the former president of the ACHS MESA (Mathematics, Engineering, Science, & Achievement) chapter, he mentored 45+ first-generation students, leading them to compete in national STEM competitions. In the summer of 2024, he worked with L5 Automation, a robotics company based in La Cañada, CA, in Olmos, Peru where he helped develop harvesting platforms for one of the largest agriculture producers in Peru.
Beyond engineering, believes in the power of storytelling to inspire action. His TEDx talk, “Avocados Rot” drew from his upbringing to challenge audiences to seize fleeting chances—a message that resonated globally. Recognized as Camarillo Youth of the Year (2023) and awarded the Bronze Volunteer Award by the American Red Cross, he balances innovation with service, whether rebuilding communities after disasters or leading robotics teams.
Carlos’s mission is to democratize STEM access. Carlos envisions a world where education erases barriers. He aims to pioneer low-cost robotic solutions for agriculture and healthcare while expanding mentorship networks for first-gen students. When not engineering or volunteering, he unwinds by hiking, playing pickup soccer, or tinkering with 3D printers. -
Mauricio Valencia
Director Corporate Relations, School of Engineering - External Relations
Current Role at StanfordDirector of Corporate Relations, School of Engineering
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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. -
Gregory Valiant
Associate Professor of Computer Science
On Leave from 10/01/2025 To 06/30/2026Current Research and Scholarly InterestsMy primary research interests lie at the intersection of algorithms, learning, applied probability, and statistics. I am particularly interested in understanding the algorithmic and information theoretic possibilities and limitations for many fundamental information extraction tasks that underly real-world machine learning and data-centric applications.
