Stanford University
Showing 431-440 of 509 Results
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Madeleine Udell
Assistant Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsProfessor Udell develops new techniques to accelerate and automate data science,
with a focus on large-scale optimization and on data preprocessing,
and with applications in medical informatics, engineering system design, and automated machine learning. -
Johan Ugander
Associate Professor of Management Science and Engineering
BioProfessor Ugander's research develops algorithmic and statistical frameworks for analyzing social networks, social systems, and other large-scale data-rich contexts. He is particularly interested in the challenges of causal inference and experimentation in these complex domains. His work commonly falls at the intersections of graph theory, machine learning, statistics, optimization, and algorithm design.
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Melissa Valentine
Associate Professor of Management Science and Engineering
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.