Suggestions
Madeleine Udell
Optimization and Machine Learning
Professional Background
Madeleine Udell is an esteemed Assistant Professor of Operations Research and Information Engineering at Cornell University, where she also serves as the Richard and Sybil Smith Sesquicentennial Fellow. With a robust focus on optimization and machine learning, her research addresses large-scale data analysis and control, impacting multiple fields including marketing, demographic modeling, medical informatics, and engineering system design. Throughout her impressive career, Dr. Udell has stood out for her innovative work on generalized low-rank models (GLRMs), which take principal components analysis (PCA) to new heights. This groundbreaking research enables the embedding of tabular datasets with varied types—such as numerical, Boolean, categorical, and ordinal—into a lower-dimensional space. Such models provide an exceptional framework for compressing, denoising, and imputing missing entries in data sets.
In addition to her teaching and research duties, Dr. Udell has made significant contributions to the field of optimization through her development of open source libraries. One of her standout accomplishments is Convex.jl, recognized as one of the ten leading tools in the emerging Julia programming language for technical computing. Her involvement with the JuliaOpt organization underscores her commitment to advancing high-quality optimization software. The blend of her academic pursuits and software contributions positions her as an influential player in the operations research community.
Education and Achievements
Dr. Udell's academic journey is marked by a series of prestigious accolades and milestones. She completed her PhD in Computational and Mathematical Engineering at Stanford University in 2015, under the mentorship of notable professor Stephen Boyd. During her time at Stanford, she was the proud recipient of several fellowships, including the National Science Foundation (NSF) Graduate Fellowship, the Gabilan Graduate Fellowship, and the Gerald J. Lieberman Fellowship. Additionally, her leadership skills were recognized when she was appointed as the doctoral student member of Stanford's School of Engineering Future Committee. There, she played a pivotal role in developing a roadmap that would guide the future of engineering at Stanford for the upcoming decades.
Her academic roots run deep, having graduated summa cum laude with a B.S. degree in Mathematics and Physics from Yale University. At Yale, she earned honors in both disciplines, showcasing her exceptional abilities and dedication to her studies.
Career Highlights
Dr. Udell's career trajectory exemplifies a rich blend of academic and industry experiences. Before her current role at Cornell University, she was an Assistant Professor of Management Science and Engineering at Stanford University, where she further honed her expertise in optimization and data analysis. Her industry experience includes notable positions such as a Senior Research Scientist at Qadium, where she immersed herself in developing innovative solutions to complex data challenges, and a Lead Data Scientist at DARPA, consulting through Data Tactics. Here, she applied her data analysis skills to national security problems.
Her experience extends to consulting roles, including as an Optimization Consultant at Computational Consulting (C2), and her analytical prowess was tested during her time in digital analytics for Obama for America. This wide-ranging experience across sectors underlines Dr. Udell's versatility and capability in applying her academic knowledge to real-world applications.
Dr. Udell also served as a Research Scientist at Apixio, where she contributed to health informatics, aligning with her research interests in medical informatics. Her early career included invaluable internship experiences as a Commodities Strategies Summer Analyst and a Summer Analyst in Risk Management at Goldman Sachs, providing her with a strong foundation in data-driven decision-making and financial modeling.
Moreover, Dr. Udell shared her passion for learning and mathematics through her role as a Math and Physics Tutor at Yale University, where she inspired the next generation of scientists and engineers.
Notable Contributions
Dr. Udell's contributions to the field extend beyond her research and academic positions. Her dedication to creating open-source tools, such as Convex.jl, signifies her commitment to making optimization tools accessible to practitioners and researchers alike. Her leadership in the JuliaOpt organization facilitates the spread of high-quality optimization software, further establishing her reputation as a thought leader in this domain.
By exploring optimization frameworks like GLRMs, she has not only advanced theoretical knowledge but also made practical impacts across industries reliant on data analysis. Dr. Udell's multifaceted approach showcases her ability to bridge the gap between theory and application, making her an invaluable asset in both academic and industry circles.
