Eight Columbia Engineering Professors Win NSF CAREER Awards

Newswise — Eight professors from Columbia Engineering are among this year’s recipients of the National Science Foundation’s (NSF) Early Career Development (CAREER) awards, one of the most prestigious recognitions for junior researchers. Their areas of expertise will contribute to gains in personalized cancer treatment, the analysis of cellular processes, distributed control in large-scale systems, quantum information theory, understanding multiphase flows, as well as cloud computing and storage operations.

James Anderson, assistant professor of electrical engineering

James Anderson, assistant professor of electrical engineering, received the award for his work on developing randomized algorithms for the analysis and control of large-scale cyber-physical systems, such as connected autonomous cars, smart power grids, and even the internet. With the goal of finding optimal solutions as close to real-time as possible, Anderson will use randomization to focus on the formulation of “approximate” solutions that provide comparable levels of performance and robustness to high-precision solutions and be used with large-scale systems. Results will enable the widespread adoption of distributed control in the aerospace, robotics, automotive, and energy industries. Anderson is also a member of the Data Science Institute.

Elham Azizi, Herbert and Florence Irving Assistant Professor of Cancer Data Research in the Irving Institute for Cancer Dynamics and department of biomedical engineering

Elham Azizi, Herbert and Florence Irving Assistant Professor of Cancer Data Research in the Irving Institute for Cancer Dynamics and department of biomedical engineering, received a grant for her project “Integrative modeling of intercellular interactions in the tumor microenvironment.” Her research focuses on studying interactions between cells inside and around breast cancer tumors to better understand how aggressive tumors evade the body’s immune defenses in the hopes of informing approaches to improve anti-tumor immunity. Azizi is also an affiliated faculty member of computer science, and a member of the Data Science Institute and the Herbert Irving Comprehensive Cancer Center.

Chris Boyce, assistant professor of chemical engineering

Chris Boyce, ​​assistant professor of chemical engineering, is working to advance understanding of the physics of multiphase flows to optimize industrial device performance and generate exciting new technologies in energy, health, and the environment. He is engineering structured bubbling patterns in multiphase flows and developing magnetic resonance imaging (MRI) techniques to characterize these systems. Ubiquitous in both nature and industry, multiphase flows, in which bubbles rise through fluids that contain solid particles, have been difficult to study due to chaotic behavior of the bubbles. The grant will support Boyce’s work to use MRI as a way to characterize the interior of flow systems in 3D. Through his NSF project, Boyce plans to use visualizations of multiphase flows to inspire middle- and high-school students from Harlem and the Bronx to pursue STEM studies. The project includes the launch of a Visualization of Flow symposium for students in Boyce’s lab, as well as young professionals from diverse backgrounds.

Asaf Cidon, assistant professor of electrical engineering and computer science

Asaf Cidon, assistant professor of electrical engineering and of computer science, received the award for his proposal, “In-Kernel Execution of Storage Functions.” Cidon’s research will build a new software framework, XRP, that will speed up cloud computing and improve storage operations. XRP would enable cloud applications using fast storage devices to offload commonly used storage functions, such as index traversals and aggregations, to the operating system. By doing so, XRP allows applications to eliminate the significant overhead of traversing all the operating system layers and going back and forth between the application and the operating system, each time the storage device is accessed. Cidon expects XRP to more than halve the amount of computation and energy needed to conduct common storage operations on fast storage devices.

David Knowles, assistant professor of computer science

David Knowles, assistant professor of computer science, will use statistical machine learning to develop a new conceptual framework to transform how the cellular process of alternative splicing (AS) is analyzed. Findings will help researchers understand the role of AS in organismal development, disease, and environmental response at unprecedented resolution. As part of his research, he will expand the capabilities of LeafCutter, a method he co-developed to quantify RNA splicing from short-read RNA-seq data and test for differences between conditions. Knowles is also a member of the Data Science Institute, an interdisciplinary appointee in Systems Biology, and a Core Faculty Member at the New York Genome Center (NYGC).

José L. McFaline-Figueroa, assistant professor of biomedical engineering

José L. McFaline-Figueroa, assistant professor of biomedical engineering, won support for his project, “Defining kinase-driven cellular response networks using single-cell genomics.” He studies how cancer cells respond after exposure to anti-cancer therapy, and how that response depends on the genetic background of individual cancer cells. This research addresses the need to study tumors at the resolution of single cells within heterogeneous cell groups and will aid in the development of more powerful treatment combinations to treat disease, especially cancer. McFaline-Figueroa is also an associate member of the Herbert and Florence Irving Institute for Cancer Dynamics and a member of the Herbert Irving Comprehensive Cancer Center.

Shuran Song, assistant professor of computer science

Shuran Song, assistant professor of computer science, received the award to create a framework--machine learning algorithms--that will enable robots to explore their environment and decide how to accomplish a task based on the situation they face. Building upon her previous research in 3D-scene understanding and self-supervised learning frameworks, this new project will focus on creating a framework she calls “active scene understanding,” where the agent leverages its ability to interact with the world in order to better understand what it sees --from discovering new objects to deciphering their physical dynamics, and exploiting the learned knowledge to accomplish the task on hand. Song is hoping to build a unified framework that can handle a diverse set of complex environments without needing to be deliberately re-engineered for each new task or scenario. Successful algorithms for inferring scene representations through active interactions could change working processes for a number of applications, including field, space, or home robots.

Henry Yuen, assistant professor of computer science

Henry Yuen, assistant professor of computer science, will use his award to advance and connect multiple facets of quantum information theory, theoretical computer science, and pure mathematics. He is developing theoretical foundations that explain the difference between classical computers and emerging quantum computers. The award will support Yuen’s development of verification protocols to help researchers verify that quantum computers are behaving as intended and advance quantum entanglement theory to help solve enormously complex problems. The award also supports Yuen’s outreach efforts which include the production of Nonlocal, a quantum-themed podcast for a quantum-curious public audience.

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