Viswanath Nagarajan Awarded NSF Grant
The awarded project focuses on developing advanced algorithms for stochastic optimization, tackling a fundamental challenge in algorithm design: uncertainty in input parameters.
Viswanath Nagarajan, an associate professor at the University of Michigan, has been awarded a grant from the National Science Foundation (NSF), totaling $484k. The grant will support Nagarajan’s project titled “AF: Small: Adaptivity and Learning in Stochastic Combinatorial Optimization,” set to commence on October 1, 2024, and conclude in 2027.
The project: Creating adaptable algorithms
The awarded project focuses on developing advanced algorithms for stochastic optimization, tackling a fundamental challenge in algorithm design: uncertainty in input parameters. Unlike classical algorithms that assume precise knowledge of input data, stochastic optimization treats these inputs as random variables, making it highly relevant for modern applications ranging from healthcare to robotics and cloud computing. This ambitious endeavor aims to bridge gaps in current algorithmic techniques by providing robust solutions for complex, real-world problems influenced by data uncertainty.
“Data uncertainty is ubiquitous in several algorithmic applications such as healthcare, retail, transportation and robotics,” said Nagarajan. “This project will design algorithms for some fundamental stochastic problems arising in these areas, with a focus on parallelizable policies that lead to significant time savings.”
Nagarajan’s pioneering work could vastly improve the efficiency and applicability of algorithms in various sectors, providing practical and scalable solutions to handle uncertainty in data-driven environments. Examples of real-world application could include robot path planning in uncertain environments, sequencing medical tests to diagnose an unknown disease or scheduling tasks of uncertain durations in cloud computing.
The NSF’s recognition through this significant grant underscores the importance and potential impact of Nagarajan’s research contributions in the rapidly evolving landscape of algorithm design. Through this grant he hopes to achieve his goal of designing new algorithmic and analysis techniques for stochastic versions of fundamental combinatorial optimization problems, such as knapsack, set cover, submodular cover and influence maximization.
About Viswanath Nagarajan
Viswanath Nagarajan has been a faculty member at the University of Michigan since 2014. Throughout his career, Nagarajan has received multiple NSF grants, including the prestigious NSF CAREER Award. He has served on the program committee or editorial board of several top conferences and journals. These include the Society of Industrial and Applied Mathematics (SIAM) Symposium on Discrete Algorithms and the Association for Computing Machinery (ACM) Transactions on Algorithms and Operations Research.
Nagarajan’s primary research focuses on the design and analysis of algorithms for discrete optimization problems. His expertise lies in models that incorporate uncertainty, such as stochastic and online optimization. His research interests span a variety of application areas, including scheduling, vehicle routing, facility location and machine learning.
He is currently a member of both the Institute for Operations Research and the Management Sciences (INFORMS) and the ACM. Before coming to U-M IOE he gained his BTech at the Indian Institute of Technology – Bombay as well as an MS and PhD at Carnegie Mellon University.