Yu Du
Assistant Professor
Business Analytics

BUSB 5021

Yu Du’s research interest is in large scale data-driven mathematical optimization. The majority of her research focuses on developing nonlinear optimization algorithms for solving large-scale problems with applications in machine learning and data mining, specifically statistical convex and non-convex optimization problems.

Du has also been working on modeling and solving combinatorial optimization problems. Much of her efforts are concerned with new ways of modeling quadratic binary problems and with designing and testing new algorithms for solving these problems.

Education

PhD Operations Research, RUTCOR, Rutgers University

MS Quantitative Finance, Rutgers University

BS Economics, Central South University

Areas of expertise

Nonlinear Optimization, Combinatorial Optimization, Machine Learning and Business Analytics

Publications and presentations

F. Glover, G. Kochenberger, Y. Du, Quantum Bridge Analytics: A Tutorial on Formulating and Using QUBO Models, 4OR, Springer, vol. 17(4), pages 335-371, 2019.

Y. Du, X. Lin, A. Ruszczyński, A Selective Linearization Method for Multiblock Convex Optimization, SIAM Journal on Optimization 27 (2017), 1100-1117.

Y. Du, A. Ruszczyński, Rate of convergence of the bundle method, Journal of Optimization Theory and Applications 173 (2017), 908-922.

Glover, F., Kochenberger, G. and Ma, M., Du, Y., Quantum Bridge Analytics II: Combinatorial Chaining for Asset Exchange, 4OR, forthcoming.

Du, Y., Lin, X. and Ruszczynski, A., Statistical Learning via Selective Linearization (SLIN) Algorithm, European Journal of Operational Research, under review.

Pham, M., Lin, X., and Ruszczynski, A., Du, Y., An outer-inner linearization method for nonconvex and nondifferentiable composite regularization problems, Journal of Global Optimization, under review.

Du, Y., Glover, F.,Kochenberger, G., Lewis, M and Wang, H., Solving Clique Partitioning Problems: A Comparison of Models and Commercial Solvers, Discrete Optimization, under review.

He, J., Liu, M., Du, Y., Su, Y., How do Professors Teach? An Analysis of Student Comments on almost One Million Professors in RateMyProfessors.com, Journal of Educational Psychology, under review.

F. Glover, G. Kochenberger, Y. Du, Quantum Bridge Analytics: A Tutorial on Formulating and Using QUBO Models, INFORMS Annual, Seattle, 2019.

M. Pham, Y. Du, X. Lin, A. Ruszczynski, An outer–inner linearization method for nonconvex and nondifferentiable composite regularization problems, ICCOPT 2019, Berlin.

Y. Du, F. Glover, G. Kochenberger, H. Wang, An Improved Study on the Quadratic Knapsack Problem with Multiple Constraints, EURO 2019, Dublin, 2019.

Y. Du, F. Glover, G. Kochenberger, H. Wang, Solving Weighted Vertex Covering Problems: A Comparison of Models and Commercial Solvers., EURO 2019, Dublin, 2019.

F. Glover, G. Kochenberger, Y. Du, A Tutorial on Formulating and Using QUBO Models, contributed seminar at Applied mathematics, University of Colorado Boulder, May 2019.

Y. Du, X. Lin, A. Ruszczynski, Selective linearization for statistical learning, the 23rd International Symposium on Mathematical Programming, July 2018, Bordeaux, France.

Y. Du, X. Lin, A. Ruszczynski, Selective linearization method for statistical learning, contributed seminar at DIMACS, Rutgers University, June 2018, Piscataway, NJ.

https://www.youtube.com/watch?v=4vqyDu99YE4&list=PLKVCRT3MRed4pvskhC7ciyGa6xLD_Wz0g&index=21&t=517s

Awards

Excellence Fellowship in the Department of Operations Research, Rutgers University, 2012

Distinguished Graduates, 2010

National Scholarship of Ministry of Education of People’s Republic of China, 2008-2010

Affiliations

Princeton-Rutgers Graduate Student Cooperative Exchange Program, Princeton University

Reviewer: Annals of Operations ResearchFrontiers in Applied Mathematics and Statistics Section OptimizationDiscrete Applied MathematicsComputational Optimization and Applications, Journal of Global Optimization, Mathematical Programming.

Professional Memberships: The Mathematical Programming Society, Institute for Operations Research and the Management Sciences (INFORMS), and Society for Industrial and Applied Mathematics (SIAM), Operations research of China.