Assistant Professor

 Optimization algorithms, machine learning and data science
scientific programming language, deep learning
School of Information Management and Engineering 609


Dr. Qi Deng received his Ph.D. in computer engineering from department of computer & information system and engineering, University of Florida, and Bachelor in computer science from Shanghai Jiao Tong University.

His research interests include convex/nonconvex optimization algorithms and their applications in machine learning and data science.

He received several awards, including Research and Assistant Scholarship at University of Florida, the Computer Science Best Undergraduate Paper Award at Shanghai Jiao Tong University, and several Academic Scholarship at the Shanghai Jiao Tong University and Hong Kong University of Science and Technology.

Selected papers

  1. Reducing Inventory Waste: Optimal Order-Up-to Level with Service Level Agreements in a Finite Horizon.
    Y. Tan, A. Paul, Q. Deng, L. Wei.
    in submission.

  2. Randomized block subgradient methods for convex nonsmooth and stochastic optimization, arXiv preprint.
    Q. Deng, G. Lan and A. Rangara jan.
    in submission.

  3. Stochastic Coordinate Descent for Nonsmooth Convex Optimization.
    Q. Deng, G. Lan and A. Rangara jan.
    In Optimization for Machine Learning Workshop, NIPS 2013.

  4. An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity.
    Biswas, D. Thompson, W. He, Q. Deng, C.M. Chen, H.W. Shen, R. Machira ju, and A. Rangara jan.
    PacicVis 2015, Hangzhou, China, 2015.

  5. Boosting Techniques for Physics-Based Vortex Detection.
    L. Zhang, Q. Deng. R. Machira ju, A. Rangara jan, D. Thompson, D.K. Wal- ters and H.W. Shen.
    Computer Graphics Forum, 33(1):282-293, 2014

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