Home Dr.  Mostafa Rezapour

Dr.  Mostafa Rezapour

Teacher Scholar Postdoctoral Fellow

Dr. Rezapour’s

  • Office: 348 Manchester
  • Home Page:
  • Email: rezapom 'at' wfu.edu
  • Ph.D. in Applied Mathematics (optimization and machine learning), Department of Mathematics and Statistics, Washington State University, Jun 2020 Adviser: Dr. Thomas Asaki;    Thesis: Trust-region methods for unconstrained optimization problems
  • M.S. in Statistics (Data Analysis), Department of Mathematics and Statistics, Washington State University, Spring 2019 Adviser: Dr. Nairanjana Dasgupta;  Project: Application of Machine Learning on a diagnostic Breast Cancer data with a modified Gradient Descent
  • M.S. in Applied Mathematics (Optimization), Department of Mathematics and Statistics, Sharif University of technology Adviser: Dr. Nezam Mahdavi-Amiri Thesis: Implementation of a Retrospective Trust-Region Method for Unconstrained Optimization
Professional Website

Recent (2021):
  • A New Multipoint Secant Method with a Dense Initial Matrix (with Dr. Oleg Burdakov and Dr. Jennifer Erway)- in progress
2019-2020:
  • Rezapour, Mostafa. Trust-Region Methods for Unconstrained Optimization Problems. Diss. Washington State University, 2020.
  •  Rezapour, Mostafa, and Thomas Asaki. "Neural-trust-region algorithm for unconstrained optimization." arXiv preprint arXiv:2004.09058 (2020).
  •  Rezapour, Mostafa, and Thomas J. Asaki. "Adaptive trust-region algorithms for unconstrained optimization." Optimization Methods and Software (2019): 1-23.
  •  Rezapour, Mostafa, Adebowale Sijuwade, and Thomas Asaki. "A sigmoidal fractional derivative for regularization." AIMS MATHEMATICS 5.4 (2020): 3284-3297.
  •  Sijuwade, Adebowale and Rezapour, Mostafa. "A fractional derivative with a new smooth kernel." arXiv preprint arXiv:2001.01610 (2020).
  • Ramezani, I., Niaki, M. K., Dehghani, M., Rezapour, M. (2020). Stability analysis of feature ranking techniques in the presence of noise: a comparative study. International Journal of Business Intelligence and Data Mining, 17(4), 413-427.
Spring 2021: Fall 2020: Previous (2017-2020, instructor):
  • Advanced Linear Algebra for PhD students (PhD Qualifying Exam)
  • Principles of Optimization (Linear, Integer and Nonlinear)
  • Differential Equations
  • Introductory Statistics for Engineers
  •  Calculus for Business and Economics
  •  Calculus III
  • Calculus II (course mentor)
  • Calculus I
Python, Matlab, PHP, Java, R (exposure), SAS (exposure)
Awards 2019-2020
  • The Craft Family Scholarship, Jun 2020, Washington State University, the College of Arts and Sciences (CAS). This funding is offered in recognition of the outstanding achievements and is intended to support the academic success. Arnold M. and Atsuko (Onda) Craft established this scholarship to support hard working students in a variety of fields.
  • Sidney G. and Evelyn Hacker Graduate Research Fellowship (2019-2020, WSU). The scholarship recognizes excellence in graduate research.
  • American Mathematical Society Travel Award (2020). To attend Joint Mathematics Meeting, Jan 15-18, 2020, Denver, Colorado, US.
  •  SIAM Travel Award (2019). To attend the "Applied Mathematics: The Next 50 Years".
  •  SIAM Travel Award (2020). To attend SIAM Conference on Mathematics of Data Science (MDS20) Hilton Cincinnati Netherland Plaza, Cincinnati, Ohio, U.S.
  •  GPSA Travel Award (2019). To attend Informs Annual Meeting, October 2019.
  •  GPSA Travel Award (2020). To attend Joint Mathematics Meeting, Jan 15-18, 2020, Denver, Colorado, US.
Exams
  • The top score of GQE (PhD Qualifying Examination) - Department of Mathematics and Statistics, WSU (94/100, 2017)
  • Ranking number 8 among more than 12000 of students participating in the national university entrance examination for master's degree in Applied Mathematics.
  • Ranking number 9 among more than 12000 of students participating in the national university entrance examination for master's degree in Pure Mathematics.
 Recent
  • How to use deep learning in our research (part 2), April 30, 2021, Python Working Group, WSU, Washington, U.S.
  • Adaptive trust-region algorithms for unconstrained nonlinear optimization, Department of Mathematics and Statistics Colloquium, April 29, 2021, Wake Forest University, North Carolina, U.S.
  • How to use deep learning in our research (part 1), April 23, 2021, Python Working Group, WSU, Washington, U.S.
  • A new approach in derivative-free optimization (part II), Analysis, PDEs, differential geometry and applications seminar, April 15, 2021, Department of Mathematics and Statistics, Wake Forest University, North Carolina, U.S.
  • A new approach in derivative-free optimization (part I), Analysis, PDEs, differential geometry and applications seminar, April 8, 2021, Department of Mathematics and Statistics, Wake Forest University, North Carolina, U.S.
  • Python for Machine Learning, Deep Learning, Differential Equations, and Optimization, Python Working Group, WSU, Dec 4, 2020, Washington, U.S.
  • Trust-region Methods for Unconstrained Optimization Problems, WFU MST 683 Seminar, Nov 11, 2020, Wake Forest University, Winston Salem, North Carolina, U.S.
  • Neural Trust-Region Methods for Unconstrained Nonlinear Optimization, SIAM Conference on Mathematics of Data Science (MDS20), May 2020, Cincinnati, Ohio, U.S.
  • Neural partial differential equation solver with fractional gradient descent, JMM (American Mathematical Society contributed paper session), Jan 2020, Denver, Colorado, U.S.
  • Solving PDEs with Neural Networks, JMM (Mathematical Association of America contributed paper session), Jan 2020, Denver, Colorado, U.S.
  • Two Modified Trust Region Algorithms for Unconstrained Optimization, Informs Annual Meeting, October 2019, Seattle, WA, U.S.
  • Application of a Flexible Gradient Descent to Machine Learning, Informs Annual Meeting, October 2019, Seattle, WA, U.S.
  1. Lucas Hansen (Machine Learning and Deep Learning)
  2. Harry Zhou (Machine Learning and Deep Learning)
Soccer, computer programming, travel, hiking and running

 

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