Curriculum Vitae

PhD in Mathematics and Statistics, School of Mathematics and Statistics, University of New South Wales, Sydney, Australia
anant.mathur@unsw.edu.au

Download CV (PDF)

Career

• Principal Research Engineer — Solaris AI (University of Queensland start-up)
  Current

Education

• PhD in Statistics — UNSW Sydney
  Focus area: Computational Statistics and Operations Research
  Dissertation: Efficient Algorithms for Sparse Statistical Learning
  Supervisors: Dr Zdravko Botev, Dr Sarat Moka
  09/20 – 06/25
• Bachelor of Science (Honours), Statistics — UNSW Sydney
  01/15 – 12/19

Research areas

Awards & honours

• PhD thesis evaluated in the top 10% by both external examiners (UCLA, NCSU) and nominated for the UNSW Dean's Award for Outstanding PhD Theses (awaiting outcome)
• Outstanding Statistics Talk, UNSW School of Mathematics and Statistics, Postgraduate Conference (2023)
• UNSW Nominee for JB Douglas Award (2023)

Academic service

Reviewer for journals

• Pattern Recognition

Reviewer for conferences

• Conference on Neural Information Processing Systems (NeurIPS)

Organizer/chair of technical sessions

• Probability and Optimization for Statistical Learning, INFORMS International Meeting, Singapore
  07/25

Honours thesis research guidance

• Ruiqi Dao (Primary advisor: Sarat Moka)
  01/25 – 10/25
• Seungjoo Lee (Primary advisor: Sarat Moka)
  01/24 – 10/24

Research publications & preprints

Manuscripts under peer-review

• A. Mathur, B. Liquet, S. Muller, S. Moka — Parsimonious Subset Selection for Generalized Linear Models with Biomedical Applications. [arXiv]
• A. Mathur, S. Moka, Z. Botev — A Fast MM Algorithm for Group Lasso. [PDF]

In peer-reviewed journals

• 2022 A. Mathur, S. Moka, Z. Botev — Coordinate Descent for Variance-Component Models. Algorithms, 15 (10): 354. [DOI]

In peer-reviewed conference proceedings

• 2024 A. Mathur, S. Moka, B. Liquet, Z. Botev — Group COMBSS: Group Selection via Continuous Optimisation. Proceedings of the 2024 Winter Simulation Conference, IEEE Press, pp. 3217–3228. [DOI]
• 2023 A. Mathur, S. Moka, Z. Botev — Feature Selection in Generalised Linear Models via the Lasso: To Scale or Not to Scale? 15th OPT-ML Workshop, NeurIPS 2023. [PDF]
• 2023 A. Mathur, S. Moka, Z. Botev — Column Subset Selection and Nyström Approximation via Continuous Optimisation. Proceedings of the 2023 Winter Simulation Conference, IEEE Press, pp. 3601–3612. [PDF]
• 2021 A. Mathur, S. Moka, Z. Botev — Variance Reduction for Matrix Computations with Applications to Gaussian Processes. VALUETOOLS 2021, LNCS 13116, pp. 275–290. [PDF]

Research talks

Invited talks in specialized workshops/conferences

• SSA NSW Branch Annual Event · JB Douglas Award
  Dec 2023

Seminar presentations

• Macquarie University, School of Mathematical and Physical Sciences
  09/24
• UNSW Sydney, School of Mathematics and Statistics, Statistics Seminar
  09/24

Contributed talks in major conferences

• INFORMS International Meeting, Singapore
  07/25
• 2023 Winter Simulation Conference, San Antonio
  12/23
• 25th International Congress on Modelling and Simulation (MODSIM 2023), Darwin
  07/23
• Australian Mathematical Society Annual Meeting 2022, Sydney
  12/22
• VALUETOOLS 2021 (Online)
  10/21