Nimita Shinde
Bio
I am a Postdoctoral Research Associate at the Department of Radiation Oncology at University of Kansas Medical Center. I currently work on optimization problems arising in radiation therapy for cancer treatment. Prior to this, I was a Postdoctoral Research Associate in the Department of Industrial and Systems Engineering at Lehigh University from June 2023-May 2024. I was a Postdoctoral Fellow at ICERM, Brown University from September 2022-May 2023. I completed my Ph.D. in 2022 jointly from Indian Institute of Technology Bombay and Monash University under the supervision of Prof. Vishnu Narayanan and Dr. James Saunderson. My thesis was titled 'Memory-efficient structured convex optimization'. Here is my resume.
Email: nimitashinde25@gmail.com
Research Interests
My interests lie in the practical applications of optimization models and solution methodologies. Currently, I am working on various optimization problems that arise in radiation therapy for cancer treatment specifically on radiation dose planning.
I am also broadly interested in approximate algorithms for large-scale convex optimization, and integer and combinatorial optimization problems proving the tightness of semidefinite relaxations. I have also worked on developing approximate first-order algorithms for composite self-concordant optimization problems and on developing convex relaxation of Maximum Entropy Sampling Problem (MESP). I have also worked on manifold clustering problems, with a focus on proving theoretical bounds on the clustering accuracy of existing methods.
Publications and Preprints
Shinde, N., Li, W., Chen, R.C. and Gao, H., 2025. Optimizing normal tissue sparing via spatiotemporal optimization under equivalent tumor-radical efficacy. arXiv preprint arXiv:2502.16333. [pdf]
Shinde, N., Zhang, W., Lin, Y. and Gao, H., 2025. Minibeam-pLATTICE: A novel proton LATTICE modality using minibeams. arXiv preprint arXiv:2502.16332. [pdf]
Shinde, N., Zhang, W., Lin, Y. and Gao, H., 2025. A mixed integer programming approach to minibeam aperture optimization for multi-collimator proton minibeam radiotherapy. arXiv preprint arXiv:2502.16326. [pdf]
Shinde, N., Zhu, Y., Wang, W., Li, W., Lin, Y., Gan, G.N., Lominska, C., Rotondo, R., Chen, R.C. and Gao, H., 2024. Multi-IMPT: a biologically equivalent approach to proton ARC therapy. arXiv preprint arXiv:2411.17578. [pdf]
Shinde, N., Ding, T., Robinson, D. and Vidal, R., Geometric Analysis of Nonlinear Manifold Clustering. In The Thirty-eighth Annual Conference on Neural Information Processing Systems. [pdf]
Shinde, N., Narayanan, V. and Saunderson, J., 2023. An Inexact Frank-Wolfe Algorithm for Composite Convex Optimization Involving a Self-Concordant Function. arXiv preprint arXiv:2310.14482. [pdf]
Shinde, N., Narayanan, V. and Saunderson, J., 2021. Memory-efficient approximation algorithms for max-k-cut and correlation clustering. Advances in Neural Information Processing Systems, 34, pp.8269-8281. [pdf]
Shinde, N., Narayanan, V. and Saunderson, J., 2021. Memory-efficient structured convex optimization via extreme point sampling. SIAM Journal on Mathematics of Data Science, 3(3), pp.787-814. [pdf]
Posters, Talks, and Workshops
(Poster) Geometric Analysis of Nonlinear Manifold Clustering, Institute for Data, Intelligent Systems, and Computation, April 2024.
(Talk) Inexact Frank-Wolfe Algorithm for Optimizing Self-Concordant Barrier Functions, Department Seminar, Department of Management Sciences, IIT Kanpur, February 2024.
(Talk) Memory-Efficient Approximation Algorithm for Max-Cut, Max-K-Cut and Correlation Clustering, MOPTA, August 2023
(Talk) Memory-Efficient Approximation Algorithm for Max-Cut, Max-K-Cut and Correlation Clustering, SIAM Conference on Optimization, June 2023.
(Talk) Memory-efficient approximation algorithms for Max-Cut and Max-k-Cut, Semester Program on Discrete Optimization: Mathematics, Algorithms, and Computation, ICERM, 2023.
(Talk) Memory-efficient approximation techniques, Semester Program on Harmonic Analysis and Convexity, ICERM 2022.
(3-Minute Thesis Talk) ‘Memory-efficient algorithms for structured convex optimization problems.’, Monash University, 2021.
(Poster) Nimita Shinde, Vishnu Narayanan, and James Saunderson. Memory-efficient approximation algorithms for Max-Cut and Max-k-Cut, Current Themes of Discrete Optimization: Boot-camp for early-career researchers, ICERM, 2023.
(Poster) Nimita Shinde, Vishnu Narayanan, and James Saunderson. Memory-efficient approximation algorithms for Max-Cut and Max-k-Cut, IPCO, 2022.
(Workshop) Optimal Transport in Data Science, ICERM, May 8 - 12, 2023.
(Workshop) Trends in Computational Discrete Optimization, ICERM, Apr 24 - 28, 2023.
(Workshop) Combinatorics and Optimization, ICERM, Mar 27 - 31, 2023.
(Workshop) Linear and Non-Linear Mixed Integer Optimization, ICERM, Feb 27 - Mar 3, 2023.
(Workshop) Current Themes of Discrete Optimization: Boot-camp for early-career researchers, ICERM, Jan 30 - Feb 3, 2023.
Teaching
ISE 402: Applied Models in Operations Research, Spring 2024 at Lehigh University (Department of Industrial and Systems Engineering)
Awards
Recipient of IEOR Alumnus Endowment: Excellence in Doctoral Dissertation Award for 2021-23 at IIT Bombay
Institute Silver Medal (M. Tech., 2016), IIT Bombay