My research spans optimization algorithms, deep learning for biomedical imaging, and probabilistic modeling for complex systems. I focus on building scalable, interpretable, and high-impact computational tools that drive discoveries in both academia and industry.
Deep Learning for Medical Imaging
Developed CNN-based models for real-time tissue segmentation
Built image-based tracking systems to study cell growth and division
Adaptive Optimization Algorithms
Created clustering-based adaptive Differential Evolution variants
Applied them to large-scale problems in water systems, energy, and finance
Cross-Domain Modeling
Integrated ML, statistics, and optimization for real-world applications
Collaborated across biology, engineering, and economics domains
Selected Publications
Optimization & Algorithms
Bilal, Millie Pant, Hira Zaheer, Laura Garcia-Hernandez, Ajith Abraham, "Differential Evolution: A review of more than two decades of research", in Engineering Applications of Artificial Intelligence, Elsevier, 2020 https://doi.org/10.1016/j.engappai.2020.103479
Bilal & Millie Pant (2020) Parameter Optimization of Water Distribution Network – A Hybrid Metaheuristic Approach, Materials and Manufacturing Processes, 35:6, 737-749 https://doi.org/10.1080/10426914.2020.1711933
Bilal, Rani, D., Pant, M. et al. Dynamic programming integrated particle swarm optimization algorithm for reservoir operation. Int J Syst Assur Eng Manag 11, 515–529 (2020). https://doi.org/10.1007/s13198-020-00974-z
Bilal, Pant, Millie, and Vaclav Snasel. "Design optimization of water distribution networks through a novel differential evolution." IEEE Access 9 (2021): 16133-16151. https://doi.org/10.1109/ACCESS.2021.3052032
Bilal, Pant, M. & Rani, D. Large scale reservoir operation through integrated meta-heuristic approach. Memetic Comp. (2021). https://doi.org/10.1007/s12293-021-00327-8
Bilal, Millie Pant, Milan Stanko, Leonardo Sales, “Differential evolution for early-phase offshore oilfield design considering uncertainties in initial oil-in-place and well productivity,” Upstream Oil and Gas Technology, Volume 7, 2021, 100055, ISSN 2666- 2604 https://doi.org/10.1016/j.upstre.2021.100055
Deep Learning for Biomedical Data
FNU Bilal, Jesung Moon, Smita Rindhe, Elizabeth A. Maher and Robert M. Bachoo “Deep Learning based automated Cell Quantification Reveal Glioblastoma Multiforme Cell Heterogeneity in High-Throughput Microwell Devices” (On Going)
Probabilistic & Bayesian Modeling
Jaime Guerrero; Zachariah Malik; FNU Bilal; Soma Jana; Aparajita Dasgupta; Khuloud Jaqaman, “Inference of VEGFR2 dimerization kinetics on the cell surface by integrating single-molecule imaging and mathematical modeling" PLOS Computational Biology (Under Review)