Vyas completed her doctoral degree in chemical engineering from the National University of Singapore in 2016 and her undergraduate degree from IIT Varanasi in 2009. She has three years of post-undergraduate industrial experience, working in process design and development at Engineers India Limited. She has an interdisciplinary background with research experience in chemical engineering and computer vision. Her postdoctoral work is in computer vision at the University of Central Florida (2018-2022) and focused on effective representation learning through deep learning. Her long-term vision is to utilize her expertise in machine learning and bring the benefits of AI to experimental research.

• Deep learning and applications
• Bioleaching and chemical leaching
• Material characterization
• Ultrasound and applications

• Schiappa, M. C., Biyani, N., Kamtam, P., Vyas, S., Palangi, H., Vineet, V., & Rawat, Y. S. (2023). A Large-Scale Robustness Analysis of Video Action Recognition Models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 14698-14708).
• Vyas, S., Chen, C., & Shah, M. (2022, October). Gama: Cross-view video geo-localization. In European Conference on Computer Vision (pp. 440-456). Cham: Springer Nature Switzerland.
• Schiappa, M. C., Vyas, S., Palangi, H., Rawat, Y. S., & Vineet, V. (2022, June). Robustness analysis of video-language models against visual and language perturbations. In Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track.
• Fioresi, J., Colvin, D. J., Frota, R., Gupta, R., Li, M., Seigneur, H. P., … & Davis, K. O. (2021). Automated defect detection and localization in photovoltaic cells using semantic segmentation of electroluminescence images. IEEE Journal of Photovoltaics, 12(1), 53-61.
• Vyas, S., Das, S., & Ting, Y. P. (2020). Predictive modeling and response analysis of spent catalyst bioleaching using artificial neural network. Bioresource Technology Reports, 9, 100389.
• Vyas, S., & Ting, Y. P. (2020). Microbial leaching of heavy metals using Escherichia coli and evaluation of bioleaching mechanism. Bioresource Technology Reports, 9, 100368.
• Schatz, K. M., Quintanilla, E., Vyas, S., & Rawat, Y. S. (2020). A recurrent transformer network for novel view action synthesis. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXVII 16 (pp. 410-426). Springer International Publishing.
• Vyas, S., & Ting, Y. P. (2019). Effect of ultrasound on bioleaching of hydrodesulphurization spent catalyst. Environmental Technology & Innovation, 14, 100310

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