Saurabh Varshneya

PhD Student

Bio

Since 2019 Saurabh Varshneya has been a research associate and PhD student at the TU Kaiserslautern in the Machine Learning group supervised by Prof. Dr. Marius Kloft. He received his M.Sc. in computer science at the TUK in 2019. During his studies, he worked as a teaching assistant at the department of computer science and a research assistant at DFKI, Insiders Technologies GmbH and at the chair of Prof. Kloft.

Research interests

Saurabh Varshneya is interested in the interpretability of neural networks, their improvement by training algorithms, early and late fusion techniques for heterogeneous data and image processing. He has been working on multimodal classification, anomaly detection and semantic segmentation using deep learning.

Appointments and scientific matters: ==gdhJ3co5WZ5FGQjNnL15WatsGbuQWZ
Office: RPTU, Building 36, Room 316 - 67653 Kaiserslautern
Office phone: +49 631 205 3326

Curriculum Vitae

Education

2016-2019: Master degree in Computer Science, TU Kaiserslautern, Germany
2008-2012: Bachelor degree in Compuer Engineering, Jamia Millia Islamia, India

Professional Experience

since 2019: PhD candidate - Researcher, RPTU Kaiserslautern, Kaiserslautern, Germany
since 2018: Teaching Assistant for the course "Very Deep Learning"
2018-2019: Research Assistant, ML Group, RPTU Kaiserslautern, Kaiserslautern, Germany
2017-2018: Research Assistant, Insiders Technologies GmbH, Kaiserslautern, Germany
2016-2017: Research Assistant, Computer Vision Group, DFKI, Kaiserslautern, Germany
2013-2016: Software Developer, Tata Consultancy Sevices, India

Key publications

S. Varshneya, A. Ledent, P. Liznerski, A. Balinskyy, P. Mehta, W. Mustafa, and M. Kloft Interpretable Tensor Fusion. Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), (to appear) , 2024.
M Hussong, S Varshneya, P Rüdiger-Flore, M Glatt, M Kloft and J C Aurich A process planning system using deep artificial neural networks for the prediction of operation sequences. Procedia CIRP, 2023.
S Varshneya, A Kölsch, A Mishra, MZ Afzal, and M Liwicki Recognizing Challenging Handwritten Annotations with Fully Convolutional Networks. International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018.
S Varshneya, L Yi, S Ehmsen, M Cassani, M Glatt, P Liznerski, M Kloft, E J da Silva, and J C Aurich Deep Learning zur Prozessüberwachung in der additiven Fertigung. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 2020.
S Varshneya TUKL INDUCING INTERPRETABILITY IN CNN. AHRP Berichte, 2020.
S Varshneya, M Hussong, M Glatt, P Rüdiger-Flore, P Liznerski, M Kloft, and J C Aurich Deep Learning zur Unterstützung der Arbeitsplanung. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 2021.
S Varshneya, A Ledent, RA Vandermeulen, Y Lei, M Enders, D Borth, and M Kloft Learning interpretable concept groups in CNNs. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.

(* denotes equal contribution)

MACHINE LEARNING GROUP

RPTU KAISERSLAUTERN-LANDAU