Dr Shrutika Sawant

AI software specialist at Fraunhofer IIS
Rapidly growing needs of humans and corresponding exploitation of natural resources threatens the ecological integrity of the forest and its inhabitants. Realizing the need for immediate conservation of wildlife, it's our bonded duty to act now to reverse the declining trend of climate. I firmly believe the GAIA Initiative is one such step towards this goal. As a researcher, I am greatly obliged to Fraunhofer IIS and Leibniz-IZW for allowing me to contribute to solve problems related to wildlife conservation.

Shrutika is currently working as AI (software) In-charge for GAIA SAT IoT project in Fraunhofer IIS. This involves preliminary analysis of images, cleaning of dataset, labelling of images, performing augmentation and development of suitable algorithm for classifying the images. As part of her doctoral work, she has developed AI algorithms for classification of hyperspectral images captured by satellites or drones. She is also trained in working with Problem Based Learning (PBL), an appropriate methodology for problem solving.

Shrutika S. Sawant is currently working as Wissenschaftliche Mitarbeiterin in Multimodal Human Sensing research group at Fraunhofer Institute for Integrated Circuits IIS, Germany. She worked as Postdoctoral researcher at Fraunhofer Institute for Integrated Circuits IIS, Germany from February 2021 to January 2023. She received B.E degree in Electronics and Telecommunication Engineering and M.E. degree in Electronics Engineering from Rajarambapu Institute of Technology, Rajaramnagar, Maharashtra, India in 2009 and 2012, respectively. From 2012 to 2016, she was Assistant Professor at the same institute. She received PhD degree in Hyperspectral Image Classification from Vellore Institute of Technology, Vellore, India in 2020. She has authored and co-authored many scientific articles in leading Elsevier, Springer and Taylor and Francis journals, and IEEE conferences. She reviews several remote sensing and image processing based journals, including IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Infrared Physics and Technology. Her current research interests include machine learning and computer vision applications, model compression of deep neural networks (DNNs) and DNNs efficient inference.