Tushar Shinde currently serves as an Assistant Professor at the Indian Institute of Technology Madras Zanzibar. His professional journey includes a role as a Postdoctoral Researcher at Stanford University, USA, where he made contributions to dose prediction in radiotherapy planning, medical image compression, and video compression. Having earned his M.Tech. and Ph.D. degrees from the Indian Institute of Technology Jodhpur in 2015 and 2020, respectively, with a focus on efficient motion estimation and predictive coding, Dr. Shinde's expertise extends globally. His international research engagements include being a Sakura Science Exchange Student Researcher at Hiroshima University, Japan, and an Exchange Student Researcher at Shanghai Jiao Tong University, China.

In the realm of industry, Dr. Shinde held a Senior Engineer position at Qualcomm, Hyderabad, specializing in enhancing compression efficiency for video codecs in Qualcomm chipsets. Additionally, his entrepreneurial pursuits as an Entrepreneur in Residence at Entrepreneur First Hong Kong showcased his involvement in team formation and ideation for deep-tech startups. During his tenure at Infosys, Pune, as a System Engineer, he made technical contributions to full-stack software development.

Dr. Shinde's notable achievements include winning the 3 Minute Thesis (3MT) Competition at ICIP 2018, Athens, Greece, being selected for the Sakura Science Exchange Program by the Japan Science and Technology Agency in 2019, and representing India as a Youth Delegate in 2017 in Sochi, Russia. Acknowledged with the Best Student Award at IIT Jodhpur, Dr. Shinde continued to make an impact as a Keynote Speaker at the International Conference on RAMMML 2023. Recognition through grants and fellowships, such as the Stanford University Medical Physics Division Trainee Seed Grant Award and the Visvesvaraya Ph.D. Fellowship further highlights his dedication and contributions to research.

His research interests include:

• Image and Video Processing

• Video coding and compression, 

• Artificial Intelligence (AI), 

• Machine Learning (ML), 

• Deep learning, and 

• Applications of AI/ML in Data Science