FACULTY
Prof. Aniruddha Pant is Adjunct Faculty – Computer Science has a Doctorate Degree in Control Systems from the University of California at Berkeley, USA. He holds MS, Engineering from University of Hawaii at Manoa, USA. He has completed BE, Engineering from College of Engineering, Pune, India.
Prof. Aniruddha has over nineteen years of work experience and is the Founder of three AI first start-ups - AlgoAnalytics: One Stop AI Shop, A2IOT: Manufacturing AI and DeepTek: Radiology AI. He was associated with Capital Metrics Technology Solutions Pvt. Ltd., Pune, Persistent Systems and TCS.
He has developed cutting edge solutions, ranging from developing advanced mathematics based financial trading algorithms to leveraging Machine Learning techniques and AI in Healthcare. He has an Expertise in Machine Learning, Optimization and Control Theory and is ML/AI technology expert.
- Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant (June 2020) Quantum Computing Methods for Supervised Learning https://arxiv.org/abs/2006.12025
- Amit Kharat, Vinay Duddalwar, Krishna Saoji, Ashrika Gaikwad, Viraj Kulkarni, Gunjan Naik, Rohit Lokwani, Swaraj Kasliwal, Sudeep Kondal, Tanveer Gupte, Aniruddha Pant (June2020) Role of Edge Device and Cloud Machine Learning in Point-of-Care Solutions Using Imaging Diagnostics for Population Screening https://arxiv.org/abs/2006.13808
- Rohit Lokwani, Ashrika Gaikwad, Viraj Kulkarni, Aniruddha Pant, Amit Kharat ( June 2020) Automated Detection of COVID-19 from CT Scans Using Convolutional Neural Networks https://arxiv.org/abs/2006.13212
- Sudeep Kondal, Viraj Kulkarni, Ashrika Gaikwad, Amit Kharat, Aniruddha Pant (April 2020) Automatic Grading of Knee Osteoarthritis on the Kellgren-Lawrence Scale from Radiographs Using Convolutional Neural Networks https://arxiv.org/abs/2004.08572
- Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant ( March 2020) Survey of Personalization Techniques for Federated Learning https://ieeexplore.ieee.org/abstract/document/9210355
- Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant ( March 2020) Survey of Personalization Techniques for Federated Learning https://arxiv.org/abs/2003.08673