About
I am Dr.Thupakula Bhaskar currently working as Associate Professor in the department of Computer Engineering, Sanjivani College of Engineering (An Autonomous Institute), Kopargaon, Maharashtra affiliated to SPPU Pune. I am Having 20 years of teaching experience to UG and PG Computer Engineering classes & has guided 25+ Projects at UG & PG Level Students. I have special interest of research in the areas of Machine Learning & Deep Learning. I have published & presented 60+ research papers in the journals of national as well as international & in National and international Conferences. I am having 3 patents in that 1 is Australian Patent & received Grant also for that. I am the author of Text Book entitled as Machine learning & Deep Learning Concepts & Application (ISBN:978-93-5625-288-2).
My Online Profiles:
https://sites.google.com/view/bhaskart (Personal Website)
https://orcid.org/0000-0002-0669-3966 (Research Profile)
https://vidwan.inflibnet.ac.in/profile/219913 (Vidwan Profile)
https://sanjivanicoe.org.in/index.php/component/k2/item/77-prof-t-bhaskar(Working Profile)
Employment
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Sanjivani College of Engineering,Kopargaon Associate Professor2012 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (73)
- Sanjeevani Virtual Herbal Garden Save
- IoT enabled smart energy meter using ESP32 and blynk Save
- Hybrid deep learning framework for enhanced target tracking in video surveillance using CNN and DRNN-GWO Save
- AutoML-Driven Deep Learning for Fake Currency Recognition Save
- An adaptive learning model for secure data sharing in decentralized environments using blockchain technology Save
- Predicting Blood Donations with Regression Algorithms Save
- Underwater Object Classification: Sonar-based Rock vs. Mine Detection Save
- Smart Thermostat for Energy Conservation Save
- Developing Personality Traits through Social Media Analysis Save
- A comparative evaluation of machine learning ensemble approaches for disease prediction using multiple datasets Save