Rushikesh Prakash Borse

Assistant Professor

Area of Expertise: Data Analytics (ML, Deep learning, NLP)

Email: [email protected]

Rushikesh Borse holds a PhD degree in Engineering from IIT Bombay. His area of interest lies in Data Analytics & Machine Learning, Computer Vision and Deep Learning. He has a couple of decades of experience in teaching, research and consultancy. He is also a consultant to Great Learning, upGrad, SimplyLearn and The Knowledge Academy, UK. He has 15+ Scopus research articles and a patent to his credit. Apart from the technical aspects, he also conducts sessions on ‘Science and Spirituality’ and is a member of VOICE Pune.  He explains the concepts of Niti-Sastras and teachings of Bhagwat Gita to many.

Research Interests

He has total experience of over 2 decades and over 14 years of domain experience in AI and ML with focus on implementing Computer Vision applications using machine learning and deep learning models. Secondary interest lies in NLP (natural language processing) and implementing signal processing algorithms for 1D, 2D data using MATLAB and Python. He is also a reviewer to many journals/conferences from reputed publication houses like Springer, IEEE, Elsevier, Inderscience, CRC press etc.

Research Grants

Received grants more than INR 6 lakhs+ for developing project, patent and organizing technical conferences. Grant received from Pune University.

Peer - reviewed Journal Articles

• Rishabh Iyer, Rushikesh Borse, Subhasis Chaudhuri, Embedding capacity estimation of reversible watermarking schemes, Springer Sadhana Journal, Academy Proceedings in Engineering Sciences, Volume 39, Part 6, December 2014, pp. 1357–1385. https://link.springer.com/article/10.1007/s12046-014-0288-8
• Supriya Londhe, Rushikesh Borse, “Emotion recognition based on various Physiological Signals: A review, ICTACT Journal of Communication Technology, Volume 9, issue 3, Sept 2018. pp 1815-1822. (IET Inspec Indexed) http://ictactjournals.in/paper/IJCT_Vol_9_Iss_3_Paper_2_1815_1822.pdf
• Rushikesh Borse, Rochishnu Das, Devasish Dash and Akshay Yadav, Detecting early warning signs of employee attrition using Machine Learning Algorithms, Accepted for publication at the IOS press journal of intelligent and fuzzy systems, 2024

Technical articles

• Rajeshwari Krishnamurthy and Rushikesh Borse, Why is AIML Best Suited for Metaverse Consumer Data Analysis? California Management Review (Insights), Jan 2023

Book Chapter(s)

• Manisha Choudhary, Monika Lokhande, Avinash Bhute, and Rushikesh Borse, A Machine Learning approach to aid Paralysis patients using EMG signals, Invited book chapter for Elsevier’s Advanced Data Mining Tools and Methods for Social Computing, 2022. https://www.sciencedirect.com/science/article/pii/B9780323857086000138
• Pallavi Derver, Rushikesh Borse, Deep Learning based Paperless Attendance Monitoring System, Springer International Conference on Signal and Data Processing,  ICSDP-2019, published as book chapter in Springer Lecture Notes Series in Electrical Engineering, Jan 2021. https://link.springer.com/chapter/10.1007/978-981-15-8391-9_47
• N. Darapaneni and Rushikesh Borse, "Traffic Monitoring and Analysis at Toll Plaza," 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), USA 2021, doi:10.1109/IEMTRONICS52119.2021.9422543 (https://ieeexplore.ieee.org/document/9422543)
• Abhishek Kharade, Rushikesh Borse, Image Analytics To Detect Cigarette In A Frame Using Deep Learning, Springer International Conference on Signal and Data Processing,  ICSDP-2019, published as book chapter in Springer Lecture Notes Series in Electrical Engineering, Jan 2021. https://www.springerprofessional.de/en/image-analytics-to-detect-cigarette-in-an-image-using-deep-learn/18759254
• Tejas Agarwal, Mira Andhale, Anand Khule, and Rushikesh Borse, Age and Gender Classification based on Deep Learning, Springer International Conference TechnoSocietal-2020, published as book chapter in Springer Lecture Notes Series in Advanced Technologies for Societal Applications, May 2021.  https://link.springer.com/chapter/10.1007/978-3-030-69921-5_43
• Sonal Sharma and Rushikesh Borse, Automatic Agriculture Spraying Robot with Smart Decision Making, Springer Conference at Jaipur, Sept 2016, published as Book Chapter in Springer ASIC Series Book, Sept 2016. https://link.springer.com/chapter/10.1007/978-3-319-47952-1_60

Conference presentations

• Rushikesh Borse and Rajeshwari Krishnamurthy, Harnessing AIML in metaverse data analytics, to provide a superior customer experience, presented at ICODO conference at IIM Ahmedabad, 16-17 Dec 2023
• Rushikesh Borse and Rajeshwari Krishnamurthy, How is Metaverse 3D Advertising different from 2D advertising? presented at the 17th NAEMEI conference at Great Lakes Institute of management, Chennai 18 Dec 2023
• Rushikesh Borse and Rajeshwari Krishnamurthy, How does Metaverse impact customer experience and brand outcomes? -An AIML based user analytics study, presented at the 16th NAEMEI conference at Great Lakes Institute of management, Chennai 16-18 Dec 2022

International and national conference papers

A list of all these papers is at https://www.scopus.com/authid/detail.uri?authorId=55421091800

Google Scholar Link:

https://scholar.google.co.in/citations?user=K1jPjt8AAAAJ&hl=en

Scopus Author link:

https://www.scopus.com/authid/detail.uri?authorId=55421091800

Patent:

• Published a patent on “Battery Life Management System and Method”. Mumbai patent office on 2nd April 2021. (Application No: 202021005342)

Invited speech/Panel discussions

• Consulting trainer and ML/DL project developer to many industries and top Ed-Tech companies like Great Learning, SimplyLearn, upGrad, The Knowledge Academy (TKA) UK.
• Delivered more than 30 talks as invited speaker and resource person for various events & workshops at places like IIT Bombay, Pune University etc., on topics related to Deep learning, Data Science, Computer vision etc.
• Also conducted day long sessions on MATLAB, Python and LaTeX software training.