Mrs. Yogita Shivaji Hande

Bio

I am an Information Technology professional with more than 10 years of academic and 3.8 years of industry experience, dedicated to advancing learning in Information Technology and Computer Engineering. My teaching philosophy focuses on connecting strong theoretical foundations with practical, industry-oriented applications.

I strive to create an interactive learning environment that promotes critical thinking, innovation, and problem-solving skills among students. I am also motivated to contribute to research in emerging areas like Artificial intelligence, encouraging students to engage in research driven learning and technological innovation.

Through teaching, mentorship, and research, I aim to support MIT-WPU’s vision of developing competent, ethical, and future ready technology professionals.

Professional Affiliations: ISTE (International Society for Technology in Education)

Specialisation: Artificial Intelligence and Data Science

Areas of Expertise: Artificial Intelligence, Machine Learning, Deep Learning, Computer Networks, Software Defined Networks

Teaching Experience: 10 Years

Industry/Research Experience: 3.8 Years

Education:

Ph.D.: Ph.D, in Computer Engineering - GITAM University, Hyderabad

M.Tech: M.E in Information Technology - MIT COE,Pune

B.tech: B.Tech. Information Technology - Sinhgad Institute, Pune

Publications and Research Work:

1. Hande, Y., Vairagade, R. S., Bhandari, M. A., Gutte, V. S., Chitalkar, S. M., & Javale, D. P. (2024). Tasmanian devil hunting optimization enabled deep Maxout network for brain activity detection based on motor imagery EEG signals. Biomedical Engineering: Applications, Basis and Communications, 36(6), 2450032. https://doi.org/10.4015/S1016237224500327

2. Vairagade, R. S., Parkhi, P., Hande, Y., & Hambarde, B. (2025). Blockchain‐powered framework for trust enhancement in FinTech: A comprehensive trust evaluation approach. Concurrency and Computation: Practice and Experience, 37(3), e8357. https://doi.org/10.1002/cpe.8357

3.Y. Hande, “A Comparative Analysis of Client Side Rendering and Server Side Rendering,” SSRN Electronic Journal, 2025. Available: https://ssrn.com

4. Reference (APA Style) Hande, Y., Lokhande, J., & Gunjal, A. S. (2026). Decoding explainable AI: A critical review of emerging techniques, key challenges, and future pathways. In Lecture Notes in Networks and Systems (pp. 259–270). Springer. https://doi.org/10.1007/978-981-96-8895-1_23

Subjects Taught:

1. Artificial Intelligence and Expert System
2. Artificial Intelligence and Machine Learning
3. Python Programming

Scopus Id:
https://www.scopus.com/authid/detail.uri?authorId=57207880532

Google scholar Id:
https://scholar.google.com/citations?hl=en&user=YqzWWdEAAAAJ

Orchid Id:
https://orcid.org/0000-0003-3335-545X

Linked In:
https://www.linkedin.com/in/dr-yogita-hande-a606b245/