Mrs. Rashmi Ashwinikumar Rane

Bio

I believe in fostering analytical thinking, practical problem-solving, and lifelong learning among engineering students. As a faculty member in Computer Engineering, my teaching philosophy emphasizes concept clarity, real-world application, and active learning through labs, case studies, and collaborative challenges.

I am motivated to bridge the gap between theory and industry expectations, especially in core areas like Operating Systems and Systems Programming.

Through innovative pedagogy and research engagement, I strive to contribute to MIT-WPU’s vision of developing globally competent, ethically grounded, and socially responsible technology professionals.Professional Affiliations: Life Membership of ISTE

Specialisation: Computer Science and Engineering

Area of Expertise: Machine Learning, Deep Learning, Social Data Mining

Teaching Experience: 24 years

Industry/Research Experience:

Currently working on ERASMUS+ Capacity Building in Higher Education (CBHE) Project titled “Next-Generation Specialist Information Support (NSIS) Program on Developing Information, Research, and Digital Skills for Business, Innovation, and Entrepreneurship in India, Sri Lanka, and Nepal.”

Education

Ph.D: Pursuing PhD in CSE at Sathyabama Institute of Science and Technology

M.Tech: M.Tech. In Computer Science and Engineering - PRMIT, Badnera

B.tech: B.Tech. In Computer Engineering - PCEA, Nagpur

Publications and Research Work:

1. Rane, Rashmi, Subhashini, R.(2026) - “An Automated Fake News Detection Framework Using Residual Convolutional Bi-LSTM with Improved Optimisation-Based Weighted Feature Representation”. Journal of Information & Knowledge Management , 2550135 Rashmi Rane, R. Subhashini,(2025),”Multi-feature classification for fake news detection using multiscale and atrous convolution-based adaptive temporal convolution network”, Data & Knowledge Engineering, Volume 160,102469

2. R. Rane, Subhashini R. and Surendran. R, (2024), "An Innovative Fake News Detection in Social Media with an Efficient Attention-Focused Transformer Slimmable Network," 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), Sakhir, Bahrain, pp. 177-183

3. R. Rane. Disha Shah, S. Kinger, (2024), “Emotion Detection using Stack Auto Encoder, Deep Learning and LSTM Model”, International Journal of Computing and Digital Systems, Vol 15, Issue 1 Mamta Bhamare, Pradnya V. Kulkarni, Rashmi Rane, Sarika Bobde, Ruhi Patankar,(2024) Chapter 14 - TinyML applications and use cases for healthcare, TinyML for Edge Intelligence in IoT and LPWAN Networks, Academic Press, Pages 331-353

Subjects Taught: Digital Electronics and Logic Design, Computer Organization, Systems Programming, Object Oriented Programming using C++ and Java, Operating Systems

Scopus Id:
https://www.scopus.com/authid/detail.uri?authorId=57191090200

Google Scholar Id:
https://scholar.google.com/citations?user=m9ey5SQAAAAJ&hl=en

Orcid Id:
https://orcid.org/0000-0002-0982-8061

Linked In:
https://www.linkedin.com/in/rashmi-rane-93b8a639/