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Ms. Aliza Rana

Ms. Aliza Rana

Assistant Professor , Computer Science & Engineering (CSE)

aliza.rana@sharda.ac.in

About

Ms. Aliza Rana holds an M.Tech in Computer Science with a specialization in Data Science from Sharda University and a Bachelor's degree in Biomedical Engineering. Prior to joining academia, she gained over five years of professional experience as a Biomedical Service Engineer, specializing in advanced healthcare technologies. She worked extensively with radiotherapy and brachytherapy systems, contributing to the installation, maintenance, and quality assurance of oncology equipment across healthcare institutions. She also received specialized technical training from BEBIG GmbH, Germany, in brachytherapy systems.

Her professional experience in healthcare engineering inspired her to pursue research at the intersection of Artificial Intelligence and healthcare. Her research interests include Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Healthcare Analytics, and Medical Image Analysis. She has presented her research on AI-driven breast cancer diagnosis and classification at international conferences.

Ms. Rana is committed to fostering academic excellence through research, innovation, and interdisciplinary collaboration. Her work focuses on developing intelligent, data-driven solutions for healthcare while promoting a research-oriented learning environment that prepares students to address emerging challenges in Computer Science and Artificial Intelligence.

 

Experience
  • 6 Years
Qualification
  • M.Tech CSE - Data Science, Sharda University
  • PGDCA, IGNOU
  • B.E in Biomedical Engineering, NIET
Award & Recognition

  • Registered and Licensed Engineer, Nepal Engineering Council (NEC)

Research

  • Multimodal Intelligence in Oncology: A Systematic Review of Deep Learning and Attention-Based Fusion Strategies for Breast Cancer, IEEE Scopus Indexed
  • IoT-Enabled Smart Asthma Monitoring System Using Arduino and Wokwi Simulation, SSRN
  • Efficient Breast Cancer Subtype Classification Using Multimodal-to-Unimodal Knowledge Distillation, CRC PRESS /Taylor & Francis Scopus indexed
  • AI Based Smart Healthcare system, Taylor and Francis
  • Generative AI for Financial Document Understanding: A Retrieval-Augmented Framework for Reducing Hallucination

Certifications

  • Successful Completion of 3 day hands-on workshop on “AI for Precise Cancer Detection” from 3rd to 6th February 2025.
  • Certified Service Engineer for Brachytherapy systems.

Area of Interest

  • Artificial Intelligence
  • Multimodal Learning
  • Medical Image Analysis 
  • Healthcare Informatics 
  • AI-enabled Clinical Decision Support