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AHSANULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

Department of

Computer Science and Engineering




Ms. Tanjila Broti



Designation: Lecturer Grade-I

Email: broti.cse@aust.edu

Office Extension: 508

Room No: 7A01/F



Research Interests

  • Computer Vision
  • Machine Learning
  • Artificial Intelligence
  • Human-computer Interaction
  • Digital Image Processing

Educational Background

  • Bachelor of Science (BSc), (CSE), Ahsanullah University of Science and Technology

Honors and Achievements

  • Project Mentor (PM), First Round, 2025 - AUST Research Grant (ASRG), AUST, 2025
  • 2nd Position, Dean's List of Honor, Batch 37, Dept. of CSE, AUST, 2021
  • Finalist, HULT PRIZE AT AUST, 2019
  • Captain of Runner-up Team, AUST CSE Cricket Tournament, 2019
  • 50% Tuition Fee Waiver (Spring 2019 & Fall 2019), AUST, 2019
  • Finalist, Women Engineering Congress, BUET, 2016
  • Scholarship Recipient (HSC), Dhaka Board, 2014
  • Scholarship Recipient (SSC) for securing 113th place in Dhaka Board, 2012

Publications

Book Chapter
Journal Article
  1. Exploring usability problems of mHealth applications developed for cervical cancer: An empirical study, SAGE Journals, 2023, Sage Open Medicine. URL
  2. Medical Image Analysis System for Segmenting Skin Diseases using Digital Image Processing Technology, International Journal of Applied Information Systems, 2020, Foundation of Computer Science (FCS), NY, USA. URL
Conference Proceedings
  1. MemeStream: A Dedicated Meme Sharing Platform with AI-powered Content Validation and Real-time Engagement, International Conference on Electrical, Computer and Communication Technologies (ECCT 2026), 2026.
  2. Multi-Class Dental Diagnosis from Panoramic Radiographs Through Object Detection using YOLO, Faster R-CNN and DETR, International Conference on Electrical, Computer and Communication Technologies (ECCT 2026), 2026.
  3. A Comprehensive Analysis of Feature Selection Techniques and Their Impact on Blood Cancer Detection, 11th IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2025.
  4. A Hybrid Classical-Quantum Deep Learning Framework for MRI-Guided Alzheimer’s Disease Classification, Comparative Analysis & Explainable AI for Medical Interpretation, IEEE INDISCON-2025, 2025. URL
  5. NeuroMindscape: Deep Learning Unraveling Alzheimer's Stages through MRI-Based Classification, 3rd International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON), 2024. URL
  6. Analysis Toward Detection System of Skin Diseases (Impetigo, Melanoma, Diabetic Foot Ulcer, and Seborrheic Dermatitis), 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI), 2020.
Others