MIST Applications

Department of Computer Science & Engineering (CSE)

Ellora Yasi

Research Assistant, Department of Computer Science & Engineering (CSE)

Academic Experience:

  • B.Sc. in Computer Science and Engineering (CSE)

Military Institute of Science & Technology

Date of Graduation: April 2024

Professional Experience:

  • Research Assistant, Department of CSE, Military Institute of Science & Technology (MIST)

 Duration: October 2024 – Present

  • Software Engineer Intern, IT Division, Trust Bank Limited

 Duration: January 2023 – February 2023

 

Awards/ Honor’s:

  • Women In Digital's Digital Innovation Challenge for Women 2023 (2nd Runners-Up) Team: MIST_Grande
  • National Girls' Programming Contest 2022 (6th position)

Team: MIST_Object_Grind

  • Poster Presentation in the Environment Mega fest 2023 (1st Runners-Up)

Team: MIST_FloodPredictors presented our thesis research and showed a panel dashboard.

  • National Collegiate Programming Contest - NCPC 2023 (145th position)

Team: MIST_Tatakae

  • MIST Intra Department Girls' Programming Contest 2022 (Champion) October 2022
  • Independence Day Programming Contest 2023 (4th Place)
  • Participated in National Girls' Programming Contest-2021 DIU (57th position)

Team: MIST_Peraheen

  • Participated in Ada Lovelace National Girls' Programming Contest 2022 (55th position)

Team: MIST_ChillCoder

Academic Projects:

  • Rice Leaf Disease Classification Machine Learning Project

A classification system for rice leaf diseases leveraging transfer learning with pre-trained TensorFlow models for enhanced accuracy and efficiency. 

Technology: Python, TensorFlow, Transfer Learning, CNN architecture, Image Augmentation, and Matplotlib.

  • AutoML Tool for Flood Assessment Machine Learning Project An AutoML tool for flood assessment with the features of flood prediction and flood mapping using image segmentation.

Technology: Python, Scikit-Learn classifiers, Tabular GAN, Transfer Learning, CNN architectures, UNet, and Panel. (B.Sc. Thesis)

  • BiteSaver An app designed to sell excess food and reduce food waste by connecting sellers with potential buyers.

Technology: Figma. also presented a business model. (May 2023)

  • An IoT-based Farmer Assistive System An app will help the farmers predict required NPK values and water requirements based on soil information from different sensors built for the Integrated Design Project (IDP).

Technology: Dart, Framework- Flutter, UI Design, Documentation, Figma. (Sep 2022 – June 2023)

  • MCC Virtual Assistant An efficient club management and ranking system for the MIST Computer Club for the students.

Technology: HTML, CSS, JavaScript, PHP, SQL and XAMPP. (Mar 2022)

  • Train Up Developed a comprehensive management system for trainees during an internship at Trust Bank.

Technology: SQL, HTML, CSS, JavaScript, Bootstrap, and PHP.

  • Parking Management System An intelligent parking system for automobiles to avoid collision in garages based on a microcontroller.

Technology: Arduino. (Mar 2022 - Jul 2022)

  • Algo Rhytm An offline problem-solving judge for judging the solutions of programming problems, will benefit students who don’t always have access to the internet. Technology: Java and Swing. (Sep 2021 - Dec 2021)

Research Interests:

Research Domain: Deep learning, Neural Networks, Generative Models, Data Science, Natural Language Processing, Computer Vision.

Journal Publications:

  • Yasi, E., Shakib, T.U., Sharmin, N. et al. Flood and Non-Flood Image Classification using Deep Ensemble Learning. Water Resour Manage 38, 5161–5178 (2024). https://doi.org/10.1007/s11269-024-03906-9
  •  FloodWatch: An AutoML Tool for Flood Forecasting and Classified Flooded Area Segmentation using Weather Data and Images. (In preparation for the Natural Hazards (NHAZ) 2024)

Conference Publications:

  • T. U. Shakib, E. Yasi, T. H. Rizu and N. Sharmin, "Tabular Generative Adversarial Networks (TabGANs) for Flood Forecasting from Meteorological data," 2023 26th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2023, pp. 1-6, doi: 10.1109/ICCIT60459.2023.10441391
  • T. U. Shakib, E. Yasi, T. H. Rizu and N. Sharmin, "An interactive flood forecasting tool with ensemble-based machine learning model: A Bangladesh Perspective," 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023, pp. 1-7, doi: 10.1109/ICCCNT56998.2023.10306471
  •  GreenAssist: an AI and IoT-Driven Irrigation and Fertilizer Management System for Enhancing Agricultural Productivity. (In preparation for the IEEE WIECON-ECE 2024)

 

Technical Skills:

1. Programming Language                         C/C++, Python, Java, JavaScript, Assembly

 

2.Database                                                  Oracle, Firebase, MySQL

 

3.Tools                                                        CodeBlocks, Google Colab, Visual Studio, Eclipse, Git, Blender, Kaggle

 

4.Simulator                                                 Cisco Packet Tracer, Circuit Maker

 

5.Scripting & Modelling                            HTML, Shell Script, LATEX

 

6.Graphics                                                  OpenGL, Blender