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General Information

Full Name Momin N. Siddiqui
Date of Birth 29th September 2002

Education

  • 2023 - 2025
    Master of Science in Computer Science
    Georgia Institute of Technology, Atlanta, GA, USA
    • GPA: 4.0/4.0
    • Relevant Coursework: Mobile & Ubiquitous Computing, Human-Computer Interaction, Qualitative Methods of HCI, Education Technologies
  • 2019 - 2023
    Bachelors of Technology in Computer Engineering
    Jamia Millia Islamia, New Delhi, India
    • GPA: 3.85/4.0
    • Relevant Coursework: Algorithms & Data Structure, Machine Learning, Artificial Intelligence, Computer Vision, Object Oriented Programming, Operating Systems, Database Management System, Automata & Complexity, Discrete Mathematics, Software Engineering

Research Experience

  • 2024 - Present
    Graduate Research Assistant
    Teachable AI Lab, Georgia Institute of Technology
    • Developing model tracing for intelligent tutoring systems.
  • 2023 - 2023
    Independent Researcher
    Teachable AI Lab, Georgia Institute of Technology
    • Engineered a Python implementation of SHOP2 using Horn clause.
    • Deployed apprentice tutor on Blackboard for 2000+ classrooms across the Technical College System of Georgia.
  • 2022 - 2023
    Research Intern
    Human Machine Interaction Lab
    • Developed bidirectional LSTM architecture for feature extraction from videos.
    • Created a mobile widget interaction detection system with 90% accuracy using SciPy and AutoML.
  • 2021 - 2023
    Undergraduate Researcher
    Jamia Millia Islamia
    • Implemented face detection from image data using YOLOv5, followed by classification. Attained a classification accuracy of 95.41% using custom Squeeze-Excitation blocks in Tensorflow.
  • 2021 - 2022
    Research Intern
    MixORG (collaborating with Oslo Metropolitan University)
    • Generated synthetic embryo dataset using NVIDIA’s StyleGAN.
    • Achieved mean Average Precision (mAP) of 0.8 for embryo cleavage stage detection using YOLOv5.
    • Employed SimCLR self-supervised learning to pre-train for medical image classification.

Open Source Projects

  • 2021 - 2021
    Omedena
    • Developed a recommendation system for cognitive training problems. Built collaborative filtering using the single value decomposition (SVD) algorithm.

Academic Interests

  • Machine Learning
    • Deep Learning, Computer Vision, Natural Language Processing, Reinforcement Learning, Self Supervised Learning
  • Knowledge Based AI
    • Planning, Hierarchical Task Networks, Knowledge Representation, Reasoning, Ontologies
  • Human Computer Interaction
    • Intelligent Tutoring Systems, Educational Technologies, Human Centered AI, Explainable AI, Assistive Technologies

Other Interests

  • Soccer, reading and hiking.