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OUR TEAM

Ms. Tahreem Khalil

Lecturer (CS)

Introduction

I am Tahreem Khalil, a Lecturer in the Department of Computer Science at Nutech. I am an avid computer scientist with a master’s degree in Artificial Intelligence and over five years of experience in academia and the tech industry. My expertise lies in Machine Learning, Deep Learning, and Natural Language Processing. I am driven by a commitment to harness AI for impactful solutions, especially in education and technology. As an educator, I strive to balance a robust theoretical foundation with hands-on problem-solving skills to prepare students for dynamic, real-world challenges.

Experience

Lecturer, Comsats University Islamabad, Abbottabad Campus (Sep 2023–Aug 2024)

    • Delivered university-level courses, including OOP, Web Development, Android Development, Algorithms, Machine Learning, and Deep Learning.
    • Conducted lectures, labs, and discussions; evaluated exams and assignments; and guided students on academic and career planning.

Senior ICT Teacher, The City School, Attock Campus (Sep 2022–Aug 2023)

    • I taught a diverse range of ICT topics, including Python programming, Excel, Word, databases, robotics (Edscratch, EdPy, BumblePi), App Lab, Ocean AI, and desktop development.
    • Fostered critical thinking and creativity through innovative tools like Minecraft: The Hour of Code.

Freelance Programmer & Trainer, Fiverr.com/Upwork (June 2021–Present)

    • Developed tailored software solutions and delivered personalized programming courses.
    • Specialized in AI automation, AI tools like TensorFlow and PyTorch, ensuring client satisfaction and learning outcomes.

Qualificaion

  • Academia:
    • MS in Computer Science (AI), Comsats University Islamabad, Attock (2023)
    • BS in Software engineering, Comsats University Islamabad, Attock (2020)
  • Certifications:
    • Python Automation and testing, LinkedIn (2024)
    • Exploratory Data Analysis in Python, Data camp (2024)
    • GDSC Core Team Member, Google Developer Club (2021)
  • Training
    • Practical Time Series Analysis, Coursera (2024)
    • Advanced Machine Learning with TensorFlow, Udacity (2020)
    • Large Language Model Concepts, Data Camp (2024)

Taught Courses

I have taught a diverse range of undergraduate and graduate-level courses in Computer Science, emphasizing both theoretical foundations and practical applications.

  • Object-Oriented Programming (OOP): Focused on the principles of encapsulation, inheritance, and polymorphism, using Java for building modular and scalable applications.
  • Software Testing: Covered software quality assurance, test case design, and automation tools to ensure robust application development.
  • Android Development: Introduced mobile app development with a focus on building user-centric apps, leveraging Android Studio and Kotlin/Java.
  • Software Engineering Concepts: Explored software development life cycles, project management, and design methodologies to develop efficient and maintainable systems.
  • Human-Computer Interaction (HCI): Addressed user-centered design principles, usability testing, and interaction techniques for enhancing user experiences.
  • Web Development: Taught front-end and back-end development using HTML, CSS, JavaScript, and frameworks for building responsive and dynamic web applications.

Research

My work lies at the intersection of machine learning, natural language processing, and data analytics, with a focus on practical applications. I am currently developing AI-driven solutions for education and technology, including time-series forecasting, text summarization, Gen AI, and recommender systems.

    • Ongoing Research Projects:
      • Transformer-based text summarization for concise knowledge extraction
      • Optimization based BiLSTM model for forecasting electricity consumption analysis
      • Collaborative filtering recommender systems for user engagement learning
    • Publications:
      • Under Review

Projects

  • Appolio (2019–2020): Developed a vaccination system in Pakistan with an Android app for health workers and a ReactJS web panel for coordinators, automating vaccine monitoring.
  • ABC-BLSTM (2022–2023): Proposed ABC-BLSTM, combining Artificial Bee Colony-based feature selection and BiLSTM for energy load forecasting.
  • Text Summarization (2023–2024): Created a transformer-based model (BERT/GPT) achieving a 70% reduction in article length while preserving key details.
  • Text-to-Image Generation (2023–2024): Leveraged CLIP and DALL·E for Generative AI projects, enabling creative and marketing use cases.