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Staff Profile

Sangita Pokhrel

Lecturer

Staff profile image of Sangita Pokhrel

I am Sangita Pokhrel, a lecturer in the Computer Science and Data Science programs at York St John University, London Campus. I earned my MSc in Computer Science with Distinction from York St John University and my undergraduate degree in Electronics and Communication Engineering from Tribhuwan University, Nepal.

My professional interests lie at the intersection of emerging technologies and market trends, particularly in Machine Learning, Deep Learning, Data Science, and Big Data. Throughout my career, I've been dedicated to advancing research in various domains, with my work being published in reputable journals and conferences such as IEEE Explore, IEEE (ICSECS), and the International Journal of Research. My research encompasses a wide range of topics, including machine learning applications in tourism, mental health analysis of international students, predictive modelling in agriculture, artificial intelligence, computer vision, and Gen AI.

Moreover, I actively engage in industry collaborations, notably with companies like IBM in the UK, to facilitate projects that bridge academia and real-world applications. Beyond research, I am deeply committed to fostering diversity and inclusion within academia. As an active member of initiatives such as the U Connect Diversity Mentoring Scheme, Global Majority Higher Education Mentoring Programme 2023-24, and the YSJ London Women's Network, I strive to promote equity and support underrepresented groups in higher education.

Additionally, I lead the Paragon Research Group, an interdisciplinary research collective based at the London Campus, focusing on data science, blockchain, Gen AI, and the integration of technology in the business and health sectors. I am involved with university projects and other teams in collaboration to utilise the MakerVerse and The Dock to enhance learning and entrepreneurship journey of students where students can develop practical skills and hands-on experience using new technology and tools such as Virtual Reality (VR) headsets, applications and podcasting. Through collaboration with multiple universities across the UK such as St Mary’s University, University of Huddersfield and University of West London, I continuously enhance my teaching practices and pedagogical approaches in higher education. 

Further information

Teaching

As part of my role, I teach master’s level courses in Computer Science and Data Science and my modules include Big Data, Agile Software Development, Artificial Intelligence, Machine Learning and Data Visualizations across both programs. I focus on practical learning and critical thinking to prepare students for real-world challenges in these fields. I aim to create a supportive and engaging learning environment for students to excel in their studies and research. 

Research

Throughout my career, I've been dedicated to advancing research in various domains, with my work being published in reputable journals such as IEEE Xplore (ICCCI), IEEE (ICSECS), and the International Journal of Research. My research encompasses a wide range of topics, including machine learning applications in tourism, mental health analysis of international students, predictive modelling in agriculture, artificial intelligence, computer vision, and Gen AI. Additionally, I am leading some funded projects as a main supervisor and co-investigator for SAAR (Student as a Researcher) and QR (Quality-related) projects.

Publications

  •  Web Data Scraping Technology using TF-IDF to Enhance the Big Data Quality of Sentiment Analysis
    - Got Best Presentation Award in CDSBDA 2022: XVI. International Conference on Data Science and
    Big Data Analytics., 7-11 November 2022, Yogyakarta, Indonesia
  • The Role of Artificial Intelligence in Education - IEEE Proceedings, 2023 International Conference
    on Computer Communication and Informatics (ICCCI).
  • An Intelligent Tutoring System for Python Programming - presented at 2nd International
    Conference on Advances in Data Science: Recent Innovations in IoT and AI, ICADRIIA 2023 (SRM,
    Institute of Science and Technologies, India)
  • Building Customized Chatbots for Document Summarization and Question Answering using Large
    Language Models using a Framework with OpenAI, Lang chain, and Streamlit. Journal of Information Technology and Digital World, 6 (1). pp. 70-86, 2024.
  • Enhancing CNN Models with Data Augmentation for Accurate Fertilizer Deficiencies and Diseases
    Identification in Paddy Crops. In: International Conference on Business Innovation 2023 (ICOBI
    2023). ICOBI, pp. 575-582
  • AI Content Generation Technology based on Open AI Language Model. Journal of Artificial
    Intelligence and Capsule Networks, 5 (4). pp. 534-548, 2023.
  • Machine learning-based predictive models for cardiovascular risk assessment in data analysis,
    model development, and clinical implications. International Journal of Recent Advances in
    Multidisciplinary Research, 10 (10). pp. 9084-9089, 2023.
  • Exploring Cryptographic Techniques for Data Security in Resource-Constrained Wireless Sensor
    Networks: Performance Evaluation and Considerations. In: 2023 IEEE 8th International Conference
    On Software Engineering and Computer Systems (ICSECS). IEEE, pp. 176-180
  • (2024) Building Customized Chatbots for Document Summarization and Question Answering using
    Large Language Models using a Framework with OpenAI, Lang chain, and Streamlit. Journal of
    Information Technology and Digital World, 6 (1). pp. 70-86.