Faculty Profile

Dr. Muhammad Rizwan
Lecturer
PhD Computer Science

With a Ph.D. in Computer Science and over 9 years of experience as a Lecturer in Information Technology, I am deeplypassionate about the intersection of Natural Language Processing (NLP), Language Modeling, Mental Health, and Social Informatics. I have extensive experience teaching courses like Data Science, Machine Learning, and Object-Oriented Programming and mentoring undergraduate students in their project journeys. Additionally, I’ve served as an Internship Coordinator, fostering collaboration between industry and academia to enhance student learning and career preparation.

Throughout my career, I have published 9 journal articles and 2 international conference papers. My research is hands-on—I personally conduct all experiments, driven by a genuine love for exploring new models and techniques. Python is my go-to language, and I frequently work with advanced NLP libraries like Transformers, NLTK, PyTorch, TensorFlow, Word2Vec, and BERTopic to deepen insights into language processing.

I have guided numerous undergrad projects, primarily utilizing Python and Java, and I am committed to helping students build robust technical skills and a curiosity-driven approach to problem-solving. As an Internship Coordinator, I’ve built bridges between academia and industry, creating valuable opportunities for students to gain hands-on experience in real-world applications.

Journal Articles

  1. First Author, “Depression intensity classification from tweets using fasttext based weighted soft voting ensemble,” Computers, Materials & Continua, vol. 78, no. 2, pp. 2047–2066, 2024.
  2. Corresponding Author, “Unifying sentence transformer embedding and softmax voting ensemble for accurate news category prediction,” Computers, vol. 12, no. 7, p. 137, 2023.
  3. First Author, “Depression classification from tweets using small deep transfer learning language models,” IEEE Access, vol. 10, pp. 129 176–129 189, 2022.
  4. Co-Author, “Dual language sentiment analysis model for youtube videos ranking based on machine learning techniques,” Pakistan Journal of Engineering and Technology, vol. 3, no. 2, pp. 213–218, 2020.
  5. Co-Author, “Early heart disease prediction with minimal attributes using machine learning,” Pakistan Journal of Engineering and Technology, vol. 3, no. 2, pp. 178–182, 2020.
  6. Co-Author, “Multi-class classification of the youtube comments using machine learning,” Pakistan Journal of Engineering and Technology, vol. 3, no. 2, pp. 183–188, 2020.
  7. Co-Author, “Sentiment base emotions classification of celebrity tweets by using r language,” Pakistan Journal of Engineering and Technology, vol. 3, no. 2, pp. 95–99, 2020.
  8. Co-Author, “Collection of autonomous system level topology using looking glass servers,” Pakistan Journal of Science, vol. 71, no. 4, p. 69, 2019.
  9. Co-Author, “Recommendation of effectiveness of youtube video contents by qualitative sentiment analysis of its comments and replies,” Pakistan Journal of Science, vol. 71, no. 4, p. 91, 2019.

 

International Conference Proceedings

  1. First Author and Presenter, “Prevalent frequency of emotional and physical symptoms in social anxiety using zero shot classification: An observational study,” in Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (EACL 2024), 2024, pp. 145–152.
  2. Co-Author, “Database schema independent architecture for NL to SQL query,” in Proceedings of The 6th International Conference on Language and Technology 2016 (CLT16), 2016, pp. 45–56.

NLP & Language Models: Creating and fine-tuning models, especially for mental health insights and social informatics applications.
Machine Learning & Data Science: End-to-end project development and data-driven decision-making.
Programming in Python & Java: Developing, mentoring, and experimenting with emerging tech.

Gold Medal
Received gold medal in MCS by securing 1st position in the whole batch of 100 students.
Issued by The Islamia University of Bahawalpur, Pakistan