Rizwan Ali

Rizwan Ali
Lecturer
Computer Science
RESEARCH INTERESTS

Artificial Intelligence • Large Language Models (LLMs) • Retrieval-Augmented Generation (RAG) • Medical Decision Support Systems • Internet of Things (IoT) • Smart Sensors and Embedded Systems • Human-Computer Interaction • Intelligent Information Systems

Profile

Rizwan Ali is a Computer Scientist, Instructor, Researcher, and Entrepreneur with expertise in Artificial Intelligence, Full-Stack Software Development, and Intelligent Information Systems. He serves as a Lecturer in the Department of Computer Science at The Benazir Bhutto Shaheed University of Technology and Skills Development, Khairpur Mirs, where he teaches undergraduate courses in Web Technologies, Human-Computer Interaction, Operating Systems, and Object-Oriented Programming, and mentors students under the People Information Technology Program (PITP), a joint initiative of Sukkur IBA University and the Government of Sindh. He is also the Founder and Full Stack Developer of NexaKode, a software development company delivering custom web and mobile solutions for startups and businesses. Prior to joining BBSUTSD, he served as an Instructor at Iqra University's Faculty of Engineering Science and Technologies and as a Co-Trainer for the PITP Mobile Application Development Boot Camp at Sukkur IBA University. His research spans AI-driven healthcare and smart sensing technologies, with a particular focus on Retrieval-Augmented Generation systems for low-hallucination clinical decision support.

Qualification

  • Degree
  • From
  • Major
  • Year
  • MS(CS)
  • Shah Abdul Latif University, Khairpur Mirs
  • Computer Science (AI, Intelligent Systems, Advanced Computing)
  • 2026-Present
  • BS(CS)
  • Sukkur IBA University
  • Computer Science
  • 2019-2024
  • Fundamentals and Advances in Ultra-Low Moisture Sensing: From Nanostructured Interfaces to Smart Industrial Infrastructure
    —  Spectrum of Engineering Sciences, 2026. ISSN (e): 3007-3138 | ISSN (p): 3007-312X
  • Enhancing Clinical Decision Support: A RAG-Based System for Accurate, Citable, and Low-Hallucination Medical Recommendations
    —  4th International Multidisciplinary Conference on Emerging Trends in Engineering Technology (IMCEET 2026), BBSU-TECH Khairpur