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Syed Muhammad Waqas

Lecturer
Iqra University

Education

  • MS (CS), Bahria University, Karachi, Pakistan.
  • BS (CS) FAST National University of Computer and Emerging Sciences, Karachi Campus, Pakistan.

Research Interests

  • Machine learning techniques include Clustering algorithms (DBSCAN, and Density peaks clustering algorithms), deep learning, fuzzy logic, etc.
  • Classification of source code of comments, Optimization, and Cryptocurrency algorithms.
  • Computer vision
  • Data science, big data, data analytics, classification, prediction, andother data mining tasks.

Biography

Syed Muhammed Waqas is a dedicated educator and researcher specializing in computer science. Since February 2023, he has been actively involved in teaching undergraduate courses, including Artificial Intelligence, Data Science, Object-Oriented Programming, and Mobile Application Development. His commitment to education is complemented by his role in supervising both undergraduate and postgraduate research projects, guiding students in their academic pursuits.

Waqas holds a Master of Computer Science from Bahria University, where he achieved a remarkable 3.83 CGPA and was honored as a Gold Medalist for his academic excellence. His master’s thesis, titled “Density Peaks Clustering Based on Gaussian Fuzzy Neighborhood with Noise Parameter,” reflects his deep engagement with advanced machine learning techniques, particularly in clustering algorithms. He also earned his Bachelor of Science in Computer Science from FAST National University of Computer and Emerging Sciences.

In addition to his academic qualifications, Waqas has extensive software development experience. He has worked as a Software Engineer at M.M. Corporation and ITsec (Pvt.) Ltd., where he gained hands-on experience in application development, maintenance, and documentation. His technical skill set includes proficiency in multiple programming languages such as Python, C, C++, and Java, as well as familiarity with various database management systems including Oracle and SQL Server.

He is passionate about leveraging his technical expertise and the latest teaching methodologies to foster a dynamic learning environment. He is dedicated to preparing the next generation of computer science professionals, instilling in them the skills needed to navigate and excel in an increasingly data-driven world. With a strong work ethic, excellent communication skills, and a collaborative spirit, Waqas continues to contribute to both his students’ success and the advancement of research in the field of computer science.

Publications

  • Syed Muhammad Waqas, Kashif Hussain, PN Suganthan. “Density Peaks Clustering Based on Gaussian Fuzzy neighborhood with noise parameter” accepted in Expert Systems with Applications journal. (I.F. 7.5)
  • Niazi, T., Das, T., Ahmed, G., Waqas, S. M., Khan, S., Khan, S., … & Wasi, S. (2023). Investigating Novice Developers’ Code Commenting Trends Using Machine Learning Techniques. Algorithms, 16(1), 53. (1.F. 2.36)
  • Omar, M.S., Waqas, S. M., Talpur, Khan, S., & Ahmad, S. (2023), Harris’s Hawks Optimization-Tuned Density-based Clustering. Sukkur IBA Journal of Emerging Technologies, 6(1), 23-34.
  • Abdul Rehman, Syed Muhammad Waqas, Sumra Khan, Shaukat Wasi. “Towards a Traffic Management Solution for Smart Cities.” Submitted in Pattern Recognition.
  • Syed Muhammad Waqas, Kashif Hussain, Ghulam Muhammad, Sumra Khan, PN Suganthan. “Density-Based Clustering: A Systematic Literature Review” submitted in Pattern Recognition Journal.
  • Sajjad Ali, Sumra Khan, Syed Muhammad Waqas, Teerath Das. “Systematic Literature Review on Cryptocurrency Price prediction using Deep Learning Model” submitted in Complexity Journal. Rimsha Javed, Sumra Khan, Syed Muhammad Waqas, Meerab Amir. “Detection of Deep Fake and Real People using Al Techniques” submitted in Algorithms journal

IU ORIC is thrilled to announce that 4 innovative packaging designs from IU have been granted design patents by the Intellectual Property Organization of Pakistan (IPO). A special endorsement to Dr. Baber Khan from the Media Sciences Department for his exceptional contributions.

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