Lecturer at Sir syed Case Institute of Technology Islamabad, Pakistan
🌟 Muhammad Wajid is a passionate computer scientist specializing in deep learning 🤖, natural language processing 📖, and computer vision 👁️🗨️. As a Lecturer at Sir Syed CASE Institute of Technology, he teaches and mentors in cutting-edge fields. With a strong academic foundation from COMSATS University and Gomal University 🎓, he has earned recognition for his impactful research, including publications in prestigious journals 📜. Muhammad’s expertise spans Python, TensorFlow, PyTorch, and Scikit-Learn, making him a skilled innovator in AI and machine learning 🚀.
Publication Profile :
Google Scholar
Education 🎓
Muhammad Wajid earned his Master of Science in Computer Science from COMSATS University Islamabad (2020–2023) with a CGPA of 3.43/4.00. His thesis focused on using deep learning and preprocessing techniques to detect communities in graph-structured data. Prior to this, he completed his Bachelor of Computer Science at Gomal University (2015–2020), graduating with a stellar CGPA of 3.79/4.00. His undergraduate thesis involved the classification and identification of iris flowers using machine learning. Muhammad also holds a certification in machine learning from Stanford and freelancing from the Virtual University of Pakistan, further showcasing his commitment to technical growth.
Professional Experience💼
Muhammad is a Lecturer at the Sir Syed CASE Institute of Technology in Islamabad, Pakistan (Feb 2024–Present). He teaches advanced courses in Deep Learning, Natural Language Processing (NLP), Programming Fundamentals, and Web Technology. He also supervises final-year projects in cutting-edge domains like computer vision, deep learning, and NLP. Previously, he served as a Research Assistant at COMSATS University Islamabad (Feb 2019–Jul 2021), contributing to impactful research under expert supervision. His efforts have led to publications and advancements in deep learning and NLP.
Research Interests 🔬
Muhammad’s research interests lie at the intersection of deep learning, natural language processing, computer vision, and medical imaging. He is particularly passionate about applying AI techniques to tackle real-world challenges, including tumor segmentation, financial forecasting, and community detection in graph-structured data.
Publications Top Notes 📚
- Wajid, Muhammad, Iqbal, Ahmed, Malik, Isra, Syed Jawad Hussain, and Yasir Jan.
“A semi-supervised approach for breast tumor segmentation using sparse transformer attention UNet.”
Pattern Recognition Letters, 2024.
[Impact Factor: 3.9]
DOI: 10.1016/j.patrec.2024.11.008
- Wajid, Muhammad, and Ahmad Kamran Malik.
“A Stacked GRU-based Recurrent Deep Learning Approach for Bitcoin Price Prediction to Maximize Profit.”
Complex & Intelligent Systems, 2024.
[Impact Factor: 5.0]
[Under Review]