PREMIER UNIVERSITY
Department of Computer Science And Engineering
PREMIER UNIVERSITY
Department of Computer Science And Engineering
Profile
Department of Computer Science And Engineering
Asif Mohammed Saad
Lecturer, Department of Computer Science and Engineering
saad.cse@puc.ac.bd; asifsaad730@gmail.comAbout
I am Asif Mohammed Saad, a Lecturer at Premier University, Chattogram, specializing in DBMS, Microprocessors, AI, and Mobile App Development. With a robust background from KUET, I integrate theory and practice in my teaching and research. My projects include quantum neural networks, localized vehicle and object recognition with situational guidance, human activity recognition for targeted demographics, AI versus human-generated Bangla corpora comparisons, a comprehensive Chittagong weather station network, skin cancer lesion detection, and satellite-based AQI estimation. Currently, I am exploring Quantum Machine Learning in Variational Quantum Algorithms and advancing research on Quantum Error Correction.
Qualification
Pursuing M.Sc. In Computer Science and Engineering
Chittagong University of Engineering & Technology
B.Sc. In Computer Science and Engineering
Khulna University of Engineering and technology
Experience
| May 2024 Present | Lecturer, Department of Computer Science & Engineering Premier University, Chattogram, Bangladesh |
Research
- A. M. Saad, R. Mahmud, and S. Das, “Forecasting Crucial Biogeochemical Indicators of the Southern Ocean for Climate Monitoring Using Modified Kernel-Based Support Vector Regression”, Proc. 2nd Int. Conf. on Big Data, IoT and Machine Learning (BIM 2023), Lecture Notes in Networks and Systems, vol. 867, Springer, Singapore, 2024, pp. 809-823.
- A. M. Saad, U. N. Mahi, M. S. Salim, and S. I. Hossain, “Bangla news article dataset”, Data in Brief, vol. 2024, Art. no. 110874, ISSN 2352-3409. Available: https://doi.org/10.1016/j.dib.2024.110874 .
Area of Interests
- Quantum Machine Learning
- Quantum Error Correction
- Explainable AI
- Human Computer Interaction
- Computer Vision
- Medical Imaging
Certification
- Online graduate 6 ECTS credits QCourse551-1 by completing Implementing a “Hybrid Network to classify the MNIST Dataset” under the mentorship of Tal Michaeli from Classiq.
Award & Prizes
- Dean’s Award (2019-2020)
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