Muhammad Saadan
NUST
· 2025
Email
msaadan.bese21seecs@seecs.edu.pk
Phone
923329297757
LinkedIn
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GitHub
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Academic
Program
BE Software Engineering
CGPA
3.38
Year
2025
Education
School of Electrical Engineering and Computer Science
Address
Islamabad , Pakistan
DOB
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Career
Current role
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Target role
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Skills
Convolutional neural networks, Recurrent neural networks, Specialization in python, Flask, Information security (infosec), Network troubleshooting, Tensorflow, keras, pytorch, Machine learning, Firewalls, IP subnetting, Optical Network and Technologies, Federated Learning, Transfer learning, Active learning, Knowledge distillation
Interests / quote
I am a Software Engineer with professional experience spanning both corporate and research domains. My expertise lies in bridging the gap between theoretical advancements and practical applications in AI, Deep Learning, and Federated Learning. With a strong background in research experimentation and implementation, I am passionate about addressing unsolved challenges through innovative ideas and approaches.
Verbatim text
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Muhammad Saadan Cell: 923329297757 Email: msaadan.bese21seecs@seecs.edu.pk Address: HOUSE NO 578/C-36, STREET NO 6, ALLAHABAD, 3,WESTRIDGE RAWALPINDI CANTT Islamabad , Pakistan Convolutional neural networks Recurrent neural networks Specialization in python Flask Information security (infosec) Network troubleshooting Tensorflow, keras, pytorch Machine learning Conflict management Communication and presentation Team management skills Effective leadership and manag Intuitive problem solving Time management To be furnished upon request. Professional Profile I am a Software Engineer with professional experience spanning both corporate and research domains. My expertise lies in bridging the gap between theoretical advancements and practical applications in AI, Deep Learning, and Federated Learning. With a strong background in research experimentation and implementation, I am passionate about addressing unsolved challenges through innovative ideas and approaches. Education BE Software Engineering School of Electrical Engineering and Computer Science , 3.38 Matric / O levels , (2019) Intermediate / A levels , (2021) Matric (Computer Science Group) Army Public School and College Westridge III , 95% (2019) FSC. Pre-Engineering Army Public School and College Westridge III , 96% (2021) Bachelors in Software Engineering School of Electrical Engineering and Computer Sciences (NUST-SEECS) , 3.32 (2025) Internship Experience National Database and Registration Authority NADRA (Network Security Intern) ( 10-Jul-2024 - 20-Aug-2024 ) Analyzed the network security posture on NADRA and presented a Network Access Control based solution. Worked with different network officers to understand the working of organization network communication inside and outside the organization. Gained hands-on deployment experience of Firewalls, IP subnettin Optical Network and Technologies Lab (Deep Learning Intern) ( 07-Jun-2024 - 05- Sep-2025 ) Analysed and compared more than 8 regression models to select the most appropriate one. Utilized the given dataset to predict the GSNR value minimizing the MSE loss up to 0.01 units. Enhanced the model prediction utilizing transfer, active, and federated learning along with knowledge distillation implement School of Electrical Engineering and Computer Science (Federated Learning Researcher) ( 09-Sep-2024 - 30-May-2025 ) Addressed privacy concerns in AI by proposing solution for challenges in federated deep learning based on extensive literature review. Constructed an end to end pipeline performing data loading and preprocessing followed by configuration and collaboration setup till model learning visualization and analysis
AI enrichment
Muhammad Saadan is a recent Software Engineering graduate with a 3.38 CGPA and internship experience in network security and deep learning research. He has practical exposure to AI frameworks like TensorFlow and PyTorch, as well as network troubleshooting and firewall deployment.
Skills (AI)
["Python", "Machine Learning", "Deep Learning", "TensorFlow", "Keras", "PyTorch", "Flask", "Convolutional Neural Networks", "Recurrent Neural Networks", "Information Security", "Network Troubleshooting", "Firewalls", "Federated Learning", "Transfer Learning", "Knowledge Distillation"]
Status: ai_done