Syed Musa Ali Kazmi
NUST
· 2025
Email
musalikazmi@gmail.com
Phone
923321759639
LinkedIn
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GitHub
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Academic
Program
BS in Computer Science
CGPA
3.47
Year
2025
Education
School of Electrical Engineering and Computer Science
Address
Gujranwala , Pakistan
DOB
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Career
Current role
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Target role
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Skills
Game designing on unity, Convolutional neural networks, Recurrent neural networks, Computer vision, Data science, Risk management, Python, keras, Docker, Multi tasking, Group work, Communication oral/written, Communication skill
Interests / quote
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Verbatim text
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Details Technical Skills Soft Skills Reference Syed Musa Ali Kazmi Cell: 923321759639 Email: musalikazmi@gmail.com Address: PHASE 2 HOUSE NO 376 GUJRANWALA CANTT Gujranwala , Pakistan Game designing on unity Convolutional neural networks Recurrent neural networks Computer vision Data science Risk management Python, keras Docker Multi tasking Group work Communication oral/written Communication skill To be furnished upon request. Professional Profile Please update objective section. Education BS in Computer Science School of Electrical Engineering and Computer Science , 3.47 Matric / O levels , (2019) Intermediate / A levels , (2021) BS CS National University of Sciences and Technology , 3.47/4 (2025) Internship Experience Mindstorm Studios ( 01-Jun-2023 - 31-Aug-2023 ) Unity Developer EMRchains ( 15-Mar-2024 - 15-May-2024 ) Machine Learning Engineer Projects Semantic segmentation of Slums using Semi-Supervised learning Page No. 82 | BSCS - Graduate Profile Booklet 2025 Page No. 83 | BSCS - Graduate Profile Booklet 2025
AI enrichment
Syed Musa Ali Kazmi is a recent BS Computer Science graduate from NUST with a 3.47 CGPA and internship experience as a Unity Developer and Machine Learning Engineer. His technical background includes proficiency in Python, Keras, Docker, and computer vision, with a focus on game design and neural networks.
Skills (AI)
["Unity", "Python", "Keras", "Docker", "Computer Vision", "Convolutional Neural Networks", "Recurrent Neural Networks", "Data Science", "Semantic Segmentation", "Semi-Supervised Learning"]
Status: ai_done