Mobeen Ahmad
Research Scientist at Pyler
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolMobeen Ahmad is a research scientist based in Seoul with 8 years of hands-on experience in deep learning, AutoML, and neural architecture search, focused on computer vision problems like object detection, heterogeneous face recognition, and small object detection. He holds a PhD in Deep Learning from Sejong University and a strong academic foundation with an MSc in Robotics and Intelligent Machine Engineering (GPA 3.8/4.0) and a BEng in Electrical/Computer Engineering. At Pyler he contributes as an ML researcher, bridging algorithmic innovation with practical image-processing systems for real-world deployment. His work blends automated model search and algorithm design, enabling robust performance on challenging visual tasks where data heterogeneity and tiny targets are key obstacles. Known for translating research prototypes into reproducible solutions, he brings both theoretical depth and applied engineering rigor to ML projects.
8 years of coding experience
Doctor of Philosophy (PhD), Deep Learning, Doctor of Philosophy (PhD), Deep Learning at Sejong UniversityBachelor’s Degree, Electrical (Computer) Engineering, Bachelor’s Degree, Electrical (Computer) Engineering at COMSATS Institute of Information and TechnologyMaster’s Degree, Robotics and Intelligent Machine Engineering, 3.8/4.00, Master’s Degree, Robotics and Intelligent Machine Engineering, 3.8/4.00 at National University of Sciences and Technology (NUST)
English, German, Korean, Urdu, Punjabi
Github Skills (47)
visual-question-answering8
genetic7
sequence6
counter5
prompt-tuning5
genetic-algorithm5
pytorch4
face4
machine-learning-models4
machine-learning4
multimodal4
visual-recognition4
transfer-learning4
matlab4
efficientnet4
Programming languages (4)
Github contributions (5)
ahmadmobeen/SyntheticDisguiseFaceDatabase
Nov 2021 - May 2022
Contributions:9 commits, 8 pushes, 1 branch in 6 months
ahmadmobeen/gentun
Mar 2020 - May 2020
Hyperparameter tuning for machine learning models using a distributed genetic algorithm
Contributions:35 commits, 2 PRs, 13 pushes in 1 month
hyperparametergeneticmachine-learningdistributed-genetic-algorithmgenetic-algorithm
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