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Muhammad Umer Ali

NUST · 2026
Email
m.umer.ali.0987@gmail.com
Phone
923186856560
LinkedIn
https://www.linkedin.com/in/mumer-ali/
GitHub

Academic

Program
BSCS
CGPA
3.19
Year
2026
Education
SEECS
Address
Sadiqabad, Pakistan
DOB

Career

Current role
Target role
Skills
Machine Learning, Deep Learning, CNNs, RNNs, GANs, RAG, Transformers, Transfer Learning, Machine Unlearning, LLMs, Agentic AI, Python, JavaScript, TypeScript, Java, Kotlin, C#, C++, SQL
Interests / quote
Seeking opportunities to apply expertise in AI safety and computer vision to solve complex real-world problems.

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.
Muhammad Umer Ali
Cell: 923186856560 |  Email: m.umer.ali.0987@gmail.com
LinkedIn: https://www.linkedin.com/in/mumer-ali/
Address: House # 06 , Main Street , Ilyas Colony , Sadiqabad , Pakistan
PROFESSIONAL PROFILE
Final-year Computer Science student at NUST with a strong foundation in deep learning research. Passionate about Ethical AI, with
active research focused on Machine Unlearning. Experienced in building medical AI solutions, including neonatal pain assessment
and disease detection systems. Seeking opportunities to apply expertise in AI safety and computer vision to solve complex real-world problems.
EDUCATION
Bachelor of Science in Computer Science
School of Electrical Engineering & Computer Science , Islamabad , 3.19 (2026)
INTERNSHIP EXPERIENCE
KBS Lab
01-Sep-2024 - 30-Jun-2025
Researched machine unlearning techniques for privacy-preserving neural networks and transfer learning methods to improve
generalization across vision datasets.
Melior
01-Jun-2024 - 31-Aug-2024
Developed real-time emotion recognition models for marketing by integrating audio data streams to improve customer engagement
efficiency.
Ehsaas
01-Jun-2023 - 31-Aug-2023
Built a full-stack web platform connecting patients with attendants by featuring real-time updates and successfully reducing request
latency by 25%
FINAL YEAR PROJECT
PANDA: Pain Assessment in Neonates using Deep Learning and Analytics
PANDA is a research project that utilizes Deep Learning to assess pain levels in neonates due to their inability to communicate. The
project analyzes brain activity, EEG signals, to provide objective pain quantification, aiming to overcome the limitations of manual
observation in neonatal intensive care units.
TECHNICAL EXPERTISE
Machine Learning & Deep Learning
CNNs, RNNs, GANs, RAG, Transformers, Transfer Learning, Machine Unlearning, LLMs, Agentic AI.
Programming Languages
Python, JavaScript, TypeScript, Java, Kotlin, C#, C++, SQL.

AI enrichment

Muhammad Umer Ali is a final-year Computer Science student with a 3.19 CGPA, specializing in deep learning, machine unlearning, and computer vision. He has internship experience in AI research and full-stack development, with a focus on ethical AI and medical applications.
Skills (AI)
["Python", "JavaScript", "TypeScript", "Java", "Kotlin", "C#", "C++", "SQL", "Deep Learning", "Machine Learning", "CNNs", "RNNs", "GANs", "Transformers", "LLMs", "Machine Unlearning", "Computer Vision", "Full-Stack Development", "Agentic AI", "RAG"]
Status: ai_done
Provenance
Source file: SEECS - Computer Science-2026.pdf
From job #258 page 72
Created: 1778167261