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Muhammad Hissan Umar

NUST · 2026 · 411644
Email
mumar.bese22seecs@seecs.edu.pk
Phone
923004499554
LinkedIn
https://www.linkedin.com/in/hissan-umar-68028a228
GitHub

Academic

Program
CGPA
2.96
Year
2026
Education
Bachelors in Software Engineering School of Electrical Engineering and Computer Sciences , Islamabad , 3.03 (2026)
Address
301/A NISHTER BLOCK IQBAL TOWN LAHORE , Lahore , Pakistan
DOB

Career

Current role
Target role
Skills
PROFESSIONAL PROFILE Final-year Computer Science student and Software Engineer experienced in full-stack development, backend services, and applied machine learning. Proficient in building scalable web applications using modern frameworks, implementing REST APIs, and integrating ML/DL models into production environments. Passionate about solving real problems through software and data-driven systems EDUCATION Bachelors in Software Engineering School of Electrical Engineering and Computer Sciences , Islamabad , 3.03 (2026) INTERNSHIP EXPERIENCE Machine Learning and Intelligent Systems, Nust (MACHVIS) 17-Jun-2025 - 21-Aug-2025 Working on remote sensing projects for a real time dashboard for the currently growing crops along with analysis to provide 35% better insights for agricultural practices. This project uses ML analysis, along with Deep Learning CNN for yield prediction and LLMs for explainability. The project also focuses on creating a mutable pipeline for constant model improvements. It is already deployed on GitHub. TUKL Deep Learning Lab 03-Jun-2024 - 30-Aug-2024 Improved Machine Learning and Deep Learning skills while building a CV recommendation system for firms using LLM agents. The system leverages instruction-set manipulation to optimize LLM behavior and produce more accurate candidate recommendations, making the hiring process significantly more efficient for medium-scale recruitment. FINAL YEAR PROJECT UAV Based Remote Sensing for Wheat Yield Prediction I conducted a UAV-based remote sensing research project utilizing multispectral imagery to analyze crop growth and yield prediction. The study combined vegetation indices, canopy traits, and genotype-aware modeling with machine learning and deep learning approaches. The outcomes of this work were compiled into a structured research paper, which I successfully submitted for publication. TECHNICAL EXPERTISE Machine Learning Engineer Machine Learning Engineer experienced in designing, developing, and deploying ML models to solve real-world problems. Skilled in data preprocessing, model training, evaluation, and scaling production-ready ML systems. Strong foundation in algorithms, statistics, deep learning, and software engineering, with h ... Full Stack Development Full-stack developer specializing in Next.js for building server-rendered and client-rendered web applications. Experienced in developing RESTful APIs, integrating databases, and implementing server-side logic for end-to-end features. Strong understanding of React architecture, routing, authentication, and pe ...

AI enrichment

Final-year Computer Science student and Software Engineer experienced in full-stack development, backend services, and applied machine learning. Proficient in building scalable web applications using modern frameworks, implementing REST APIs, and integrating ML/DL models into production environments. Passionate about solving real problems through software and data-driven systems
Status: ai_done
Provenance
Source file:
Created: 1777448793