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Wadood Ur Rehman Ranjha

NUST · 2026

wadood2003@gmail.com

Phone

923330540123

https://www.linkedin.com/in/wadood-ranjha/

GitHub

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Academic

Program

BS Computer Science

CGPA

3.45

Year

2026

Education

SEECS

Address

SDH-365, Gulberg 3, PAF Falcon Complex , Islamabad , Pakistan

DOB

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Career

Current role

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Target role

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Skills

Machine Learning, AI, PyTorch, Tensorflow, Deep Learning, Full Stack Development, Python, Rust, Node.JS, Data Engineering, Optical Fiber Networks, Anomaly Detection, Autoencoder, Focal Loss, Weighted Sampling, Quantum Kernel Interface, SVM, Multimodal Stock Price Forecasting, NLP, Financial Sentiment Analysis

Verbatim text

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Wadood Ur Rehman Ranjha
Cell: 923330540123 |  Email: wadood2003@gmail.com
LinkedIn: https://www.linkedin.com/in/wadood-ranjha/
Address: SDH-365, Gulberg 3, PAF Falcon Complex , Islamabad , Pakistan
PROFESSIONAL PROFILE
Computer Science undergraduate with Machine Learning experience at Fortis Capital, ONT Lab, Chalmers
University and CETQAP, along with a project portfolio featuring multimodal stock price forecasting, land
classification based GDP prediction, NLP powered financial sentiment analysis, full stack application
development and more. 
EDUCATION
BS Computer Science
SEECS , Islamabad , 3.45 (2026)
INTERNSHIP EXPERIENCE
ONT Lab SEECS
01-Jun-2025 - 12-Sep-2025
Developing Deep Learning models for automated anomaly detection, identiﬁcation, and localization in Optical Fiber networks, later
used in a research paper. Implemented unsupervised pretraining (autoencoder) to handle label scarcity, added class-imbalance
handling (focal loss, weighted sampling). Configured data pipelines with synthetic data augmentation
CETQAP
01-Jun-2024 - 15-Aug-2024
Implemented, veriﬁed, and contributed to multiple research paper results and conclusions; developed a quantum kernel interface for
SVM classification.
Chalmers University, Optical Networks Department
15-Sep-2025 - 15-Jan-2026
Co-authored two submitted papers on the application of machine learning in Optical Fiber Networks, publish decision pending.
Developed ML models for extensive novel Optical Fiber datasets, achieving accuracy over 95% for multiple projects.
FINAL YEAR PROJECT
Fortis Aegis
Fortis Aegis is an AI-powered portfolio advisory platform that uses advanced Machine Learning algorithms to provide multimodal data
based advice for investment decisions in stocks, options, and cryptocurrency, along with quantitative analysis of user portfolios.
TECHNICAL EXPERTISE
Machine Learning & AI
Extensive Machine Learning experience developing vision and temporal models with PyTorch and Tensorﬂow. Completed Deep
Learning Specialization certificate.
Full Stack Development
Experienced in Full Stack Development, including projects in Python, Rust, and Node.JS.
Data Engineering

AI enrichment

Wadood Ur Rehman Ranjha is a BS Computer Science undergraduate with a 3.45 CGPA and extensive internship experience in machine learning and deep learning at institutions like ONT Lab and Chalmers University. He has contributed to research papers and developed ML models for optical fiber networks and financial applications using PyTorch and TensorFlow.

Skills (AI)

["Machine Learning", "Deep Learning", "PyTorch", "TensorFlow", "Python", "Rust", "Node.js", "Full Stack Development", "Data Engineering", "Optical Fiber Networks", "Anomaly Detection", "NLP", "Quantum Computing"]

Status: ai_done

Provenance

Source file: SEECS - Computer Science-2026.pdf
From job #258 page 139
Created: 1778167261