~/portfolio$whoami

Adeel Asghar

|

// Building AI Solutions with Code, Curiosity, and Data

Adeel Asghar

// 01. about

About Me

I'm an aspiring AI engineer who turns messy, real-world data into systems that actually work — from raw datasets to deployed, production-ready applications. I think in pipelines: what's the problem, what does the data look like, what's the right model, how does it ship. Currently in my 3rd year at COMSATS University Islamabad (CGPA 3.83/4.00), I've built across computer vision, data science, and cybersecurity — not as coursework, but as real problems worth solving. Certified by DeepLearning.AI, Harvard, and IBM. Interested in research opportunities and applied AI/ML roles — if you're working on a hard problem, I'd like to hear about it.

$ research --interests

Efficient deep learning for resource-constrained environments
AI security — adversarial robustness and autonomous red-teaming
Computer vision for accessibility and human-AI interaction

$ education --details

Degree:BS Artificial Intelligence
University:COMSATS University Islamabad, Wah Campus
Semester:6th Semester
CGPA:3.83 / 4.00

$ achievements --list

Academic Excellence Award

COMSATS University Wah Campus

1st Place — CS Quiz Competition

UET Taxila

1st Place — Speed Programming Competition

HITEC University

Top 4 of 80+ — Tech Quiz Competition

Tech Fest COMSATS Islamabad

MIT Hackathon Participant

Massachusetts Institute of Technology

$ gdg --role

Tech Lead & Founding Member

GDG On Campus — COMSATS Wah

Organizing AI/ML and Data Science workshops, fostering a community of tech enthusiasts on campus.


// 02. skills

Tech Stack

💻

Languages

PythonC++JavaSQLPHP
🤖

AI / Machine Learning

Supervised LearningUnsupervised LearningTransfer LearningFine-tuningFeature EngineeringModel EvaluationScikit-learn
🧠

Deep Learning

TensorFlowKerasCNNMobileNetV2Neural NetworksMediaPipe
📊

Data Science

PandasNumPyMatplotlibEDAETL PipelinesTableauPower BISPSS
🌐

Web & Databases

HTMLCSSJavaScriptPHPLaravelBootstrapSQLDatabase DesignOracle DBOracle APEX
⚙️

MLOps / DevOps

GitGitHubJenkinsDockerDocker SwarmCI/CD PipelinesBitbucket
🚀

Deployment & Tools

StreamlitFlaskJupyter NotebookVS Code

// 03. projects

Featured Projects

$ ./

BSL Hand Gesture Recognition

Deep learning system classifying 34 British Sign Language gestures with 95.74% accuracy and 95.78% F1-score. Uses MobileNetV2 transfer learning with CLAHE normalisation and MediaPipe hand landmark preprocessing. Trained on 34,000 balanced images and deployed as a live Streamlit web app.

💡 Key Insight

CLAHE normalisation on the LAB L-channel alone outperformed standard RGB preprocessing — preprocessing quality mattered more than model complexity at this scale.

PythonTensorFlowMobileNetV2Transfer LearningMediaPipeStreamlitComputer Vision
$ ./

Smart Recycle System

Industrial waste classifier using MobileNetV2 transfer learning achieving 86%+ accuracy across 12 material categories — outperforming a custom CNN baseline by 25%. Features real-time hazardous waste flagging with an efficient inference pipeline for industrial constraints.

💡 Key Insight

MobileNetV2 with fine-tuning outperformed a custom CNN baseline by 25% on the same dataset — transfer learning wins when data is limited and classes are visually similar.

PythonTensorFlowMobileNetV2Transfer LearningStreamlitComputer Vision
$ ./

Retail Sales Analytics Dashboard

End-to-end ETL pipeline processing 500,000+ transaction records for a UK-based online retailer. Identified seasonal revenue spikes, top-performing product categories, and high-value customer segments through in-depth EDA. Visualised with interactive Tableau dashboards for business intelligence decisions.

💡 Key Insight

500K+ transaction records revealed that 80% of revenue came from just 3 product categories — classic Pareto, but only visible after cleaning 40% missing/duplicate records in the ETL stage.

PythonPandasEDAETLTableauData Science
$ ./

AutoRedBlue (FYP)

🚧 In Progress

Final Year Project (In Progress) — an autonomous LLM-powered red/blue teaming platform for cybersecurity. Simulates attacker and defender agents to autonomously identify vulnerabilities and generate patches in real time. Currently in early development.

💡 Key Insight

Most red-team tools are manual and reactive. The core hypothesis: LLM agents can simulate both attacker and defender roles simultaneously, closing the feedback loop autonomously.

PythonLLMsCybersecurityAI AgentsRed Teaming

// other projects

$ ./

AI/ML Model Advisor

Rule-based expert system with custom forward and backward chaining inference engines that recommends optimal ML algorithms based on dataset characteristics. Includes explainability support and a lightweight Flask web interface for interactive user queries.

PythonFlaskSymPyExpert SystemsAIKnowledge Representation
$ ./

Indian Air Pollution Analysis

Analyzed historical air quality data (2015–2020) across 26 major Indian cities. Built an automated data pipeline with robust preprocessing, compared 4 regression models with hyperparameter tuning to forecast PM2.5 levels, and deployed an interactive Streamlit prediction dashboard.

PythonScikit-learnPandasRandom ForestStreamlitEDA
$ ./

Encrypted Monitoring App

Python application that periodically captures desktop screenshots, encrypts them using AES or DES, generates SHA-256 integrity hashes, and securely logs all data. Supports full decryption and hash verification.

PythonAESDESSHA-256CryptographySecurity
$ ./

Smart Farm Security System

Custom CNN built from scratch to classify 10 farm animal species and flag potential intruder threats from live image analysis. Trained on 28,000 images from the Animals-10 dataset and deployed via Streamlit for real-time inference.

PythonTensorFlowKerasCNNStreamlitComputer Vision
$ ./

CIFAR-10 Classical ML Classifier

CPU-efficient classical ML approach to CIFAR-10 using Histogram of Oriented Gradients (HOG) for feature extraction and SVMs for classification. Lightweight, interpretable, and runs without GPU.

PythonScikit-learnSVMHOGMachine Learning
$ ./

Bring It Buddy

🧪 Prototype

Prototype — a Laravel-based peer-to-peer delivery web app connecting senders with travellers going the same route for cost-effective package delivery.

PHPLaravelMySQLWeb Development

// 04. experience

Work Experience

My professional journey building AI systems and leading technical communities.

100+

Students Mentored

2+

Years Building

Tech Lead & Founding Member

CURRENT

GDG On Campus — COMSATS Wah

Oct 2024 – Present · Community Leadership

  • Co-founded the Google Developer Groups chapter at COMSATS University Wah Campus — one of the first student-led tech communities at the university
  • Leads AI/Data Science initiatives and coordinates student project teams across multiple domains
  • Organizes technical workshops, seminars, and hands-on sessions for 100+ students
  • Mentors junior members in AI/ML fundamentals and drives cross-team collaboration

DevOps & AI Intern

SPS — Software Productivity Strategists

Jul 2025 – Sep 2025 · Internship

  • Built and deployed CI/CD pipelines using Jenkins covering build triggers, notifications, and automated testing
  • Worked with Docker and Docker Swarm for containerization and service orchestration
  • Used Git, Bitbucket, and branching strategies for version control and team collaboration

// 05. certifications

Certifications

Verified credentials from world-class institutions.

$ issuers --summary

DeepLearning.AI3 certificates
IBM1 certificate
Coursera1 certificate
LearnKartS1 certificate
Harvard University1 certificate

DeepLearning.AI

Machine Learning Specialization

Sep 2025

ID: 5TSYTOKNM8WK

DeepLearning.AI

Advanced Learning Algorithms

Aug 2025

ID: CC6G4J9FCJ9Q

DeepLearning.AI

Supervised ML: Regression and Classification

Jul 2025

ID: 6IBGFBNW631T

IBM

Data Analysis with Python

Sep 2025

Coursera

Python for Data Analysis: Pandas & NumPy

Jul 2025

ID: OQ72QO3FEQBX

LearnKartS

Git with GitLab & Bitbucket

Jul 2025

ID: EG8AW0B5MDYC

Harvard University

Introduction to Programming with Python (CS50P)

Aug 2024

ID: c5546069-3e7c-480e-9d0c-e70b549fe065


// 06. contact

Let's Work
Together.

Open to freelance AI/ML projects, remote roles, and research collaborations. If you're working on a hard problem, I'd like to hear about it.

$ send --message