class ComputerScientist:
def __init__(self):
self.name = "Abu Bakar"
self.role = "Machine Learning & Software Engineer"
self.language_spoken = ["en_US", "ur_PK"]
self.current_focus = ["Machine Learning", "Generative AI", "Distributed Systems", "Cybersecurity"]
self.experience = [
# Machine Learning & NLP
"NLP", "Urdu Sentiment & Emotion Analysis", "Large Language Models",
"Transformers", "Neural Networks", "Random Forests", "Transfer Learning",
"Classification", "Regression", "Clustering", "Prompt Engineering",
# Parallel & Distributed Systems
"Parallel Computing", "Distributed Socket Systems", "Multi-user Systems",
# Cybersecurity & Cryptography
"Log Analysis", "Threat Detection", "RSA Cryptography",
"Digital Signatures", "SHA-256 Hashing", "Defensive Operations",
# Data Science & Analysis
"Exploratory Data Analysis", "Data Preprocessing", "Statistical Analysis",
"Data Visualization", "Feature Engineering", "Time Series Analysis",
# Web Application Development
"Full-Stack Development", "Real-time Messaging", "Cloud Deployment"
]
def say_hi(self):
print("Thanks for dropping by! Let's build secure, intelligent systems together!")
me = ComputerScientist()
me.say_hi()-
BS Computer Science @ Namal University Mianwali
- Actively studying Software Engineering, AI/ML/NLP and Web Application Development.
- Applying academic theory directly to robust open-source projects.
-
Advanced NLP & Deep Learning Research
- Fine-tuning models for sentiment and emotion classification on noisy Urdu tweets.
- Working on next-generation text and representation learning projects.
-
Intelligent Distributed & Cloud Systems
- Building multi-user secure remote access architectures and cloud-deployed full-stack projects.
- Exploring real-time style intelligence with BarberAI.
|
Jupyter Notebook, Python, NLP, Deep Learning — An advanced NLP semester project designed to classify emotion and sentiment in highly noisy Urdu tweets using tokenizers and custom fine-tuned architectures. |
TypeScript, Node.js, AI, Full-Stack — An innovative AISeekho platform providing intelligent styling and interactive visualization, featuring a responsive TypeScript interface. |
|
Python, Information Security, Regex — Automated defensive operations tool built for CS-332 Information Security. Parses network, auth, and system logs in real-time to detect Blue Team threat anomalies. |
Python, Sockets, Parallel Computing — Parallel and distributed computing project letting multiple remote clients securely connect to, execute commands on, and stream output from a single host machine. |
|
Python, Streamlit, sklearn, Pandas — High-accuracy machine learning model (97.96% accuracy) that predicts employee turnover patterns and delivers actionable retention insights for HR. |
React, Node.js, Firebase, Azure — Scalable, real-time messaging and file-sharing app built as a semester project for CS-371 Cloud Computing, featuring secure channels and cloud storage. |
gantt
title Abu Bakar's Learning & Tech Journey
dateFormat YYYY-MM-DD
section Education & Experience
100 Days of Bytewise Fellowship :a1, 2024-07-01, 100d
GDGoC FAST Peshawar ML Fellowship :a2, 2024-08-01, 120d
Python Internship @ CodeX Computing :a3, 2024-09-01, 90d
BS CS @ Namal University (Ongoing) :active, a4, 2023-09-15, 2027-06-15
section Core Projects
Customer Churn & Attrition Predictors :2024-09-15, 60d
Tweet Virality Predictor (NLP) :2024-11-01, 21d
Python Log Analyzer (Security) :2025-05-27, 22d
Real-time Cloud Chat App (React/Azure) :2025-06-18, 33d
Certea Cryptography & Digital Signatures :2025-12-21, 28d
Multi-User Remote Access System :2025-12-24, 31d
BarberAI & Urdu NLP Tweet Classifier :2026-04-02, 50d
