About
I'm Gul Hassan
I am a fresh graduate of Information Technology on merit-based scholersip. As an AI enthusiast, it's quite fascinating to solve
real-world problems using Machine Learning and Deep Learing for good.
Driven by this passion for applying Machine Learning and Deep Learning to solve real-world problems.
I've honed my skills through personal projects, LeetCode challenges, and technical article writing.
My active participation in international hackathons (3 awards) showcases my strong leadership,
communication, and teamwork ability, my experience as a Data Analyst on Fiverr further strengthens my
practical data analysis expertise.
Technical Skills, Tools, & Programming
Skills: Data analysis, Machine learning, Deep learning, Natural Language processing, Data structures and algorithms.Programming languages: Python, Flask, C++, Javascript, PHP.
Tools: Google spreadsheets, Git and Github, VS code, Google Colab, Anaconda.
Operating system: Ubuntu, Kali Linux, Windows.
Achievements
FYP (2nd Place)
- Achieved #2 Ranking in final year project (FYP) in 100+ participants, 30+ FYP’s.
Note! check details of FYP below in projects section.
Finalist (2 place)
- Analyzed disaster data (floods, tornadoes, landslides) using Numpy, Pandas, Matplotlib, and Seaborn, leveraging Google Sheets for data management.
- Created impactful reports revealing trends and the human cost of disasters, highlighting the number of people severely and partially affected.
Finalist (3rd place)
- Employed data pre-processing techniques like feature engineering, data imputation, and text preprocessing.
- Trained the ML model on historical race data to predict race outcomes based on weather, track characteristics, and past performance.
RunnerUp
- Leveraged Machine Learning skills and created a model that can take food names, have a fridge at home or not, season, food type, food quantity, and number of people, and predict whether food will be wasted or consumed properly.
- Evaluated model performance using F1 score, Cohen's Kappa, and confusion matrix to provide a detailed analysis of classification effectiveness and error distribution.
Regional Ambassador
- Competed against 250+ applicants and secured a position in the top 20 ambassadors with Hackmaker.
- Consistently ranked among the top 3 of 20 regional ambassadors, surpassing MoU signing targets by 99%.
- Secured 6+ strategic partnerships between Hackmakers, universities, student groups, and companies.
Scholerships
- Secured merit-based scholarship by HEC
- Awarded a laptop as part of the PM's Scheme for ranking in the top 20 of the batch.
Projects
Bird's voice classification
- Preprocessed audio with librosa to generate mel spectrograms and extract features for deep learning.
- Developed a deep CNN using TensorFlow for multi-class image classification, incorporating six convolutional layers with filters ranging from 16 to 1024.
- Achieved 80% accuracy on test data, evaluated model performance using F1 score, precision, recall, and confusion matrix.
- Built a Flask web interface with HTML/CSS for user interaction with the classification model.
Sentiment-Analysis
- The model predicts sentiment by analyzing linguistic patterns, emotional cues, and contextual features within the text.
- Developed NLP pipeline using NLTK to optimize text preprocessing and sentiment classification workflows.
- Utilized TF-IDF vectorizer for feature extraction and implemented an SVM model.
- Selected Support Vector Machine (SVM) from five machine learning algorithms due to its superior performance, achieving an accuracy of 0.89, with precision, recall, and F1-scores of 0.89.
- Created a Streamlit interface for real-time sentiment analysis and deployment.
Handwritten digit classification
- Preprocessed the MNIST dataset through normalization and resizing to enhance data quality and model performance.
- Developed and serialized a Support Vector Machine (SVM) classifier for digit recognition, employing robust techniques to optimize accuracy.
- Achieved 97.77% accuracy with an SVM classifier on validation data and 97.82% accuracy on test data, with detailed confusion matrices demonstrating high classification performance across digit categories.
- Designed and deployed a Streamlit interface for the model, hosting the application on Hugging Face for accessible and interactive digit recognition.
Education
BS Information Technology
GPA 3.35
Core courses: Computer Vision, Data Science, Discrete Mathematics, Statistics, Linear Algebra, Calculus, DSA, Python, C++, Java, Web development, Android app development, and software engineering.
Higher Secondary School
Pre-medical
Experience
Section Leader in Code in Place
- Chosen from 2,000+ global applicants to mentor 20,000+ learners in Python programming for Stanford’s largest-ever cohort.
- Will lead technical discussions on algorithms, debugging, and OOP, collaborating with a teaching team spanning 87 countries.
- Joining a diverse, international team to standardize coding pedagogy and troubleshoot technical challenges.
- Contributing to remote learning strategies for large cohorts under Stanford faculty guidance.
Regional Ambassador
- Partnerships were secured through MoUs with over 2 universities, 2 student clubs/organizations, and 2 companies.
- Collaboration and growth were fostered within the Hackmakers community in Pakistan through strategic partnerships.
Data Analyst
- Partnered with international clients on over 2 analytical projects, providing data-driven insights and solutions.
- Developed and maintained interactive dashboards using Google Sheets and Data Studio to track key performance metrics.
- Delivered comprehensive reports that identified trends, supported decision-making, and improved business outcomes.
Moderator and Trainer
- Taught 4+ courses on data analysis using Google spreadsheets, Data Analysis1, and Data Analysis2.
- Instructed in a 5-week long IELTS course.
- Designed and conducted a comprehensive Python course, covering fundamentals to intermediate levels and incorporating problem-solving techniques from LeetCode.
- Conducted workshops on Python, Data Analysis, VS Code, Git, and GitHub at iCodeGuru.
- Managed workshops as a lead, covering areas like Data Structures and Algorithms, Computer Vision, Machine Learning, Data Manipulation, Data Analysis, and iCodeGuru and the University of Sindh.