me

Using AI and machine learning expertise to create impactful solutions for human well-being.

In my journey as an AI Explorer, I traverse the intricate landscapes of artificial intelligence, guided by a profound understanding of data science and machine learning. With a passion for innovation, I dedicate myself to crafting impactful solutions that enhance the well-being of humanity. Armed with a curiosity-driven mindset, I delve into the complexities of AI, decoding patterns, and unraveling insights that contribute to the greater good. My commitment to pushing the boundaries of technology aligns with a broader mission—using advanced AI techniques to address real-world challenges and make a positive impact on the world we inhabit.

Work Experience

DATA SCIENCE AND ANALYSIS

DEEP LEARNING

DATABASE

SPARQL microsoft-access
Version Control & Virtualization

Data Scientist

TecHayal

November 2022 - March 2023

Remote

  • - Executed image recognition system for SEO, diminishing manual tagging by 30%.
  • - Utilized deep learning to amplify image categorization accuracy.
  • - Conducted model fine-tuning to refine tagging precision.

Data Scientist | Analyst

Freelance

October 2019 - November 2022

Remote

  • - Developed a machine learning model for predictive maintenance using IoT sensor data and Flask API for real-time monitoring.
  • - Developed time series models (ARIMA, SARIMA, Prophet) for sales prediction and inventory management with a user-friendly dashboard.
  • - Implemented sentiment analysis on social data using NLP, visualized trends, and provided actionable insights for marketing campaign adjustments.

Data Analyst

Auvitronics Limited

October 2019 - October 2021

Karachi, Pakistan

  • - Administered initiatives in demand analysis for data-driven decision-making.
  • - Monitored fiscal year growth and analyzed shipment trends for data-driven decision-making.
  • - Analyzed geographical data to optimize logistics routes, achieving a 10-15% reduction in transportation losses.

Education

FAU Erlangen-Nürnberg

Master of Science - MSc, Artificial intelligence

Grade: Grade 1.6

Courses:

  • Pattern Recognition and Analysis
  • Machine and Deep Learning
  • Explainable Machine Learning
  • Data Analysis and Visualization

NED University of Engineering

Bachelors - BE, Industrial and Manufacturing

Grade: Grade 3.907 (Equivalent German Grade 1.1)

Courses:

  • Manufacturing Processes
  • Machine Learning for Manufacturing
  • Data Analysis
  • Data Driven Processes Control

My Portfolio

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Real-time Facial Emotion Recognition Web Application

Our web app uses AI to analyze facial expressions in real time, helping users understand and categorize emotions instantly. Ideal for mental health, UX enhancement, and education.

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EDA on Tree Datasets in German Cities

Explore urban greenery through our EDA project on tree datasets from two major German cities. Dive into rich insights for a comprehensive understanding of the urban tree landscape.

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xML Framework: Decoding Neural Networks on Pokémon Dataset

Explore neural network intricacies with our eXplainable Machine Learning (xML) framework on Pokémon data. Enriched with data augmentation, this project expands 800 images into 60,000, offering transparent AI insights through visualization and interpretation tools. Uncover model intricacies for a deeper understanding of your models.

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YOLO v5 Object Detector Implementation

Successfully implemented a state-of-the-art YOLO v5-based object detection system, leveraging cutting-edge techniques for real-time and accurate identification of objects in images. This project showcases my expertise in computer vision and deep learning, ensuring optimal performance in object detection tasks.

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Customer Churn and Risk Analysis

Analyzed customer churn and risk factors, delivering actionable insights through dynamic visualizations for informed decision-making.

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Diversity & Inclusion in a Company

Implemented initiatives for fostering workplace diversity, leveraging data insights to enhance inclusion and strengthen organizational culture.

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Background-Informed Object Labeling for Semi-Supervised Detection

Innovative background separation and aspect ratio analysis drive this project's semi-supervised object detection. Distinguish humans and vehicles by extracting data from video frames, pushing the efficiency boundaries of detection methods.

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Brain tumor diagnosis using SIFT-DNN

This project is for diagnosis of brain tumor with a dataset of four classes using SIFT and Deep learning architecture

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KNN classification on Iris dataset

Explore KNN Classification on the Iris Dataset: Uncover the accuracy and versatility of the k-nearest neighbors (KNN) algorithm as it predicts iris flower characteristics. This project demonstrates the effectiveness of KNN in real-world scenarios through meticulous analysis and model training.

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Employee Recommender System

Unlock personalized career paths with the HR Recommender System, tailoring recommendations for employees based on their unique traits. Enhance workforce engagement and satisfaction through targeted professional development suggestions.

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Employee Performance Analysis

Uncover valuable insights in employee performance through analysis of environment satisfaction, social satisfaction, and job satisfaction. Predict and enhance workforce productivity with data-driven precision.

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Panorama Stitching

This project consists of a generalized Code implementation for SIFT, SURF and ORB descriptors for panorama image stitching

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Predictive Homesteads by Random Forest

This project centers on fundamental housing price predictions using the Random Forest approach.

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Titanic Voyage Insights

Discover "Titanic Voyage Insights," my exploratory data analysis (EDA) project unraveling key patterns within the Titanic dataset. Delve into a comprehensive analysis showcasing my skills in uncovering meaningful insights.

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Predictive Homesteads by DNN

This project revolves around foundational housing price predictions employing a deep learning neural network approach.

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