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AI Engineer with less than a year in Data Science & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Motivated Data Science graduate student pursuing an MS in Data Science, seeking an internship in Data Science, Computer Vision, AI, or Machine Learning. Strong foundation in Python, SQL, Machine Learning, Deep Learning, NLP, and Explainable AI (XAI). Hands-on experience in data preprocessing, model development, visualization, and building interpretable ML solutions. Eager to apply academic knowledge to real-world analytics and AI workflows while growing professionally.
University of Lahore
MS · Data Science
February 1, 2025 – Present
University of Education, Lahore
BS · Information Technology
November 1, 2020 – May 1, 2024
Early Detection and Risk Prediction of Heart Hypokinesia
January 1, 2025 – Present
Built a 3D CNN pipeline using CAMUS and EchoNet-Dynamics echocardiography videos to detect hypokinesia and predict cardiovascular risk from temporal cardiac motion patterns.
Invoice Parsing with LayoutLMv3
January 1, 2025 – Present
Deployed a document intelligence pipeline using LayoutLMv3 to parse invoices and generate structured outputs for finance workflows.
Sales Performance Dashboard (Power BI)
January 1, 2025 – Present
Designed interactive Power BI dashboards with automated SQL-based ETL pipelines, improving reporting efficiency and decision-making speed by 50%.
Facial Emotion Recognition (Computer Vision)
January 1, 2025 – Present
Built a CNN-based facial emotion recognition system using the FER2013 dataset. Evaluated robustness under varying lighting conditions and facial expressions.
Explainable AI on E-SNLI Dataset (NLP + ΧΑΙ)
January 1, 2025 – Present
Built a DeBERTa-v3 model on the E-SNLI dataset and applied explainability techniques to measure word-level importance and prediction confidence. Evaluated faithfulness of explanations using attention-based and attribution methods.
Safe City Emergency Response System
January 1, 2025 – Present
Fine-tuned YOLOv11 on Kaggle and ModelScope datasets to detect anomalies such as smoke, accidents, and fires. Integrated Twilio for automated emergency calls and Freshdesk for ticket creation, simulating AI-powered customer support agent workflows.
IMDB Movie Rating Analysis (Sentiment Analysis)
January 1, 2025 – Present
Performed NLP-based sentiment analysis on IMDB reviews using TF-IDF and embedding-based features to predict movie ratings. Compared classical ML and deep learning approaches.
Flower Classification using Deep Learning (CNN)
January 1, 2025 – Present
Developed a multi-class CNN using transfer learning (VGG16, ResNet) for flower classification. Applied Grad-CAM to visualize class-discriminative regions and explain model decisions.
Cultural Fit Analysis
The candidate's project portfolio shows a strong interest in diverse AI applications, from NLP and computer vision to explainable AI and document intelligence. This breadth of interest aligns well with an innovative and research-oriented culture. The academic focus suggests a drive for continuous learning and skill development. However, the absence of team-based professional projects makes it difficult to assess collaboration and adaptability in a corporate cultural context.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to learning and applying advanced AI techniques. The academic nature of most projects suggests a strong theoretical understanding and problem-solving ability within structured environments. However, the lack of professional experience means operational fit in a fast-paced industry setting, including collaboration, project management, and handling real-world constraints, is yet to be fully demonstrated.