- Designed and developed an end-to-end food recommendation system using unsupervised association rule mining and deployed using FastAPI.- Developed a therapy notes generator using LLMs (Whisper & GPT) and deployed as a backend service on AWS EC2 that reduced notes generation time by ~60%.- Developed a treatment planner system that leveraged ChatGPT API and reduced therapists time for writing customized treatment plans for psychological health.- Developed a Chatbot for question answering for multiple websites and PDF documents using LangChain and Llama-index (Used GPT-4, BERT, LongFormer for generating answers)- Developed an end-to-end query classification pipeline. Collected data from various resources, used Open Source LMs (T5) for generating synthetic data and used Logistic Regression, SVM and BERT for query classification, deployed the model using FastAPI. This resulted in reduced cloud costs upto ~45%.- Developed a video subtitle generation pipeline using OpenAI's Whisper and deployed as a custom software solution.- Developed a DotNet and Angular project generator that provides basic boilerplate code based on input MySQL tables.- Developed an insect classification model and deployed on Azure using Container Registry and App service.- Developed multiple APIs in FastAPI for object recognition and text classification.- Working with backend developers to deploy and integrate ML models with existing systems in production.

- Taught undergraduate AI courses and conducted practical labs.- Delivered practical lectures on Machine Learning and Deep Learning.- Assisted the senior faculty in designing course contents and writing proposals for research grants.- Helped and guided final-year students in their ML based FYPs.- Worked on researching the latest AI technologies to solve real-world problems.Achievements:------ A research proposal entitled "Tea disease detection using Machine Learning and Remote Sensing" that I wrote won a grant of PKR 3.5 Million from Higher Education Commission's National Research Program for Universities.- Published a journal paper entitled "Detection and Classification of Malignant Melanoma Using Deep Features of NASNet"

- Worked on weed detection projects using YOLOv5 algorithm- Developed a medical speech recognition system by fine‑tuning an Nvidia QuartzNet model via NeMo library- Worked on AWS S3 and MLFlow platform for deployment and maintenance of deep learning models.- Worked on researching various methods for converting deep learning models to work with different ML libraries.

Worked on Melanoma Diagnosis in Bioinformatics Research Lab at KICS UET Lahore where I used Computer-Based Diagnosis (Deep Learning and Computer Vision) to detect and classify a rare type of skin cancer. Two research papers has been published from the outcomes of this research. Some of my projects during my research work are:1. Intelligent crop disease detection system using deep transfer learning2. Leveraging deep learning algorithms for steel defect classification3. An automated detection system for melanoma in dermoscopic images using deep ConvNets.4. Developed a simple program to download the images dataset from YouTube videos which has more than 10 stars on github

Assisted in design and development of a Video Analytics System for cars at parking station which stores information related to cars, where it was parked, it's number plate and will inform user whether the specific place is available for parking or not. My responsibilities were to:1. Research and develop best vehicle registration plate segmentation model.2. Develop a large dataset from videos and annotation of images dataset3. Training, Testing and evaluation of deep learning model (Mask R-CNN) using test dataset4. Research Python code optimization techniques5. Developed a small website using HTML, CSS and Bootstrap.

Served as a lecturer in Computer Science department. I conducted practical labs and taught following courses to undergraduate (B.S and BSc.) students1. Introduction to Computer Programming (C, Python)2. Operating Systems Basics3. Computer Networks4. Database Systems Fundamentals5. Introduction to Computers and Information Technology

Worked as a Computer Vision and Deep Learning Intern. I worked on following project1. Learnt the basics of ANNs, CNNs and deep learning2. Developed small CNNs for object recognition3. Developed GUIs for Object Recognition models deployment (HTML/CSS/Bootstrap)