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Schedule Interview NowMy name is Nausherwan M. and I have over 0 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Machine Learning Model, Deep Learning, Computer Vision, Natural Language Processing, etc.. I hold a degree in Master of Science (MS), Bachelor of Science (BS), High school degree. Some of the notable projects I've worked on include: Custom LLM-Powered System for Call Center Agent Evaluation, AI-Powered DXF File Generation for Laser Cutting, Image Annotations - Boreholes Dataset using OpenCV, Car Body Parts Detection with Instance Segmentation, PDF Parsing and Generation. I am based in Lahore, Pakistan. I've successfully completed 5 projects while developing at Softaims.
I possess comprehensive technical expertise across the entire solution lifecycle, from user interfaces and information management to system architecture and deployment pipelines. This end-to-end perspective allows me to build solutions that are harmonious and efficient across all functional layers.
I excel at managing technical health and ensuring that every component of the system adheres to the highest standards of performance and security. Working at Softaims, I ensure that integration is seamless and the overall architecture is sound and well-defined.
My commitment is to taking full ownership of project delivery, moving quickly and decisively to resolve issues and deliver high-quality features that meet or exceed the client's commercial objectives.
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CITY at LUMS
Built a full pipeline for evaluating call center agents using AI. Used Whisper for transcription and diarization, and a quantized Mistral 7B model via llama-cpp for KPI scoring. Integrated FAISS for R
Developed an AI system to automate DXF file creation from user-uploaded images for industrial laser cutting. Used contour detection with a 0.5-inch reference marker for scale accuracy. Enabled adjusta
Developed a computer vision pipeline using Python, OpenCV, PIL, and NumPy to detect and annotate core loss in borehole strip images. Images were divided into 100 segments, with pixel-level white space
Annotated 25 distinct car body parts (e.g., bumper, hood, headlights) using Roboflow with instance segmentation. Trained a YOLOv11 model to detect and classify parts, especially in accident-damaged ve
Developed a custom pipeline to extract geotechnical data from unstructured PDFs and convert it into clean, structured JSON using Python, OpenCV, and OCR techniques. Parsed both digital and scanned fil
Master of Science (MS) in Artificial Intelligence
2024-01-01-2026-01-01
Bachelor of Science (BS) in Electrical engineering
2020-01-01-2024-01-01
High school degree in Science
2018-01-01-2020-01-01