Summary
My research interests lie at the intersection of Embedded Systems and Machine Learning, with a particular focus on Embedded AI and intelligent microcontroller-based systems. I am also interested in Digital Signal Processing, Internet of Things (IoT), Digital Electronics, and the development of practical intelligent systems that integrate hardware and software for real-world applications.
Academic Background
Bachelor of Science in Electrical Engineering
(Embedded Artificial Intelligence System for Real-Time Analysis and Classification of Heart Sounds Using Machine Learning Techniques, with deployment on a RISC-V-based VisionFive platform)
Namal University Mianwali
2026
Experience
Lab Engineer, Department of Electrical Engineering
Namal University, Mianwali
07-Sep-2026 - Present
Grid Girls Internship Program — Intern
National Transmission and Dispatch Company (NTDC)
17-Jun-2025 - 17-Aug-2025
Teaching Assistant
Namal University Mianwali
13-Jul-2023 - 30-Jun-2025
Honours and Awards
Best 2-Minute Video Award
Awarded for the Best 2-Minute Video Competition of the Final Year Project at Namal University.
02-Jul-2026
Courses
- Microprocessor-Based Embedded Systems Lab(5th semester, Fall 2026 [ongoing])
- Applications of Information and Communication Technologies Lab(1st semester, Fall 2026 [ongoing])
- Object-Oriented Programming Lab(3rd semester, Fall 2026 [ongoing])
- Digital Signal Processing Lab(5th semester, Fall 2026 [ongoing])
Carbon-Based Microwave Absorber
Designed and simulated a carbon-based microwave absorber using ANSYS HFSS, analyzing electromagnetic properties and optimizing material parameters and structural configurations to improve microwave absorption performance.
5-Stage Pipelined RV32I Processor
Designed and implemented a 5-stage pipelined RISC-V RV32I processor supporting 47 instructions using Verilog HDL, including the development and verification of key processor components such as the ALU, register file, control units, instruction memory, and pipeline registers.
Embedded AI System for Real-Time Heart Sound Analysis
Developed an AI-based embedded system for real-time classification of normal and abnormal heart sounds using Phonocardiogram (PCG) signals. Collected, processed, and labeled cardiac sound data in collaboration with DHQ Hospital Mianwali and implemented machine learning models for heart sound classification and deployment on a RISC-V processor for low-power, real-time healthcare applications.
Namal University