Muhammad Taaha Hashmi
NUST
· 2022
Email
mtaahahashmi@gmail.com
Phone
923369996069
GitHub
—
Academic
Program
BSE
CGPA
3.27
Year
2022
Education
SEECS
Address
VILLAGE PINDI MIANI P.O. JALALPUR JATTAN TEHSIL AND DISTRICT GUJRAT , Gujrat , Pakistan
DOB
—
Career
Current role
—
Target role
—
Skills
Hardware Design, Automated Intelligence, System Integration, Circuit Design, Algorithm Implementation, Processor Verification, CVA6 RISC-V Architecture, Cadence Xcelium, RTL Compilation, Memory Management Unit (MMU), Floating Point Unit (FPU), mm-Wave Radar Technology, Digital Signal Processing, TI AWR6843AOP, Health Monitoring Systems
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
Muhammad Taaha Hashmi Cell: 923369996069 | Email: mtaahahashmi@gmail.com LinkedIn: https://www.linkedin.com/in/muhammad-taaha-hashmi-3648a2248 Address: VILLAGE PINDI MIANI P.O. JALALPUR JATTAN TEHSIL AND DISTRICT GUJRAT , Gujrat , Pakistan PROFESSIONAL PROFILE Electrical Engineering student at SEECS, NUST. I possess a deep-rooted interest in the synergy between robust hardware design and automated intelligence. Through my involvement in the Xcelerium, I have gained valuable exposure to industry-standard methodologies, refining my ability to transition theoretical concepts into scalable, real-world engineering solutions. My background focuses on developing high-fidelity systems that bridge the gap between physical components and digital decision-making. I am a detail-oriented problem solver with a proven ability to navigate the complexities of system integration, from low-level circuit design to high-level algorithm implementation. I excel in collaborative, multidisciplinary environments where technical precision and creative thinking are required to solve complex challenges. With a commitment to continuous learning and technical excellence, I am prepared to contribute to innovative teams focused on advancing the next generation of autonomous and intelligent systems. EDUCATION Bahelors in Electrical Engineering SEECS , Islamabad , 3.27 (2022) INTERNSHIP EXPERIENCE Xcelerium 03-Nov-2025 - 02-Feb-2026 During my time in the Xcelerium (XCLR) early hire program, I gained hands-on experience in high-performance processor verification, specifically focusing on the CVA6 RISC-V architecture. I worked extensively within the Cadence Xcelium environment, where I managed complex simulation infrastructures, resolved RTL compilation dependencies, and verified critical processor components such as the Memory Management Unit (MMU) and Floating Point Unit (FPU). Beyond technical debugging and verification, I contributed to the team’s efficiency by developing a comprehensive beginner’s guide for the Cadence Xcelium toolset. This role allowed me to bridge the gap between academic hardware design and industry-standard verification methodologies, sharpening my ability to ensure system-level reliability in complex digital designs. TUIL Lab at RIMMS 21-Jul-2025 - 21-Sep-2025 During my summer internship, I led the initial development of a contactless health monitoring system using mm-Wave radar technology. I was responsible for the entire project lifecycle during this phase, from conducting research and defining the technical methodology to configuring the TI AWR6843AOP hardware for high-precision sensing. I successfully designed and implemented a digital signal processing pipeline that extracts heart and breathing rates from raw radar data by filtering out noise and isolating subtle body movements. By the end of the internship, I had established a fully operational test environment and validated the system’s accuracy against medical-grade sensors, proving the feasibility of wireless vital sign tracking. FINAL YEAR PROJECT Vital Signs Monitoring using mm-wave Radar Technology This project uses advanced radar technology to monitor a person’s heart rate and breathing without any physical contact. By using a specialized mm-wave sensor, the system can detect tiny movements in the chest from a distance and convert that data into vital sign readings. The goal is to create a comfortable, wireless way to track health, making it especially useful for hospitals or home care where traditional wearable sensors might be inconvenient. TECHNICAL EXPERTISE
AI enrichment
Muhammad Taaha Hashmi is an Electrical Engineering undergraduate with a 3.27 CGPA, specializing in hardware verification and embedded systems. He has practical experience in RISC-V processor verification using Cadence Xcelium and developing mm-wave radar-based health monitoring systems.
Skills (AI)
["RISC-V Architecture", "Hardware Verification", "Cadence Xcelium", "RTL Debugging", "Digital Signal Processing", "mm-Wave Radar", "TI AWR6843AOP", "System Integration", "Circuit Design"]
Status: ai_done
Provenance
Source file: SEECS - Electrical Engineering-2026.pdfFrom job #259 page 146
Created: 1778168427