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Muhammad Taaha Hashmi

NUST · 2022
Email
mtaahahashmi@gmail.com
Phone
923369996069
LinkedIn
https://www.linkedin.com/in/muhammad-taaha-hashmi-3648a2248
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

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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.pdf
From job #259 page 146
Created: 1778168427