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Abdussalam Sarmad

NUST · 2026

abdussalamsarmad@gmail.com

Phone

923224772853

https://www.linkedin.com/in/abdussalam-sarmad-76a749237/

GitHub

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Academic

Program

Electrical Engineering

CGPA

2.89

Year

2026

Education

SEECS

Address

132/C SHAH RUKN-E-ALAM COLONY , Multan , Pakistan

DOB

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Career

Current role

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Target role

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Skills

Embedded Systems, Microcontrollers, IoT, Arduino, ESP32, Motor Control, Digital Electronics, Circuit Design, AI, Machine Learning, Radar Systems, Signal Processing, C, C++, Verilog, RTL Design

Verbatim text

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Abdussalam Sarmad
Cell: 923224772853 | Email: abdussalamsarmad@gmail.com
LinkedIn: https://www.linkedin.com/in/abdussalam-sarmad-76a749237/
Address: 132/C SHAH RUKN-E-ALAM COLONY , Multan , Pakistan
PROFESSIONAL PROFILE
Motivated Electrical Engineering undergraduate with strong hands-on experience in embedded systems, microcontrollers, and IoT-
based projects. Proﬁcient in Arduino and ESP32, with practical exposure to motor control, digital electronics, and circuit design.
Actively exploring AI and machine learning applications to build intelligent, real-world engineering solutions.
EDUCATION
Electrical Engineering
School of Electrical Engineering and Computer Sciences (SEECS) , Islamabad , 2.89 (2026)
INTERNSHIP EXPERIENCE
RIMMS , Nust H12 (TUIL Lab)
21-Jul-2025 - 21-Sep-2025
During my internship, I worked on developing a contactless bioradar system to monitor vital signs. I conducted a detailed literature
review, planned the system methodology, and got hands-on experience with the TI AWR6843AOP radar module. I helped set up the
hardware, collected test data alongside a medical reference device, and implemented basic software to process and visualize
respiration and heartbeat signals. This experience gave me practical knowledge in radar systems, signal processing, and
experimental testing, while establishing a solid foundation for the next stages of the project.
FINAL YEAR PROJECT
Vital Signs Monitoring using MM-Wave radar technology
This project focuses on developing a non-contact system to monitor human vital signs using a 60 GHz millimetre-wave radar and a
Raspberry Pi. Chest wall movements are captured to estimate respiration rate, heart rate, and heart rate variability through digital
signal processing techniques such as ﬁltering and peak detection. The system processes data in real time and uploads results to a
web-based interface for remote monitoring. The aim of the project is to provide a safe, accurate, and privacy-friendly alternative to
conventional contact-based health monitoring systems, particularly for clinical and telemedicine applications.
TECHNICAL EXPERTISE
Embedded Systems & IOT
I have a strong technical background in embedded systems and microcontroller-based development, with hands-on experience using
Arduino and ESP32 for real-world applications. My expertise includes digital electronics, circuit design and analysis, and RTL/Verilog-
based digital design. I am proficient in C, C++, ...

AI enrichment

Abdussalam Sarmad is an Electrical Engineering undergraduate with a focus on embedded systems, IoT, and signal processing. He has practical experience in developing contactless vital signs monitoring systems using millimeter-wave radar and microcontrollers like ESP32 and Arduino.

Skills (AI)

["Embedded Systems", "IoT", "Arduino", "ESP32", "C", "C++", "Verilog", "Signal Processing", "Circuit Design", "Radar Systems", "Digital Electronics"]

Status: ai_done

Provenance

Source file: SEECS - Electrical Engineering-2026.pdf
From job #259 page 164
Created: 1778168427