Muhammad Abdullah Asim
NUST
· 2026
·
411172
Email
masim.bee22seecs@seecs.edu.pk
Phone
923080650799
GitHub
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Academic
Program
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CGPA
3.16
Year
2026
Education
Bachelors in Electrical Engineering
School of Electrical Engineering and Computer Sciences (SEECS) , Islamabad (2026)
Address
HOUSE # 315, STREET # 6, NEMAT COLONY # 1, FAISALABAD , Faisalabad , Pakistan
DOB
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Career
Current role
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Target role
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Skills
PROFESSIONAL PROFILE
Electrical Engineering undergraduate at NUST with a strong grasp of circuit and system design fundamentals. Experienced in
developing, testing, and refining engineering solutions through academic and hands-on projects. Skilled at applying technical
knowledge, logical thinking, and problem-solving approaches to address real-world engineering challenges and contribute effectively
in technical environments.
EDUCATION
Bachelors in Electrical Engineering
School of Electrical Engineering and Computer Sciences (SEECS) , Islamabad (2026)
INTERNSHIP EXPERIENCE
NUST Chip Design Centre, SINES
10-Jun-2025 - 29-Aug-2025
Completed an intensive training and project phase under the iFYP program in the domain of Analog IC Design on CMOS technology,
focusing on schematic and layout design of integrated circuits using Cadence Virtuoso. Training covered DC characterization of
MOSFETs, DC/Transient/AC analyses of single-stage and differential amplifiers, current mirroring, biasing techniques, and
introductory layout practices. Applied acquired skills to design the schematic and layout of a two-stage operational transconductance
amplifier (OTA) with defined performance targets, gaining insights into design trade-offs and parameter optimization
ESDAC Research Laboratory, SEECS
17-Jun-2024 - 30-Aug-2024
Developed embedded Linux applications for Linux based DE1 SoC board by Intel, gaining hands-on experience in I/O operations,
memory-mapped I/O, and kernel module development Implemented device drivers for various peripherals and custom FPGA
hardware, enhancing embedded systems solutions
Crescent Textile Mills, Faisalabad
11-Jul-2023 - 11-Aug-2023
Gained hands-on experience in power generation, transformer operations, and maintenance, working with various types of
generators and learning key safety and reliability practices Developed practical skills in electronic instrument calibration, motor speed
control, and troubleshooting electrical devices, while collaborating with engineers and technicians across multiple departments
FINAL YEAR PROJECT
LiDAR Analog Front-end Chip for Automotive Applications
This project focuses on the design of a low-power, high-performance LiDAR Analog Front-End (AFE) chip for automotive
applications, addressing the growing demand for long-range, high-resolution, and energy-efficient sensing systems in advanced
driver-assistance and autonomous vehicles. The work targets key limitations in existing LiDAR receivers, particularly high input-
referred noise in dual-gain Transimpedance Amplifiers (TIAs) under strong signal conditions and excessive power consumption in
Analog-to-Digital Converters (ADCs). The proposed solution involves replicating and optimizing a dual-gain TIA architecture to
improve noise performance while maintaining wide dynamic range, alongside redesigning the ADC using a more power-efficient
architecture that meets required linearity, resolution, and speed specifications. The project deliverables include complete schematic-
level designs of the TIA and ADC blocks, detailed pre-layout and post-layout simulation results, integrated layout implementation, and
performance validation against target specifications to demonstrate suitability for automotive LiDAR systems.
AI enrichment
Electrical Engineering undergraduate at NUST with a strong grasp of circuit and system design fundamentals. Experienced in
developing, testing, and refining engineering solutions through academic and hands-on projects. Skilled at applying technical
knowledge, logical thinking, and problem-solving approaches to address real-world engineering challenges and contribute effectively
in technical environments.
Status: ai_done
Provenance
Source file: —Created: 1777448793