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Ahmed Jamil

NUST · 2026

ahmedjamilkhokhar@gmail.com

Phone

923246106402

https://www.linkedin.com/in/ahmed-jamil-31881b2ba

GitHub

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Academic

Program

BEE (Electrical Engineering)

CGPA

3.3

Year

2026

Education

School of Electrical Engineering and Computer Sciences (SEECS)

Address

HS#2,ST#5,BAZAR #1 ASGHAR COLONY NEARNIGAR UNDERPASS ,FAISAL ROAD , Gujranwala , Pakistan

DOB

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Career

Current role

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Target role

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Skills

Embedded Systems, Semiconductor Design, Chip Design, Verification, AI Techniques, RISC-V, Neuromorphic Accelerator, Spiking Neural Networks (SNNs), Vivado, FPGA Design, Synthesis, Implementation, Timing Analysis, Verilog, SystemVerilog, IP Cores, Simulations, Bitstreams, Verilator, High-speed Simulation, Cycle-accurate C++ models, Functional Validation, Performance Analysis, Debugging, Testbench Integration

Verbatim text

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Ahmed Jamil
Cell: 923246106402 |  Email: ahmedjamilkhokhar@gmail.com
LinkedIn: https://www.linkedin.com/in/ahmed-jamil-31881b2ba
Address: HS#2,ST#5,BAZAR #1 ASGHAR COLONY NEARNIGAR UNDERPASS ,FAISAL ROAD , Gujranwala , Pakistan
PROFESSIONAL PROFILE
Electrical Engineer specializing in embedded systems and semiconductor design, with hands-on experience in chip design and
veriﬁcation. Strong focus on applying AI techniques within embedded environments to build eﬃcient, intelligent, and hardware-aware
solutions.
EDUCATION
BEE (Electrical Engineering)
School of Electrical Engineering and Computer Sciences (SEECS) , Islamabad , 3.3 (4)
INTERNSHIP EXPERIENCE
ChipXprt
09-Jun-2025 - 11-Jul-2025
Worked on the processor core design and Verification
System On Chips (SoC) Lab
14-Jul-2025 - 22-May-2026
Working on Risc - V Neuromorphic Accelerator for Low power Surveillance.
FINAL YEAR PROJECT
Risc V Based Neuromorphic Accelerator for Spiking Neural Networks
This project focuses on the design and implementation of a RISC-V based neuromorphic accelerator specifically optimized for Spiking
Neural Networks (SNNs). Spiking neural networks are inspired by the way biological neurons communicate using discrete spikes,
making them highly energy-eﬃcient and suitable for real-time and edge-based intelligent systems. The proposed system integrates a
lightweight RISC-V processor with a custom neuromorphic accelerator to eﬃciently handle spike-based computation, neuron
updates, and synaptic weight processing. While the RISC-V core manages control ﬂow and general operations, the accelerator is
responsible for parallel spike processing, reducing execution latency and power consumption compared to conventional CPU-based
implementations. The project explores neuron models, spike encoding, and event-driven computation, and evaluates the system in
terms of performance, scalability, and energy eﬃciency. The ﬁnal implementation can be validated through simulation and/or FPGA
prototyping, demonstrating how open-source RISC-V architectures can be extended for emerging AI workloads such as
neuromorphic computing. This work highlights the potential of combining open-source hardware with brain-inspired computing to
build efficient and adaptable AI accelerators for future embedded and edge applications.
TECHNICAL EXPERTISE
Vivado
Proﬁcient in using Xilinx Vivado for FPGA design, synthesis, implementation, and timing analysis. Experienced in developing and
debugging Verilog/SystemVerilog designs, integrating IP cores, running simulations, and generating bitstreams for FPGA-based
prototyping and validation.
Verilator
Hands-on experience using Verilator for high-speed simulation and veriﬁcation of SystemVerilog and Verilog designs. Skilled in
converting RTL designs into cycle-accurate C++ models for functional validation, performance analysis, and debugging of hardware
modules. Familiar with testbench integration, wavefor ...

AI enrichment

Ahmed Jamil is an Electrical Engineering graduate with a focus on embedded systems and semiconductor design, specifically working with RISC-V architectures and neuromorphic accelerators. He possesses practical experience in chip verification and FPGA prototyping through internships and a final year project involving Spiking Neural Networks.

Skills (AI)

["Embedded Systems", "Chip Design", "Verification", "RISC-V", "Neuromorphic Computing", "Spiking Neural Networks", "Xilinx Vivado", "Verilog", "SystemVerilog", "Verilator", "FPGA Prototyping", "Low Power Design"]

Status: ai_done

Provenance

Source file: SEECS - Electrical Engineering-2026.pdf
From job #259 page 94
Created: 1778168427