Khansa Mishqat

NUST · 2026

khansa.mishqat@gmail.com

Phone

923185437479

https://www.linkedin.com/in/khansa-mishqat-30bb8b275?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app

GitHub

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Academic

Program

BEE

CGPA

3.02

Year

2026

Education

SEECS

Address

Islamabad, Pakistan

DOB

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Career

Current role

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Target role

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Skills

Verilog, SystemVerilog, Python, C++, Assembly, Vivado, Quartus, Matlab, Pspice, Proteus, FPGA, Digital Systems Design, Embedded Systems, AI Hardware Acceleration, Edge AI, Secure Hardware Architecture, Vitis, ModelSim, RISC-V, AXI Protocol, C/C++, Embedded C, Microcontroller Programming, GPIO & Peripheral Interfacing, I2C, SPI, UART, Arduino, ATmega328P, ATmega16A, STM32, ESP32, Arduino IDE, Atmel Studio, STM32CubeIDE, Data Cleaning & Preprocessing, Feature Extraction, Supervised & Unsupervised Learning, Linear & Logistic Regression, Decision Trees, SVM, K-Nearest Neighbors, Clustering, Dimensionality Reduction (PCA)

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.

Khansa Mishqat
Cell: 923185437479 |  Email: khansa.mishqat@gmail.com
LinkedIn: https://www.linkedin.com/in/khansa-mishqat-30bb8b275?
utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Address: HOUSE NO.575-B, SECTOR G-7/3-1, ISLAMABAD-44000 , Islamabad , Pakistan
PROFESSIONAL PROFILE
Final-year Electrical Engineering student at NUST with a specialized focus on Digital System Design, Embedded Systems, and AI
Hardware Acceleration. Gained industry experience during a research internship at NECOP, where i in a team designed and
modiﬁed AXI/DMA-based data transfer systems and custom control logic on FPGA. Currently working on a high-speed AI
accelerator for YOLOv8 inference on the Xilinx ZCU102 platform to optimize real-time latency and throughput.
Proﬁcient in languages like Verilog/SystemVerilog, Python, C++ and Assembly and tools like Vivado, Quartus, Matlab, Pspice
and Proteus, with a strong interest in edge AI and secure hardware architecture.
EDUCATION
Bachelor of Electrical Engineering
SEECS , Islamabad , 3.02 (2026)
INTERNSHIP EXPERIENCE
NECOP
23-Jun-2025 - 23-Sep-2025
The key higlights of my internship were: 1. Studied modern hardware accelerator architectures to understand how computation and
data movement are designed together. 2. Worked with a DMA loopback–based accelerator design and learned how data is
transferred between the Processing System (PS) and Programmable Logic (PL) using AXI interfaces. 3. Modiﬁed the design to
support two input streams and added buffers inside the processing loop, controlled from the PS side, to manage data flow.
FINAL YEAR PROJECT
High Speed AI Accelerator on FPGA for Real-Time Object Detection
Designed and implemented an FPGA-based AI accelerator for real-time object detection and classiﬁcation, using custom hardware
IPs to speed up the compute-heavy parts of a YOLO-based model while the processing system manages control and integration. The
system is built in a modular way with clear PS–PL communication, keeping the overall design simple and extendable.
TECHNICAL EXPERTISE
FPGA & Digital Systems Design
Verilog, SystemVerilog, Vivado, Vitis, Quartus, ModelSim, RISC-V, AXI Protocol.
Programming
C/C++, Python and Assembly
Embedded Systems
Embedded C, Microcontroller Programming, GPIO & Peripheral Interfacing, I2C, SPI, UART Microcontrollers: Arduino, ATmega328P,
ATmega16A, STM32, ESP32 Tools: Arduino IDE, Atmel Studio, STM32CubeIDE
Machine Learning
Data Cleaning & Preprocessing, Feature Extraction, Supervised & Unsupervised Learning, Linear & Logistic Regression, Decision
Trees, SVM, K-Nearest Neighbors, Clustering, Dimensionality Reduction (PCA)

AI enrichment

Khansa Mishqat is a final-year Electrical Engineering student specializing in digital system design, embedded systems, and AI hardware acceleration. She has gained practical experience through an internship at NECOP working on FPGA-based data transfer systems and is currently developing a high-speed AI accelerator for real-time object detection.

Skills (AI)

["Verilog", "SystemVerilog", "FPGA Design", "Vivado", "Quartus", "Python", "C++", "Embedded Systems", "AXI Protocol", "DMA", "RISC-V", "Machine Learning", "YOLOv8", "Xilinx ZCU102"]

Status: ai_done

Provenance

Source file: SEECS - Electrical Engineering-2026.pdf
From job #259 page 35
Created: 1778168427