Huzaifa Akhtar
NUST
· 2026
Email
huzaifaakhtar2002@gmail.com
Phone
923124558662
GitHub
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Academic
Program
BEE
CGPA
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Year
2026
Education
SEECS
Address
Lahore, Pakistan
DOB
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Career
Current role
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Target role
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Skills
Verilog, SystemVerilog, RISC-V Processor Design, Computer Architecture, Pipelining, Tomasulo’s Algorithm, Cache Memory, Arduino, ESP8226, ESP32, PLC Programming, Ladder Logic, IoT Sensor Integration, Python, Machine Learning, Supervised Learning, SVM Classifiers, Neural Networks, CNNs, OpenCV, Object Detection, YOLO, Feature Extraction, SIFT, Harris Corners, Optical Flow, Image Segmentation, Computer Vision, Deep Learning, Edge Devices, Embedded Hardware, Data-driven web applications, Desktop software
Verbatim text
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Huzaifa Akhtar Cell: 923124558662 | Email: huzaifaakhtar2002@gmail.com LinkedIn: https://https:/www.linkedin.com/in/huzaifa-akhtar-070826250 Address: HNO 14,GOSHA-E-AHBAB PHASE 03,MULTAN RD LHRE , Lahore , Pakistan PROFESSIONAL PROFILE Versatile Electrical Engineering student with a unique passion for bridging the gap between hardware and software. My technical expertise spans the full stack: from designing low-level architectures using Verilog/RISC-V and FPGAs to developing high-level software solutions. I am experienced in building machine learning pipelines with Python, creating data-driven web applications, and developing desktop software. I thrive at the intersection of these fields, building systems where efficient hardware meets intelligent software EDUCATION Matric Liaquat Foundation High School , Lahore , 1100 (2020) F. Sc Unique College Lahore , Lahore , 947 (2022) INTERNSHIP EXPERIENCE Al-Khidmat Foundation 01-Jun-2023 - 01-Sep-2023 Social Media Compaign Managment Nust Chip Design Center 01-Jun-2026 - 01-Sep-2026 Implemented an AXI-AHB bridge module to handle signal synchronization and data transfer between different bus architectures FINAL YEAR PROJECT An AI-based diagnostic involving X-ray images and facial photos to detect multiple diseases AI-Based Multi-Modal Disease Diagnostic System "Developed a dual-input diagnostic system that leverages Computer Vision and Deep Learning to detect multiple pathologies. The system fuses medical X-ray imagery with facial biomarker analysis to improve diagnostic accuracy. Designed to potentially run on edge devices, the project explores optimizing Convolutional Neural Networks (CNNs) for efficient inference on embedded hardware, aiming to provide accessible healthcare solutions." TECHNICAL EXPERTISE HDLs & Architectures Verilog, SystemVerilog, RISC-V Processor Design, Computer Architecture (Pipelining, Tomasulo’s Algorithm, Cache Memory) Microcontrollers & IoT Arduino, ESP8266/ESP32, PLC Programming (Ladder Logic), IoT Sensor Integration (Air Quality Monitors) Artificial Intelligence & Computer Vision Machine Learning: Supervised Learning, SVM Classifiers, Neural Networks (CNNs). Computer Vision: OpenCV, Object Detection (YOLO), Feature Extraction (SIFT, Harris Corners, Optical Flow), Image Segmentation. Projects: Multi-modal Disease Detection (X- ray + Facial biomarkers), Hand-movement Game Control.
AI enrichment
Huzaifa Akhtar is an Electrical Engineering student with a focus on bridging hardware and software through FPGA design, RISC-V architecture, and machine learning. He has practical experience in digital logic design and is currently developing an AI-based multi-modal disease diagnostic system for his final year project.
Skills (AI)
["Verilog", "SystemVerilog", "RISC-V", "FPGA", "Python", "Machine Learning", "Computer Vision", "OpenCV", "YOLO", "CNN", "Arduino", "ESP32", "IoT", "PLC Programming"]
Status: ai_done
Provenance
Source file: SEECS - Electrical Engineering-2026.pdfFrom job #259 page 86
Created: 1778168427