Faris H. Rizk
Faris H. Rizk

Undergraduate Engineer & Researcher

Delta Higher Institute of Engineering and Technology, Egypt
State University of New York at Buffalo, NY, USA
Zewail City Computing Society (ZCCS), Zewail City of Science, Egypt

About Me

Hello! My name is Faris Hamdi Rizk Elsayed Ibrahim, and I am an undergraduate researcher and aspiring junior Communications and Electronics Engineering student with a strong passion for Machine Learning and Computer Vision.

Currently, I’m an undergraduate researcher at the State University of New York at Buffalo, contributing to the development of a novel human-object interaction detection model. I also serve as the Research Lead at the Zewail City Computing Society’s Applied Machine Learning Lab, where I focus on advancing the frontiers of Computer Vision, Natural Language Processing (NLP), and Machine Learning.

Previously, my research at the Delta Higher Institute of Engineering and Technology delved into metaheuristic optimization and machine learning applications, culminating in four international publications. These experiences have solidified my passion for leveraging AI to solve real-world problems and deliver impactful, innovative solutions.

After graduation, I plan to pursue a Ph.D. in Computer Vision, Applied Machine Learning, or Natural Language Processing at a top-tier university in the USA. If my expertise and research interests align with the goals of your lab, I would be excited to explore opportunities for collaboration.

I’m always enthusiastic about exploring new ideas, collaborating on exciting projects, and contributing to the ever-evolving field of AI. Let’s connect and make a difference together!

Interests
  • Computer Vision and Language
  • Deep Learning
  • Optimization
Education
  • Bachelor of Engineering in Electronics and Communication Engineering

    Delta Higher Institute of Engineering and Technology in Egypt, 2026 (expected)

Recent Publications
(2024). Pothole Detection in Asphalt Roads: A Comprehensive Approach for Enhanced Road Maintenance and Safety with AlexNet Model. 2024 International Telecommunications Conference (ITC-Egypt).
(2024). Ocotillo Optimization Algorithm (OcOA): A Desert-Inspired Metaheuristic for Adaptive Optimization. Journal of Artificial Intelligence and Metaheuristics.
(2024). Enhancing Student Performance Prediction with Greylag Goose Optimization Algorithm. 2024 International Telecommunications Conference (ITC-Egypt).
(2024). NiOA: A Novel Metaheuristic Algorithm Modeled on the Stealth and Precision of Japanese Ninjas. Journal of Artificial Intelligence in Engineering Practice.
(2024). iHow optimization algorithm: a human-inspired metaheuristic approach for complex problem solving and feature selection. Journal of Artificial Intelligence in Engineering Practice.
Recent News

New Medium article; Query-Based Pairwise Human-Object Interaction Detection with Transformers (QPIC)(Explained)

Imagine a bustling city street captured by a surveillance camera: pedestrians crossing paths, vehicles maneuvering through traffic, cyclists weaving between lanes, and street vendors interacting with customers. For a computer vision system to make sense of this scene, it needs to not only detect the humans and objects present but also understand their interactions. This complex task is known as Human-Object Interaction (HOI) detection, a critical component for applications like autonomous driving, robotic assistance, and advanced surveillance systems.