Hamdi Altaheri
PhD | Senior IEEE Member | Postdoctoral Scholar | AI Researcher
PhD | Senior IEEE Member | Postdoctoral Scholar | AI Researcher
Developing EEG–LLM integration project for next-gen brain signal decoding using self-supervised learning and foundation models.
Courses: Discrete Math, Data Structures, E-business, Computer Networks.
Developed AI solutions in brain–computer interfaces, Arabic sign language recognition, computer vision, automated harvesting, robotics, and crowd analysis.
Tutorials for courses in Digital Signal Processing and Speech Processing.
Operated drones and real-time monitoring systems to support crowd analytics during Hajj 2017.
Lab sessions and tutorials for courses in Software Engineering and Information Technology.
Engaged in research and development projects focused on embedded control systems.
King Saud University, Riyadh, Saudi Arabia | GPA: 4.93 / 5.0
Thesis: "A Vision System for Date Harvesting Robot"
Taiz University, Taiz, Yemen | Honours Degree | Rank: 1st / 64
Graduation Project: "Universal Control and Security System"
| IEEE Transactions on Industrial Informatics Top 5% ISI Journal
| IEEE Internet of Things Journal Top 5% ISI Journal
| arXiv preprint
| IEEE Dataport
| IEEE SMC Conference
| IEEE SMC Conference
U.S. Patent No. 11910751
U.S. Patent No. 10485171
This project investigates self-supervised learning on large-scale brain datasets to develop a large brain foundation model, aiming to enhance the accuracy, generalization, and robustness of brain–computer interface (BCI) systems.
This project aims to develop deep learning models that automatically focus on the most relevant temporal, spatial, and spectral features of EEG signals to improve brain signal decoding accuracy.
This project aims to developed an intelligent machine vision system based on deep learning for automated date fruit harvesting in natural orchard environments. The system performs comprehensive fruit detection, segmentation, variety classification, maturity analysis, and visual yield estimation to enable robotic harvesting operations.
Designed and implemented an integrated universal and scalable system for control and security applications. The system combines an embedded microprocessor-based electronic unit with network-based 3D software interface to enable comprehensive smart building automation, monitoring, and security management.
Intelligence-based crowd-management system to track Hajj and Umrah, predict and detect incidents using smart wearables and mobile devices.
Two-way sign language translator robot using Transformer-based deep learning for Arabic sign recognition.
Interactive visualization and solution approaches for the classic Travelling Salesman Problem using various optimization algorithms.
Portable mail sorting and notification device using MSER for text detection, Tesseract OCR for recognition, and fuzzy name matching.
Stanford University & Elsevier
Scientific Forum, King Saud University
DSR–KSU for publishing in top 5% ISI journals
College of Computer and Information Sciences, King Saud University
Scientific Forum, King Saud University
President of the Republic of Yemen
President of the Republic of Yemen (one prize awarded annually)
Engineering and Computer Sciences, Taiz University
Centre for Pattern Analysis and Machine Intelligence
University of Waterloo
Waterloo, ON, Canada
