Dr. Mohamed S. Darweesh

Associate Professor

Faculty Office Ext.

3025

Faculty Building

UB2

Office Number

S09

Bio

Biography

Mohamed Saeed Darweesh (M’17, SM’20) received his master’s and Ph.D. degrees (with honors) in Electronics and Electrical Communications Engineering from the Faculty of Engineering, Cairo University, Giza, Egypt, in 2013 and 2017, respectively. He is currently an Associate Professor and the Co-Director of the Electronics and Computer Engineering (ECE) Program at the School of Engineering and Applied Sciences, Nile University. Previously, he worked at the American University in Cairo (AUC), Zewail City (ZC) of Science and Technology, Arab Academy for Science and Technology and Maritime Transport (AASTMT), and Institute of Aviation Engineering and Technology (IAET).

Saeed Darweesh is a Member of the Council of Education and Scientific Research Policies, The Academy of Scientific Research & Technology (ASRT) in 2025-28, and a Member of the National Committee for Artificial Intelligence Sciences, The Academy of Scientific Research & Technology (ASRT) in 2025-28.

Saeed Darweesh is a Senior Member of the IEEE since 2020 and an HKN Professional member. He has served on the technical program committees of major IEEE conferences. Currently, he is serving as the IEEE Region 8 Young Professionals Committee Chairman 2025-2026, the IEEE MGA Student Activities Committee, Young Professionals Representative 2026, IEEE MGA YP Awards and Recognition Committee Member 2025-2026, the 2026 IEEE HTB Tech4Good Member, the 2026 IEEE HTB Program Committee Member, CRSP Member, R8 SAC as Ex-officio from MGA SAC 2026, the IEEE R8 Conference Coordination Cmte. Liaison with R8 Finance Committee 2026, the 2025 IEEE PowerAfrica Conference Treasurer, the 2026 IEEE MELECON Treasurer, and the IEEE Egypt Section Secretary 2024-2027. Additionally, he is a recipient of the 2024 IEEE MGA Young Professionals Award and a graduate of the 2024 IEEE VoLT Program. He was an IEEE SIGHT Committee Member in 2025, a corresponding member of the R8 YP Committee, a member of the HTB Proposal Evaluation Subcommittee, and a member of the HTB Events Committee. Additionally, he has served as the IEEE YP Egypt Chair for 2022-2023 and as the IEEE SIGHT Egypt Chair for 2024-2025.

Saeed actively serves as a reviewer in several journals and conference publications, including IEEE conferences and journals. Dr. Saeed has led multiple research projects in the fields of artificial intelligence, machine learning, healthcare, and Industry 4.0. He has authored/co-authored over +80 papers in international journals and conferences. Also, he is a Principal Investigator (PI), Co-PI, and Research Associate in several research projects funded by different agencies like the Science and Technology Development Fund (STDF), National Telecom Regulatory Authority (NTRA), Information Technology Industry Development Agency (ITIDA), and Academy of Scientific Research and Technology (ASRT). He supervised over +100 graduation projects. He has a solid technical background with a strong interest in machine learning and artificial intelligence. His research interests focus on Wireless Communications, Self-Driving Cars, Vehicle-to-Vehicle (V2V) Systems, Narrow-Band IoT (NB-IoT), Biomedical Engineering (EEG Seizure Detection, Sleepiness Detection using EEG, Breast Cancer Classification, and Skin Cancer Prediction), Optimization Techniques, and Data Compression. He authored/co-authored over +100 papers in international journals and conferences. Saeed also worked and trained with many telecom operators and suppliers like (MobiNil, Alcatel-Lucent, and Geniprocess) and has a strong background in computer networks and security.

Achievements

1) Best Paper Award (First Place) at NILES2020 “Comparative Analysis of Various Machine Learning Techniques for Epileptic Seizures Detection and Prediction Using EEG Data".

2) Best Paper Award (Third Place) at ICM2020 “Collision Probability Computation for Road Intersections based on Vehicle to Infrastructure Communication”.

3) Best Paper Award (Third Place) at NILES2021“Real-Time Fish Detection Approach on Self-Built Dataset Based on YOLOv3”.

4) Outstanding Paper Award at ICACT2022, “Relay Selection in NOMA-Based Diamond Relaying Networks".

5) Mohamed Saeed Darweesh ECE graduation project titled: “Enhanced Beauty Services Mobile Application Based on Artificial Intelligence” has been accepted at the AUC Science Slam competition and qualified for the finalists 2021.

6) Mohamed Saeed Darweesh was nominated to be an Expert at Phi Science Institute, 2021.

7) Mohamed Saeed Darweesh was elected as Chair for IEEE Young Professionals Egypt Section for 2022-2024.

8) Mohamed Saeed Darweesh was elected as Secretary for IEEE Egypt Section for 2024-2027.

9) Mohamed Saeed Darweesh was appointed as Chair for IEEE Region 8Young Professionals Committee for 2025-2026.

Recent Publications

The rising interest in assistive and autonomous driving systems throughout the past decade has led to an active research community in perception and scene interpretation problems like lane detection. Traditional lane detection methods rely on specialized, hand-tailored features which is slow and prone to scalability. Recent methods that rely on deep learning and trained on pixel-wise lane

In recent years, many probability models proposed to calculate the collision probability for each vehicle and those models used in collision avoidance algorithms and intersection management algorithms. In this paper, we introduce a method to calculate the collision probability of vehicles at an urban intersection. The proposed model uses the current position, speed, acceleration, and turning

This paper aims to help self-driving cars and autonomous vehicles systems to merge with the road environment safely and ensure the reliability of these systems in real life. Crash avoidance is a complex system that depends on many parameters. The forward-collision warning system is simplified into four main objectives: detecting cars, depth estimation, assigning cars into lanes (lane assign) and

This paper develops a lane-change geometric representation that can be used in an on-road vehicle. The design of the proposed system uses the data collected from active a host vehicle and measures the relative speed between host vehicle and obstacle vehicles in real-time. The available distance to the target lanes measures the separated distance between the host and obstacle vehicles in real-time

In this paper, a resource partitioning scheme combined with a new multi-carrier optical modulation technique for indoor visible light communication (VLC) system is proposed. In VLC systems, the coverage area is divided into multiple atto-cells. In each atto-cell, multiple LED arrays are used as access points (APs) serving the assigned users. The coverage area of APs might be overlapped to avoid

Indoor localization has recently attended an increase in interest due to the potential for a wide range of services. In this paper, indoor high-precision positioning and motion prediction algorithms are proposed by using light fidelity (LI-FI) system with angular diversity receiver (ADR). The positioning algorithm uses to estimate the location of an object in the room. Furthermore, the prediction

This paper demonstrates the software and hardware of a forward-collision warning system using techniques of realtime computer vision which helps self-driving cars and autonomous vehicles systems to merge with the road environment safely and ensure the reliability of these systems. The software approach of the paper consists of five parts: car detection, depth estimation, lane assignation, the

In this paper, topology design, optimal routing, and gateways placement selection algorithms are proposed in Heterogeneous Cloud Radio Access Network (C-RAN) with exploiting Free Space Optical (FSO) communication. The proposed network consists of two tiers; the lower tier concerns with clustering Remote Radio Heads (RRHs) based on traffic demands. The upper tier consists of transceivers along with

The long-term evolution (LTE) transports complex-baseband samples between the remote radio head and baseband processing unit. Common public radio interface (CPRI) protocol is used in practice and enables flexible radio head deployments and distributed antenna systems. Current wireless links (FSO and mmWave) have a few Gb/p transmissions which insufficient capacity are to support 20 MHz bandwidth

Research Tracks

Artificial Intelligence
Machine Learning
Optimization Techniques
Wireless Communications
Self-Driving Cars
Biomedical Engineering Applications

Grants

Projects

Research Project

Low Power 3GPP (Release 14) NB-IoT Platform for Internet of Things Applications

Internet of Things (IoT) is a network of physical objects or people called things, where electronics, software, and network work together to open the door for these things to be able to collect and exchange data remotely. The IoT devices serve many applications such as smart cities, wearables and health monitoring, security, and surveillance. Low cost, long battery life, low data rate, low latency

Research Project

IoT-based Platform for Wearable Devices for Continuous Healthcare Monitoring

The ultimate goal of this project is to achieve diagnosis on the fly and predict abnormal health conditions and alert people before the condition happens. In order to achieve this, the following objectives should be fulfilled: Implementing wearable self-powered painless devices for healthcare monitoring. Implementing AI algorithm for predicting abnormal health conditions. Implementing painless

Research Project

Interactive Smart Application for Museums Education (iSAME)

Information and Communication Technologies (ICTs) play a huge role in developing and updating the functions and innovative activities for a promising economic performance of museums and cultural institutions, allowing museums to achieve remarkable success and reach their main goals of attracting people and spreading historical knowledge. As a result of the increasing numbers of technologies and

Research Project

An Underwater AR based System for Marine Life Detection and Classification for Divers and Tourists

Objective/Contributions: Collecting and annotating an extensive dataset of fish images representing the fish species in the red sea. Building a machine learning model capable of detecting and classifying fish species from a real-time video. Building a proof-of-concept prototype for the AR hardware that is capable of capturing the live video of marine life, running the classification model, and

Research Project

Pre-emergency Alert IoT System-based on Wearable Devices for Diabetic Patient

According to World Health Organization (WHO), there are more than 400 million diabetic adults worldwide. In Egypt, only there are about 8 million diabetic people, and the diabetes prevalence rate is estimated to be 13.3% by 2025, according to WHO. In most cases, the diabetic person requires regular visits to the hospital for health checks. However, due to the COVID pandemic, it has become risky

Research Project

Artificial Intelligence Based Cloud Computing for Autonomous Traffic Management

Automobile-related deaths rank as one of the most common causes of death in many places, particularly developing countries; Egypt loses about 12,000 lives due to road traffic crashes every year. The greatest danger to human beings is not cars but people themselves because cars are not dangerous if driven by care and more attention. Cell phone use, whether by talking on the phone or texting

Research Project

Low-Power Artificial Intelligence Framework for Internet of Things Applications

The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI). Due to the massive scalability of modern IoT networks and increased data privacy, traditional AI algorithms require centralized data collecting and processing, which may not be practical in real-world application