Dr. Fahman Saeed | Signal Distortion Awards | Best Researcher Award

Dr. Fahman Saeed, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

Dr. Fahman Saeed is an Assistant Professor in the College of Computer and Information Sciences at Imam Mohammad Ibn Saud Islamic University (IMSIU) in Riyadh, Saudi Arabia. With a Ph.D. in Computer Science from King Saud University, his research focuses on deep learning models, particularly for automatic diabetic retinopathy screening. He has contributed significantly to various research projects, including the development of fingerprint interoperability solutions and privacy-protected breast cancer screening systems, earning multiple ISI papers, patents, and conference presentations. Dr. Saeed also has extensive experience in machine learning, specializing in PyTorch, TensorFlow, and large language models. In addition to his academic achievements, he actively participates in professional activities, such as curriculum development and leading workshops on AI, NLP, and generative AI. His dedication to education and research, coupled with his expertise in artificial intelligence, continues to influence both his academic institution and the broader scientific community.

Professional Profile:

ORCID

Suitability for Best Researcher Award: Fahman Saeed

Fahman Saeed is exceptionally suited for the Best Researcher Award due to his outstanding contributions to the field of computer science, particularly in the areas of deep learning, machine learning, and artificial intelligence. With a robust academic background and extensive experience in both research and teaching, Dr. Saeed has demonstrated leadership in advancing the application of machine learning technologies in critical areas like medical diagnostics and data security.

Education 🎓

Ph.D. in Computer Science
- Institution: King Saud University, Saudi Arabia 🎓
- Graduation: November 2021 📅
- Dissertation: Developing an auto deep learning model with less complexity and high performance for automatic diabetic retinopathy screening 🧠💻
M.Sc. in Computer Science
- Institution: King Saud University, Saudi Arabia 🎓
- Graduation: May 2014 📅
B.Sc. in Computer Science
- Institution: King Saud University, Saudi Arabia 🎓
- Graduation: February 2007 📅

Academic Experience 📚

Assistant Professor
- Institution: College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia 🏫
- Duration: 2022 to Present ⏳
- Responsibilities: Teaching courses in Artificial Intelligence 🤖, Natural Language Processing 💬, Algorithm Design and Analysis 💻, Image Processing 🖼️, and Computer Vision 👀
Lecturer (Part-time)
- Institution: King Saud University, Riyadh, Saudi Arabia 🎓
- Duration: 2017 to 2021 ⏳
Researcher
- Institution: King Saud University, Riyadh, Saudi Arabia 🧪
- Duration: March 2015 to 2021 ⏳
- Projects:
  - Automatic Diabetic Retinopathy Screening 🩺👁️
    - Achievements: Two ISI papers 📄
  - Identification of Fingerprint Interoperability 🧑‍⚖️
    - Achievements: One patent, one ISI paper, two conference papers 📑
  - Cloud-Based Privacy-Protected Computer-Aided Diagnosis System for Breast Cancer Screening 🩻
    - Achievements: One ISI paper 📄

Publication Top Notes

Adaptive Renewable Energy Forecasting Utilizing a Data-Driven PCA-Transformer Architecture

Blockchain-Based Quality Assurance System for Academic Programs

Optimal Sizing and Placement of Distributed Generation under N-1 Contingency Using Hybrid Crow Search–Particle Swarm Algorithm

A Data-Driven Convolutional Neural Network Approach for Power Quality Disturbance Signal Classification (DeepPQDS-FKTNet)

Designing the Architecture of a Convolutional Neural Network Automatically for Diabetic Retinopathy Diagnosis

Assist Prof Dr. Hwa-Dong Liu, Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taiwan

Hwa-Dong Liu is an Assistant Professor at National Taiwan Normal University (NTNU) in Taipei, Taiwan, specializing in power electronics, microcontrollers, rail vehicle power systems, and solar power systems. He holds a Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST). His research interests include the development of advanced power converters, control strategies for renewable energy systems, and innovative solutions for electric vehicle charging. Dr. Liu has authored numerous papers in reputable journals, with a focus on improving the efficiency and performance of power electronic systems and renewable energy technologies. His recent work includes contributions to energy management systems, high-gain boost converters, and novel MPPT algorithms for solar power generation.

Publication top Notes: