Abid Iqbal | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Abid Iqbal | Artificial Intelligence | Best Researcher Award

Assistant Professor at King Faisal University, Saudi Arabia

Dr. Abid Iqbal is an accomplished Assistant Professor at the University of Engineering and Technology Peshawar, specializing in Electrical Engineering and artificial intelligence. He earned his Ph.D. from Griffith University, Australia, where he researched piezoelectric energy harvesters. With a strong academic background, he ranked first in his Master’s program at Ghulam Ishaq Khan Institute, Pakistan. Dr. Iqbal has a diverse professional experience, including roles as an Electrical Design Engineer and Research Assistant. His expertise encompasses developing embedded devices and innovative teaching methodologies, mentoring students, and conducting impactful research. He has successfully secured funding for multiple projects in AI applications for health and agriculture. Dr. Iqbal’s publication record includes numerous papers in reputable journals, reflecting his commitment to advancing knowledge in his field. His technical skills in programming and software further enhance his research capabilities, making him a valuable asset to academia and industry.

Profile

Education

Dr. Abid Iqbal is a highly accomplished academic with a solid educational foundation in electrical and electronics engineering. He earned his Ph.D. from the Queensland Micro- and Nanotechnology Centre at Griffith University, Australia, from April 2013 to February 2017. His doctoral research focused on the design, fabrication, and analysis of aluminum nitride (AlN)/silicon carbide (SiC)-based piezoelectric energy harvesters, contributing significantly to renewable energy technologies. Prior to his Ph.D., Dr. Iqbal completed his Master’s degree in Electronics Engineering at the Ghulam Ishaq Khan Institute in Topi, Swabi, Pakistan, graduating with a remarkable GPA of 3.88/4 and securing the top position in his class. His academic journey began with a Bachelor’s degree in Electrical Engineering from the University of Engineering & Technology in Peshawar, Pakistan, where he was recognized as an outstanding student. Dr. Iqbal’s educational background reflects his dedication and expertise in his field, laying a strong foundation for his professional career.

Professional Experience

Dr. Abid Iqbal is an accomplished electrical engineer currently serving as an Assistant Professor at the University of Engineering and Technology Peshawar since August 2019. In this role, he has been instrumental in teaching undergraduate courses in Electrical Engineering, developing innovative teaching methods, and mentoring students on research projects. Prior to this position, he worked as an Electrical Design Engineer at Alliance Power and Data in Australia, focusing on ERGON and NBN projects. He also contributed to the development of embedded systems for individuals with disabilities while employed as an Electronic Engineer at Community Lifestyle Support. His research experience includes a significant role as a Research Assistant at Griffith University, where he worked on piezoelectric devices for harsh environments and gained expertise in various semiconductor fabrication processes. Additionally, he has served as a lecturer at Comsat Institute of Information Technology and worked as a research associate at the City University of Hong Kong, demonstrating a robust and diverse professional background in academia and industry.

Research Interest

Dr. Abid Iqbal’s research interests lie at the intersection of electrical engineering and artificial intelligence, focusing on the development of innovative technologies that enhance energy efficiency and improve healthcare outcomes. His work includes designing and fabricating advanced piezoelectric energy harvesters using AlN/SiC materials, aimed at harnessing renewable energy sources. Additionally, Dr. Iqbal is deeply involved in projects utilizing artificial intelligence for agricultural applications, such as real-time disease detection in crops, and developing telehealth systems that leverage IoT technology to monitor patient health remotely. He has a keen interest in embedded systems and the design of hardware for assistive technologies, including portable ventilators and muscle sensors for individuals with disabilities. Through his research, Dr. Iqbal aims to contribute to sustainable energy solutions and advancements in healthcare technology, fostering a multidisciplinary approach that integrates engineering principles with artificial intelligence for practical applications.

Research Skills

Dr. Abid Iqbal possesses a robust set of research skills that underscore his expertise in Electrical Engineering and artificial intelligence. His extensive experience in designing and fabricating piezoelectric energy harvesters highlights his proficiency in materials science and device characterization. Dr. Iqbal is adept at using advanced simulation tools such as COMSOL, Ansys, and Coventorware, which facilitate in-depth analysis and optimization of microelectromechanical systems (MEMS). His work on artificial intelligence applications in telehealth and agricultural systems showcases his ability to integrate machine learning techniques with practical engineering solutions. Additionally, Dr. Iqbal has a strong background in programming languages such as Python and MATLAB, enhancing his capability to develop innovative software solutions for complex engineering problems. His involvement in funded projects and numerous publications further illustrates his commitment to advancing research and contributing to knowledge in his field. Overall, Dr. Iqbal’s diverse skills position him as a valuable asset to any research team.

Award and Recognition

Dr. Abid Iqbal is a distinguished electrical engineer and academic known for his significant contributions to the field of electrical and electronics engineering. He has received multiple accolades for his research and academic excellence, including the IGNITE funding for four innovative projects focused on machine learning applications in health and agriculture. Dr. Iqbal was awarded publication scholarships and prestigious Griffith University PhD scholarships, recognizing his outstanding academic performance during his doctoral studies. Additionally, he ranked first among his peers in the Master’s program at Ghulam Ishaq Khan Institute, further demonstrating his commitment to excellence in engineering. His dedication to teaching and mentoring future engineers is evident in his role as an Assistant Professor at the University of Engineering and Technology Peshawar, where he has developed innovative curricula and guided numerous student research projects. Dr. Iqbal’s work has been widely published, contributing significantly to advancements in artificial intelligence, embedded systems, and renewable energy technologies.

Conclusion

Dr. Abid Iqbal is a highly qualified candidate for the Best Researcher Award, demonstrating exceptional expertise in Electrical Engineering and a strong commitment to research and education. His accomplishments in renewable energy research, successful project management, and dedication to mentoring future engineers make him a standout choice. While he has areas for growth, particularly in expanding collaborative networks and enhancing commercialization efforts, his current achievements and potential for future contributions position him as an inspiring figure in his field. This award would not only recognize his past efforts but also encourage his continued pursuit of excellence in research and education.

Publication Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Year: 2024
    • Journal: Results in Engineering
    • Volume/Page: 24, 102994
  2. Novel dual absorber configuration for eco-friendly perovskite solar cells: design, numerical investigations and performance of ITO-C60-MASnI3-RbGeI3-Cu2O-Au
    • Authors: Hasnain, S.M., Qasim, I., Iqbal, A., Amin Mir, M., Abu-Libdeh, N.
    • Year: 2024
    • Journal: Solar Energy
    • Volume/Page: 278, 112788

 

 

 

Mona Jamjoom | AI | Best Researcher Award

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Assoc Prof Dr. Mona Jamjoom | AI | Best Researcher Award

Assoc Prof Dr. Mona Jamjoom, Princess Nourah bint Abdulrahman University, Saudi Arabia

Assoc Prof Dr. Mona Jamjoom is an accomplished researcher in the field of artificial intelligence, recognized for her innovative contributions and impactful studies. With a strong focus on machine learning and data analytics, she has published numerous papers in leading journals and has been awarded the Best Researcher Award for her groundbreaking work. Mona is passionate about harnessing AI to solve complex problems and improve decision-making processes across various industries. Her commitment to advancing technology while addressing ethical considerations makes her a prominent figure in the AI community.

Profile:

Scholar

Academics:

Assoc Prof Dr. Mona Jamjoom holds a PhD in Artificial Intelligence from King Saud University, awarded in May 2016. She also earned her Master’s degree in Computer Science from the same institution in 2004, following her Bachelor’s degree in Computer Science, which she completed in 1992. Her academic background provides a strong foundation for her research and contributions to the field of AI.

Professional Experiences:

Assoc Prof Dr. Mona Jamjoom has extensive professional experience in academia. Since 2021, she has served as an Associate Professor at Princess Nourah bint Abdulrahman University in Riyadh, Saudi Arabia. Prior to this, she was an Assistant Professor at the same institution from 2017 to 2021. Mona began her academic career as a Lecturer at Princess Nourah bint Abdulrahman University from 2007 to 2016, and before that, she worked as a Teaching Assistant from 1998 to 2007. Her career in the field began in 1993, when she provided technical support at the university, further solidifying her commitment to education and technology.

Activities:

Assoc Prof Dr. Mona Jamjoom is actively engaged in various professional activities that enhance her contributions to the field of artificial intelligence. In 2024, she joined the work team at the Center for Advanced Studies in Artificial Intelligence at King Saud University, collaborating on the KSU AI Satellite Lab project with SDAIA. She served as an external examiner for a doctoral thesis on deep learning applications for visual pollution detection in Riyadh. Additionally, she reviewed applications for the Apple Developer Academy’s second challenge for female students and participated in consulting sessions during the Gulf Hackathon Program focused on AI in public education. Mona also acted as a consultant for the UNESCO project “AI Capacity Building in Arabic-speaking Countries,” supported by Huawei Technologies. She has reviewed numerous papers for ISI journals and attended the research day at Princess Nourah bint Abdulrahman University. Furthermore, she co-supervised a PhD student specializing in Cognitive Computing at Universiti Kuala Lumpur, Malaysia.

Publication Top Notes:

M. Adil, Z. Yinjun, M. M. Jamjoom, and Z. Ullah. “OptDevNet: An Optimized Deep Event-Based Network Framework for Credit Card Fraud Detection.” IEEE Access, vol. 12, pp. 132421-132433, 2024. doi: 10.1109/ACCESS.2024.3458944.

Rabbani, H., Shahid, M. F., Khanzada, T. J. S., Siddiqui, S., Jamjoom, M. M., Ashari, R. B., Ullah, Z., Mukati, M. U., and Nooruddin, M. “Enhancing Security in Financial Transactions: A Novel Blockchain-Based Federated Learning Framework for Detecting Counterfeit Data in Fintech.” PeerJ Computer Science, vol. 10, e2280, 2024.

Malik, M. S. I., Nawaz, A., and Jamjoom, M. M. “Hate Speech and Target Community Detection in Nastaliq Urdu Using Transfer Learning Techniques.” IEEE Access, 2024.

Kurtoğlu, A., Eken, Ö., Çiftçi, R., Çar, B., Dönmez, E., Kılıçarslan, S., Jamjoom, M. M., Abdel Samee, N., Hassan, D. S. M., and Mahmoud, N. F. “The Role of Morphometric Characteristics in Predicting 20-Meter Sprint Performance Through Machine Learning.” Scientific Reports, vol. 14, no. 1, 16593, 2024.

Shah, S. M. A. H., Khan, M. Q., Rizwan, A., Jan, S. U., Samee, N. A., and Jamjoom, M. M. “Computer-Aided Diagnosis of Alzheimer’s Disease and Neurocognitive Disorders with Multimodal Bi-Vision Transformer (BiViT).” Pattern Analysis and Applications, vol. 27, no. 3, 76, 2024.

Ishtiaq, A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Product Helpfulness Detection with Novel Transformer Based BERT Embedding and Class Probability Features.” IEEE Access, 2024.

Abbas, M. A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection from Social Media.” IEEE Access, 2024.

Elhadad, A., Jamjoom, M., and Abulkasim, H. “Reduction of NIFTI Files Storage and Compression to Facilitate Telemedicine Services Based on Quantization Hiding of Downsampling Approach.” Scientific Reports, vol. 14, no. 1, 5168, 2024.

Malik, M. S. I., Younas, M. Z., Jamjoom, M. M., and Ignatov, D. I. “Categorization of Tweets for Damages: Infrastructure and Human Damage Assessment Using Fine-Tuned BERT Model.” PeerJ Computer Science, vol. 10, e1859, 2024.

Malik, M. S. I., Nawaz, A., Jamjoom, M. M., and Ignatov, D. I. “Effectiveness of ELMo Embeddings and Semantic Models in Predicting Review Helpfulness.” Intelligent Data Analysis, (Preprint), 1-21, 2023.

Ali Ghandi | Artificial intelligence | Best Researcher Award

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Ali Ghandi | Artificial intelligence | Best Researcher Award

PhD, Sharif University of Technology, Iran.

Ali Ghandi is an innovative researcher and educator specializing in Artificial Intelligence, particularly in reinforcement learning and generative AI. Currently pursuing his Ph.D. at Sharif University of Technology, he is known for his groundbreaking work that enhances reinforcement learning processes by leveraging side-channel data. Ali’s academic journey began with a B.Sc. in Digital System Design, followed by an M.Sc. in Machine Learning, where he excelled as one of the top students. He has taught courses in Neural Networks and Deep Generative Models, effectively sharing his knowledge with students. His research has been recognized through publications in reputable journals and presentations at significant conferences, such as the Iran Workshop on Communication and Information Theory. Ali’s accomplishments include a top rank in a national entrance exam and membership in Iran’s National Elites Foundation, underscoring his exceptional capabilities and contributions to the field of AI and his commitment to advancing technology for practical applications.

Profile:

 

Education

Ali Ghandi has an impressive academic background in electrical and computer engineering, with a particular focus on Artificial Intelligence. He is currently pursuing a Ph.D. at Sharif University of Technology (SUT) in Tehran, where he is conducting innovative research aimed at improving reinforcement learning processes using side-channel data. Prior to his doctoral studies, Ali earned his Master’s degree in Machine Learning from SUT, where his thesis focused on analyzing IoT systems through location-based data, effectively modeling traffic based on dynamic maps and registered commutes. He completed his Bachelor’s degree in Digital System Design at the same university, where he developed an online coordinate system for managing thermal loads in IoT applications. Throughout his educational journey, Ali has consistently demonstrated academic excellence, evidenced by his top rankings in national examinations and competitive academic events, establishing him as a leading figure among his peers in the field of electrical engineering and AI.

Professional Experiences

Ali Ghandi has an impressive academic background in electrical and computer engineering, with a particular focus on Artificial Intelligence. He is currently pursuing a Ph.D. at Sharif University of Technology (SUT) in Tehran, where he is conducting innovative research aimed at improving reinforcement learning processes using side-channel data. Prior to his doctoral studies, Ali earned his Master’s degree in Machine Learning from SUT, where his thesis focused on analyzing IoT systems through location-based data, effectively modeling traffic based on dynamic maps and registered commutes. He completed his Bachelor’s degree in Digital System Design at the same university, where he developed an online coordinate system for managing thermal loads in IoT applications. Throughout his educational journey, Ali has consistently demonstrated academic excellence, evidenced by his top rankings in national examinations and competitive academic events, establishing him as a leading figure among his peers in the field of electrical engineering and AI.

 

Research skills

Ali Ghandi possesses a strong set of research skills that position him as a leading figure in the field of Artificial Intelligence. His primary focus is on reinforcement learning, where he has developed innovative approaches, such as utilizing side-channel data to enhance the learning process. Ali’s expertise extends to deep generative models, where he explores the potential of generative AI in various applications. Additionally, he is adept at massive data mining, allowing him to extract valuable insights from large datasets, which is crucial in today’s data-driven world. His research also includes analyzing IoT systems, particularly in modeling traffic using location-based data. This multifaceted skill set enables Ali to approach complex problems with a comprehensive perspective, combining theoretical knowledge with practical applications. His ability to publish in reputable journals and present at conferences demonstrates his commitment to advancing the field and contributing to the academic community.

 

Awards And Recoginition

Ali Ghandi has received numerous accolades that underscore his academic excellence and contributions to the field of Artificial Intelligence. He achieved a remarkable 68th rank in a highly competitive university entrance exam, placing him among the top candidates out of 250,000 participants. His outstanding performance in the International A-lympiad, where he ranked third, showcases his proficiency in applied mathematics within a global context. Additionally, Ali has been a member of Iran’s National Elites Foundation since 2013, reflecting his recognition as a leading talent in his field. His academic journey at Sharif University of Technology has been marked by multiple distinctions, including first place among students in his Digital Systems minor and second place among all M.Sc. Electrical Engineering students. These honors highlight Ali’s commitment to excellence in research and education, positioning him as a promising contributor to the advancement of Artificial Intelligence.

Conclusion

In conclusion, Ali Ghandi possesses a solid foundation of academic excellence, innovative research, and early recognition in his field. His focus on advanced topics within AI positions him well for the Best Researcher Award. By addressing areas for improvement, such as increasing the practical impact of his work and expanding his collaborative efforts, Ali can further enhance his candidacy for this prestigious recognition. His commitment to advancing knowledge in AI and machine learning makes him a strong contender for the award.

Publication Top Notes

  • Title: Ex-RL: Experience-based Reinforcement Learning
    Authors: Ghandi, A., Shouraki, S.B., Gholampour, I., Kamranian, A., Riazati, M.
    Year: 2025
    Citation: Information Sciences, 689, 121479 📚🤖
  • Title: Deep ExRL: Experience-Driven Deep Reinforcement Learning in Control Problems
    Authors: Ghandi, A., Shouraki, S.B., Riazati, M.
    Year: 2024
    Citation: 12th Iran Workshop on Communication and Information Theory (IWCIT 2024) 📄🔍

Fahd Alharithi | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Department chair at Taif University, Saudi Arabia

Dr. Fahd Saad Alharithi is an accomplished researcher and academic with a Ph.D. in Computer Science from Florida Institute of Technology and extensive experience in both teaching and research. Currently an Assistant Professor at Taif University, his research spans a wide array of topics, including medical data categorization, oil spill detection, COVID-19 diagnosis, and IoT security. Dr. Alharithi has published numerous papers in high-impact journals such as Sensors and Remote Sensing, showcasing his innovative approaches and significant contributions to his field. In addition to his research, he has a strong background in teaching, having served as a lecturer and teaching assistant at various institutions. His involvement in volunteer work and leadership roles further highlights his commitment to community service. While his diverse research and impactful publications are noteworthy, highlighting research grants and awards could strengthen his profile for recognition.

Profile

Education

Dr. Fahd Saad Alharithi completed his educational journey with a strong foundation in Computer Science. He earned his Ph.D. from the Florida Institute of Technology, USA, in 2019, where he focused on advanced topics in the field. Prior to that, he obtained his Master of Science degree in Computer Science from the University of New Haven, USA, in 2013. His academic journey began with a Bachelor of Science degree in Computer Science from Taif University, Saudi Arabia, in 2008. This comprehensive educational background, spanning both international and local institutions, has equipped Dr. Alharithi with a robust theoretical and practical understanding of Computer Science, paving the way for his subsequent research and teaching career. His diverse educational experiences contribute significantly to his expertise and innovative approaches in the field.

Professional Experience

Dr. Fahd Saad Alharithi has garnered extensive experience in academia and education, currently serving as an Assistant Professor in the Computer Science Department at Taif University since 2019. His career began with roles as a Lecturer and Teacher Assistant at Taif University and the University of New Haven, where he honed his teaching and research skills. Dr. Alharithi has also contributed as a Trainer at New Horizons Institute, showcasing his versatility in the field. His professional journey is marked by significant research achievements, including innovative publications in medical data categorization, AI-assisted algorithms, and IoT security. His role extends beyond teaching, encompassing volunteer work with the Hemaya Group and leadership positions like President of the Saudi Student Club. Dr. Alharithi’s career reflects a robust blend of research excellence, educational dedication, and active community involvement.

Research Interest

Dr. Fahd Saad Alharithi’s research interests primarily focus on advancing computational methods and applications across various domains. His work explores medical data categorization using flexible mixture models, oil spill detection through SAR image analysis, and the development of hybrid convolutional neural network models for diagnosing diseases from chest X-ray images. Dr. Alharithi is also deeply involved in enhancing IoT security with AI-assisted bio-inspired algorithms and addressing environmental challenges through intelligent garbage detection systems. His research extends to secure communication protocols and energy-efficient solutions for sensor networks, demonstrating a strong emphasis on both practical and theoretical advancements. By integrating innovative methodologies such as deep learning and AI, Dr. Alharithi aims to address complex problems in medical imaging, environmental monitoring, and network security, reflecting a broad and impactful approach to computational science.

Research Skills

Dr. Fahd Saad Alharithi exhibits a robust set of research skills, underscored by his extensive work in computer science and related fields. His proficiency in advanced methodologies, including deep learning, AI-assisted algorithms, and hybrid models, highlights his capacity for innovative problem-solving. Dr. Alharithi’s experience with diverse data types and applications, such as medical data categorization, oil spill detection, and IoT security, demonstrates his ability to tackle complex, interdisciplinary challenges. His strong analytical skills are evident from his impactful publications in high-impact journals like Sensors and Remote Sensing. Additionally, his adeptness in leveraging various computational techniques and his commitment to exploring novel solutions further underscore his research capabilities. Dr. Alharithi’s contributions reflect a deep understanding of both theoretical and practical aspects of his field, positioning him as a skilled researcher with a significant impact on advancing technology and knowledge.

Award and Recognition

Dr. Fahd Saad Alharithi’s research has garnered considerable recognition within the academic community. He has published extensively in high-impact journals, including Sensors, Remote Sensing, and Computers, Materials & Continua, showcasing his significant contributions to fields such as medical data categorization, oil spill detection, and AI-assisted algorithms. His innovative work, particularly in developing hybrid convolutional neural network models and intelligent systems for garbage detection, underscores his leadership in advancing technology. Although specific awards and formal recognitions are not detailed in his resume, Dr. Alharithi’s influential publications and his role in mentoring and educating future researchers highlight his exceptional impact in computer science. His involvement in volunteer activities and community service further demonstrates his commitment to fostering academic and professional excellence.

Conclusion

Dr. Taimoor Asim is a strong candidate for the Best Researcher Award due to his substantial contributions to Mechanical Engineering, particularly in fluid dynamics and renewable energy systems. His extensive research experience, leadership roles, and professional achievements make him a noteworthy contender. To strengthen his candidacy, he could focus on broadening his research impact, exploring diverse research areas, and enhancing community engagement related to his work. Overall, Dr. Asim’s profile reflects a high level of expertise and dedication, aligning well with the criteria for the Best Researcher Award.

Publications Top Notes

  1. Machine learning approaches for advanced detection of rare genetic disorders in whole-genome sequencing
    • Authors: Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Volume: 106, pp. 582–593
  2. IoT-enabled healthcare systems using blockchain-dependent adaptable services
    • Authors: Arul, R., Alroobaea, R., Tariq, U., Alharithi, F.S., Shoaib, U.
    • Journal: Personal and Ubiquitous Computing
    • Year: 2024
    • Volume: 28(1), pp. 43–57
    • Citations: 13
  3. A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)
    • Authors: Hussein, L.F., Abass, I.A.M., Aissa, A.B., Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 76, pp. 349–360
    • Citations: 1
  4. Performance Analysis of Machine Learning Approaches in Automatic Classification of Arabic Language
    • Authors: Alharithi, F.S.
    • Journal: Information Sciences Letters
    • Year: 2023
    • Volume: 12(3), pp. 1563–1578
    • Citations: 1
  5. A blockchain-based hybrid platform for multimedia data processing in IoT-Healthcare
    • Authors: Taloba, A.I., Elhadad, A., Rayan, A., Alharithi, F.S., Park, C.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 65, pp. 263–274
    • Citations: 74
  6. Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements
    • Authors: Kumar, P., Swarnkar, N.K., Mahela, O.P., Mazon, J.L.V., Alharithi, F.S.
    • Journal: International Transactions on Electrical Energy Systems
    • Year: 2023
    • Volume: 2023, 6315918
    • Citations: 1
  7. Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
    • Authors: Gupta, N., Gupta, K., Qahtani, A.M., Singh, A., Goyal, N.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Volume: 11(23), 3932
    • Citations: 4
  8. NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange
    • Authors: Dogra, V., Alharithi, F.S., Álvarez, R.M., Singh, A., Qahtani, A.M.
    • Journal: Systems
    • Year: 2022
    • Volume: 10(6), 233
    • Citations: 7
  9. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach
    • Authors: Hamdi, Y., Boubaker, H., Rabhi, B., Dhahri, H., Alimi, A.M.
    • Journal: Engineering Science and Technology, an International Journal
    • Year: 2022
    • Volume: 35, 101215
    • Citations: 6
  10. A software for thorax images analysis based on deep learning
    • Authors: Almulihi, A.H., Alharithi, F.S., Mechti, S., Alroobaea, R., Rubaiee, S.
    • Book Chapter: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
    • Year: 2022
    • Pages: 1166–1178