Ali Alyatimi | Deep Learning | Best Research Article Award

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Mr. Ali Alyatimi | Deep Learning | Best Research Article Award

Associate Professor | The University of Sydney | Australia

Mr. Ali Alyatimiis a dedicated researcher and academic professional currently pursuing a PhD in Computer Science at the University of Sydney, specializing in deep learning and multi-omics data integration. With a solid interdisciplinary background in computer science, engineering technology, and artificial intelligence, Mr. Ali Alyatimi brings extensive experience in both research and teaching across data science, machine learning, and computer vision domains. His academic foundation includes advanced study in computational methods, database systems, and data-driven modeling, supported by expertise in programming languages such as Python, R, SQL, and MATLAB. His research focuses on developing multi-view deep learning frameworks that enhance biological data fusion and computational biology analysis, supervised by Dr. Vera Chung and Dr. Ali Anaissi. Before commencing doctoral research, he served as a lecturer and trainer in the Department of Computer Science at the College of Technology, Jizan, where he taught programming, database design, and computer network courses, guiding students in developing innovative, database-driven web applications using PHP and MySQL. His earlier research at the University of New England involved the design and implementation of illumination invariance techniques to improve weed detection in pastures using object detection models with YOLOv4 and TensorFlow, demonstrating the practical potential of deep learning in precision agriculture. Alongside research, he actively contributes to academic development through tutoring undergraduate courses in data science and computational methods at the University of Sydney. His current work integrates artificial intelligence, bioinformatics, and data fusion, aiming to advance computational modeling in healthcare and life sciences.

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VANI VATHSALA ATLURI | Machine Learning | Best Researcher Award

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Dr. VANI VATHSALA ATLURI | Machine Learning | Best Researcher Award

Professor and HOD | CVR College of Engineering | India

Dr. A. Vani Vathsala is a distinguished academician and researcher in the field of Computer Science and Engineering, currently serving as a Professor and Head of the Department of Computer Science and Engineering at CVR College of Engineering, Hyderabad. With a rich background spanning both academia and industry, including a foundational professional stint at Tata Consultancy Services, Dr. Vathsala has built a career marked by innovation, leadership, and impactful research. She holds a Ph.D. in Computer Science from the University of Hyderabad, preceded by a Master of Technology in Computer Science from the same university and a Bachelor’s degree in Computer Science and Engineering from Nagarjuna University. Her research portfolio reflects expertise in artificial intelligence, cloud computing, machine learning, data security, and sustainable computing systems. She has published extensively in Scopus and SCI-indexed journals, contributing to emerging technologies that bridge healthcare, security, and IoT-driven solutions. Her notable publications include Early Diagnosis for the Bacterial Infections for the Patients under the Medical Intervention of Automated Peritoneal Dialysis Using Machine Learning Techniques, A Cloud Integrity Verification and Validation Model Using Double Token Key Distribution Model, Energy-Efficient and Sustainable Cluster-Based Routing in IoT-Based WSNs Using Metaheuristic Optimization, and Enhanced Real-Time Surveillance and Suspect Identification Using CNN-LSTM Based Body Language Analysis.

Profile: Google Scholar 

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Zinah Saeed | Deep Learning | Best Researcher Award

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Ms. Zinah Saeed | Deep Learning | Best Researcher Award

Universiti Sains Malaysia | Iraq

Saeed ZR is a dedicated researcher and academic with a strong background in computer science, networking technology, and innovative applications of artificial intelligence, currently pursuing his doctoral studies in computer science at the School of Computer Sciences, Universiti Sains Malaysia, after completing a master’s degree in networking technology at Universiti Teknikal Malaysia Melaka and a bachelor’s degree in computer science at Mustansiriyah University in Baghdad, building his academic journey on a foundation of technical expertise and analytical thinking, his research interests cover metaheuristic algorithms, artificial intelligence, deep learning, gesture recognition, assistive technologies, human–computer interaction, and networking security, he has contributed to the academic community with impactful publications including a hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language, a systematic review on systems-based sensory gloves for sign language pattern recognition, and research on improving cloud storage security using three layers of cryptography algorithms, his professional journey includes significant teaching experience as a lecturer at the Iraqi Police Academy where he worked to advance education and training, and his ongoing research and doctoral studies have strengthened his ability to design, implement, and test intelligent systems addressing real-world challenges, his technical skills encompass proficiency in computer software, Microsoft Office applications, and operating systems across Windows and Mac environments, alongside practical programming expertise in Python for scripting and data processing, he is also experienced with widely used research and software tools such as Jupyter, Colab, Git, SPSS, and basic MATLAB, beyond his professional life he nurtures a passion for reading, research, and continuous learning, qualities that support his growth as a thoughtful academic and innovative researcher, his multidisciplinary focus, combined with a strong commitment to impactful scientific contributions, reflects a future-oriented career in advancing artificial intelligence and human-centered technologies.

Profile: Google Scholar

Featured Publications:

Saeed, Z. R., Ibrahim, N. F., Zainol, Z. B., & Mohammed, K. K. (2025). A hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language. Journal of Electrical and Computer Engineering, 2025(1), 6430675.

Saeed, Z. R., Zainol, Z. B., Zaidan, B. B., & Alamoodi, A. H. (2022). A systematic review on systems-based sensory gloves for sign language pattern recognition: An update from 2017 to 2022. IEEE Access, 10, 123358–123377.

Saeed, Z. R., Zakiah Ayop, N. A., & Baharon, M. R. (2018). Improved cloud storage security using three layers cryptography algorithms. International Journal of Computer Science and Information Security, 16(10), 11–18.

 

Sheeba Rachel S | Machine Learning | Best Researcher Award

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Mrs. Sheeba Rachel S | Machine Learning| Best Researcher Award

Assistant Professor | Sri Sai Ram Engineering College | India

  S. Sheeba Rachel has contributed extensively to the fields of artificial intelligence, machine learning, deep learning, healthcare technologies, smart devices, image processing, cloud computing, and Internet of Things with publications including Cardiovascular Disease Prediction Using Machine Learning and Deep Learning, Heart Disease Prediction of an Individual Using SVM Algorithm, Automated Driving License Testing System, Real-Time Face Detection and Identification Using Machine Learning Algorithm for Improving the Security in Public Places Using Closed Circuit Television, LEARNAUT – Upgraded Learning Environment and Web Application for Autism Environment Using AR-VR, VATTEN – A Smart Water Monitoring System, Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model, EDSYS – A Smart Campus Management System, TRACKME – Smart Watch for Women, Women’s Safety with a Smart Foot Device, Mental Health Monitoring Using Sentimental Analysis, Facilitation of Multipurpose Gloves for Impaired People, Extending OVS with Deep Packet Inspection Functionalities, Courier Service Management and Tracking Using Android Application, Detecting the Abandoned Borewell Using Image Processing, Smart Hospitals E-Medico Management System, ADROIT LIMB – Brain Controlled Artificial Limb, Autonomous Movable Packrat for Habitual Chores, Postal Bag Tracking and Alerting System, Applying Social Network Aided Efficient Live Streaming System for Reducing Server Overhead, Image Fusion of MRI Images Using Discrete Wavelet Transform, Probabilistic Flooding Based File Search in Peer to Peer Network, Multi Stage for Informative Gene Selection, Mutual Information in Stages for Informative Gene Selection, Computation of Mutual Information in Stages for Gene Selection from Microarray Data, and several other impactful studies in international journals and conferences indexed in Scopus, IEEE, and UGC; she has further contributed to innovation through consultancy projects such as AI-based pre-examination dental software and non-invasive sugar detection using eye retina, authored books and chapters including Fundamentals of Machine Learning, Management Analytics and Software Engineering, Recent Trends in Engineering and Technology – Edge Computing, and secured patents like Artificial Intelligence Based Heart Rate Monitoring Device for Sports Training, IOT Based Washing Machine for Agricultural Crops, Human Identity Recognition System Using Cloud Machine Learning and Deep Learning Algorithms, Gesture Based Anti-Rape Device, while also holding active memberships with IEEE, ISTE, IEI, UACEE, IAENG, and IACSIT; her academic journey has been marked by mentorship of award-winning projects, reviewer and session chair responsibilities in international conferences, and recognition such as the Best Faculty Advisor Award demonstrating her influence in advancing technology-driven solutions for healthcare, safety, smart systems, and education through research, teaching, patents, and community engagement.

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