Sara A. Shehab | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Sara A. Shehab | Artificial Intelligence | Best Researcher Award

Faculty Of Computer And Artificial Intelligence | Egypt

Assoc. Prof. Dr. Sara A. Shehab  is an Associate Professor in Computer Science at the University of Sadat City, Egypt, with expertise spanning artificial intelligence, bioinformatics, computational biology, quantum computing, and computer security. Her research focuses on developing intelligent algorithms for biological data analysis, optimization, and machine learning applications in medicine and environmental sustainability. She has contributed significantly to the advancement of multiple sequence alignment techniques, parallel and dynamic algorithms, and predictive modeling using machine learning. Her recent work explores deep learning for biomedical image analysis, explainable AI for green energy production, and hybrid optimization approaches for precision classification and prediction tasks. Dr. Shehab has published extensively in peer-reviewed international journals and conferences, collaborating with leading scholars in AI-driven bioinformatics and sustainable computing. She also serves as a reviewer for international journals and conferences, contributing to the academic community through quality evaluation and mentorship. Her professional experience includes leadership in e-learning, digital transformation, and program coordination within higher education, reflecting a strong integration of research, teaching, and institutional development. Through her interdisciplinary approach, she bridges artificial intelligence with biological and environmental sciences, fostering innovation in intelligent systems for healthcare, sustainability, and data-driven decision-making.

Profile: Google Scholar

Featured Publications

Shehab, S. A., Keshk, A., & Mahgoub, H. (2012). Fast dynamic algorithm for sequence alignment based on bioinformatics. International Journal of Computer Applications, 37(7), 54–61.

Ahmed, R. A. E. H., Shehab, S. A., Elzeki, O. M., & Darwish, A. (2024). An explainable AI for green hydrogen production: A deep learning regression model. International Journal of Hydrogen Energy, 83, 1226–1242.

Shehab, A. E. H. S., Mohammed, K. K., & Darwish, A. (2024). Deep learning and feature fusion-based lung sound recognition model to diagnose respiratory diseases. Soft Computing.

Shehab, A. E. H. S., & Darwish, A. (2023). Water quality classification model with small features and class imbalance based on fuzzy rough sets. Environment, Development and Sustainability.

Shehab, S., Shohdy, S., & Keshk, A. E. (2017). PoMSA: An efficient and precise position-based multiple sequence alignment technique. arXiv preprint arXiv:1708.01508.

Benitha Christinal J | Computer Science | Women Researcher Award

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Mrs. Benitha Christinal J | Computer Science | Women Researcher Award

Assistant Professor | Presidency University | India

Mrs. Benitha Christinal J is an accomplished academic and researcher specializing in Computer Science and Engineering with a strong focus on Artificial Intelligence, Deep Learning, and Internet of Things (IoT). She has extensive professional experience in higher education, demonstrating excellence in teaching, curriculum development, and academic coordination. Her research interests include deep learning applications for cybersecurity, decentralized systems, and intelligent data analysis. She has published numerous papers in reputed international journals such as Oxidation Communications, Ain Shams Engineering Journal, Journal of Supercomputing, and Optical Fiber Technology, addressing challenges in areas like federated learning, SDN-IoT security frameworks, and evolutionary intrusion detection systems. She has also presented her work at several international conferences, contributing to advancements in AI-based healthcare, blockchain-enabled sustainability, and smart network optimization. A published author of a textbook on Database Management Systems, she has guided multiple undergraduate and postgraduate projects that have gained recognition at academic and professional levels. Her technical proficiency spans programming languages like Python, Java, and C++, and tools for web and data driven applications. Beyond research and teaching, she has been actively involved in organizing academic events, fostering industry collaborations, and mentoring students toward innovation. Her commitment to advancing technology education and research underscores her vision of shaping the next generation of computer science professionals through excellence, creativity, and applied intelligence.

Profiles: Scopus | Orcid

Featured Publications

Benitha Christinal, J., Betsee Natasha, A., Nivethitha, M., Asmitha, E., & Kaviya, N. (2025). A modern generative AI framework for Alzheimer detection leveraging autoencoders and softmax classifier. In Proceedings of the 3rd International Conference on Augmented Intelligence and Sustainable Systems (ICAISS 2025). IEEE.

Benitha Christinal, J., Jagadeesh, S., Ajai, M., Lakshman, A., & Betsee Natasha, A. (2025). Memory Montage: Amnesia support appa. In Proceedings of the International Conference on Emerging Trends in Engineering and Technology (ICETET 2025). IEEE.

Benitha Christinal, J., & Ameelia Roseline, A. (2025, September). Securing SDON with hybrid evolutionary intrusion detection system: An ensemble algorithm for feature selection and classification. Optical Fiber Technology, 104206.

Benitha Christinal, J., Chandran, V., Srinic, J., & Prasannasrinivasan, A. (2024). A distributed node clustering coalition game for mobile ad hoc networks. In Proceedings of the Asia Pacific Conference on Innovation in Technology (APCIT 2024). IEEE.

Sumanth, V., Anitha, K., Christinal, J. B., Sekhar, G. S., Khekare, G., Patil, H., Kumar, N. M., & Rajaram, A. (2024). Advanced communications and networking for environmental protection monitoring in remote wilderness areas. Journal of Environmental Protection and Ecology, 25(3), 1012–1023.

Mostafa Gamal | Artificial Intelligence | Best Researcher Award

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Mr. Mostafa Gamal | Artificial Intelligence | Best Researcher Award

Egyptian Russian University | Egypt

Mr. Mostafa Gamal, is a dedicated researcher and academic specializing in artificial intelligence, machine learning, and natural language processing, with a particular focus on text summarization and semantic graph-based models. His research explores the integration of deep learning, swarm intelligence, and optimization algorithms to enhance automated summarization and intelligent decision-making systems. He has contributed to several high-impact journals, including IEEE Access, Results in Engineering, Discover Cities, and the International Journal of Data Science and Analytics, covering areas such as transformer architectures, reinforcement learning, and graph neural networks. Mr. Gamal’s work advances the field of AI through the development of novel, explainable, and efficient models for NLP applications and autonomous systems. Beyond research, he is actively involved in academic teaching and professional training, fostering AI literacy through programs with the Egyptian Russian University, Huawei Academy, and the Digital Egypt Cubs Initiative. His technical expertise spans TensorFlow, PyTorch, and Keras, alongside proficiency in Python and data analytics frameworks. With a strong foundation in applied AI, he bridges theoretical research with practical implementation, contributing to the development of intelligent systems that address real-world challenges. His scholarly and instructional activities reflect a commitment to advancing artificial intelligence education and applied innovation in computational sciences.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, December). GRAYSUM: Gray Wolf optimized multi-level semantic graph summarization. Results in Engineering, (2025), 107275.

Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, October). Abstractive text summarization using deep learning models: A survey. International Journal of Data Science and Analytics.

Gamal, M., & Ibrahim, O. A. (2025, October 24). Graph neural networks for real-time optimization of autonomous urban transit systems. Discover Cities.

Gamal, M. M., Abdul Salam, M., Sweidan, S., & Hamed, H. F. A. (2025, May 1). ACOSUM: Ant colony optimized multi-level semantic graph summarization. International Journal of Applied Intelligent Computing and Informatics.

Abdul Salam, M., Aldawsari, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2024). Improving Arabic text summarization using advanced pre-trained models. Journal of Southwest Jiaotong University, 59(3), Article 5.

Irina Karabulatova | Artificial Intelligence | Best Researcher Award

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Prof. Dr. Irina Karabulatova | Artificial Intelligence | Best Researcher Award

Professor | Heilongjiang University | China

Prof. Dr. Irina S. Karabulatova is an internationally recognized philologist, linguist, and academician known for her pioneering research in applied linguistics, psycholinguistics, neurolinguistics, sociolinguistics, media linguistics, computational psycholinguistics, and digital humanities. She serves as Head of the Research Center for Digital Humanities at Heilongjiang University, Research Professor at RUDN-University, and Senior Researcher at Moscow State University’s Institute for Advanced Research in AI. She has trained more than sixty doctoral and PhD students from multiple countries, authored nearly five hundred publications across leading journals, and contributed to global knowledge in language, brain studies, NLP, emotional artificial intelligence, and cross-cultural communication. She is an elected member of the Russian and European Academies of Natural Sciences, with global academic influence spanning Russia, China, Europe, India, and Kazakhstan. Her career combines rigorous scientific scholarship with cultural preservation, academic leadership, and contributions to international collaboration in linguistics, AI, and intercultural communication.

Profile

Scopus

Orcid

Education

Prof. Dr. Irina Karabulatova graduated with honors in philology from Arkalyk State Pedagogical Institute with a specialization in Russian language and literature. Her early academic focus was on toponymy and linguistic geography, culminating in her candidate dissertation on hydronyms of the Russian Rim, which established her as a rising scholar in Russian linguistics. She later defended her doctoral dissertation at Kuban State University on Russian toponymy in an ethno-psycholinguistic framework, combining theoretical linguistics with cultural identity studies. Her academic formation was marked by recognition from leading foundations supporting research excellence in culture and creativity. She pursued multiple advanced qualifications in philology and linguistics and was awarded the titles of associate professor and later full professor by the Higher Attestation Commission of the Russian Federation. Over her academic journey, she complemented her education with international internships in migration studies, cultural sociology, translation studies, and digital technologies, strengthening her interdisciplinary expertise in linguistics and humanities.

Professional Experience

Prof. Dr. Irina Karabulatova’s professional career spans academia, research, and international collaboration. She began as lecturer and professor at Russian universities before holding leadership positions at Tyumen State University, Kazan Federal University, and RUDN-University. She has served as professor, head of departments, and director of interdisciplinary research centers, combining linguistics with digital technologies, cultural studies, and artificial intelligence. Internationally, she has been visiting professor at universities in Kazakhstan, Turkey, China, Italy, and the United States, delivering courses on psycholinguistics, intercultural communication, digital linguistics, and verification of manipulative media markers. She has held senior research positions at Moscow State University, MIPT, and institutes of the Russian Academy of Sciences. Currently, she leads the Research Center for Digital Humanities at Heilongjiang University, China, where her work integrates NLP, emotional intelligence, and neurocognitive modeling. Her teaching, research supervision, and scientific expertise reflect global recognition, with doctoral students guided under her supervision across multiple continents.

Awards and Honors

Prof. Dr. Irina Karabulatova has received numerous prestigious awards and honors recognizing her contributions to philology, cultural preservation, and interdisciplinary research. She is a laureate of the N. Roerich International Prize for preservation of cultural values and peacemaking, and an Honored Worker of Culture of Kazakhstan. She has been awarded multiple national and international prizes including the All-Russian public award “Success” for women leaders in science, culture, and education, as well as certificates of honor and gratitude from universities, regional authorities, and cultural institutions in Russia, Kazakhstan, and Israel. Her achievements are highlighted by listings in major encyclopedias documenting leading migrationologists and psycholinguists of Russia. She has been recognized by academic, cultural, and governmental institutions for her scholarly books, research contributions, and active promotion of intercultural understanding. Her honors reflect her pioneering role in applied linguistics, psycholinguistics, media linguistics, cultural heritage, and the development of interdisciplinary fields in the digital humanities.

Research Focus

Prof. Dr. Irina Karabulatova’s research focus spans applied linguistics, psycholinguistics, neurolinguistics, sociolinguistics, migration studies, computational linguistics, NLP, sentiment analysis, emotionology, and digital humanities. She is credited with founding new applied branches of linguistics such as digital linguomigration, predictive onomastics, digital folkloristics, and academic emotionology. Her work investigates neuro-psycholinguistic mechanisms of communication, emotional intelligence, and emotional artificial intelligence. She has analyzed the transformation of linguistic consciousness among diasporas, bilingualism and ASD differentiation, social schizophrenia in aggressive media environments, and manipulative markers in mass communication. Her interdisciplinary projects address verification and detection of manipulative discourse, psycholinguistic expertise of digital texts, and digital profiling for sociocultural security. She integrates AI and machine learning into linguistics to model language, brain, and cognition interactions. Her current research emphasizes the preservation of ethnocultural codes, neurocognitive modeling of bilinguals, and the development of computational methods for automatic analysis of potentially dangerous discourses in media and intercultural communication.

Publication

Neuromorphic Elements as a First Step Towards Sociomorphic Systems
Year: 2025

The interpretations of Russian traditional song folklore in the Internet virtual space in the aspect of digital linguistic folklore studies
Year: 2025

Sociomorphic Neuromodeling in Academic Emotionology as an Integration of Neurocognitive and Psycholinguistic Knowledge in Artificial Intelligence
Year: 2025

Metaphorical Terminology in Ancient Texts of Traditional Chinese Medicine: Problems of Understanding and Translation
Year: 2024

Modeling the Socio-Economic and Demographic Development of Transborder Regions (The Example of the Russian-Chinese Border Territories)
Year: 2024

Conclusion

Prof. Dr. Irina S. Karabulatova is highly suitable for recognition through a research award, given her groundbreaking contributions, global academic engagement, and leadership in emerging fields of linguistics and digital humanities. Her innovative approaches to language, cognition, and artificial intelligence mark her as a distinguished scholar whose work continues to shape contemporary linguistic science and intercultural studies, making her a deserving candidate for international academic honors.

Aiswarya Nair | Artificial Intelligence | Women Researcher Award

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MS. Aiswarya Nair | Artificial Intelligence | Women Researcher Award

Aiswarya Anil Nair is a Machine Learning Engineer with a strong background in AI, computer vision, and natural language processing. She holds a B.Tech in Computer Science (AI & ML) and is currently pursuing a PG Diploma in Applied Statistics. With hands-on experience at Optisol, Triwizard Technologies, and Tata Elxsi, she has developed and deployed end-to-end AI solutions. Her research has been presented at international conferences and published in reputed journals, with a focus on ethical AI and generative technologies. Aiswarya is passionate about building intelligent systems that solve real-world problems.

National Open University, India.

Author Profile

GOOGLE SCHOLAR

Education 🎓

Aiswarya Anil Nair is currently pursuing a Postgraduate Diploma in Applied Statistics from Indira Gandhi National Open University, starting in 2024. She completed her Bachelor of Technology in Computer Science with a specialization in Artificial Intelligence and Machine Learning from Sree Chitra Thirunal College of Engineering in 2024, graduating with a CGPA of 8.63 out of 10.

Professional Experience 💼

Aiswarya is currently working as a Machine Learning Engineer at Optisol Business Solutions in Chennai, Tamil Nadu, where she focuses on agent orchestration and developing various proof-of-concept solutions. Prior to this, she served as a Machine Learning Engineer at Triwizard Technologies in Trivandrum, Kerala, where she built and deployed a computer vision model for plant disease detection using FastAPI and AWS and also explored tools for visualizing GitHub collaboration within teams. She also completed an internship at Tata Elxsi from October 2023 to June 2024, where she gained experience in automotive systems, particularly in ADAS, AI, and deep learning technologies.

Technical Skills 🛠️

Aiswarya is proficient in programming languages such as Python, Java, C, and SQL. Her technical toolkit includes libraries like TensorFlow, OpenCV, Keras, Numpy, Sklearn, and Pandas. She has hands-on experience in machine learning, deep learning, generative AI, and natural language processing. Alongside her technical expertise, she possesses strong interpersonal skills which complement her ability to work effectively in team settings.

Awards & Honors 🏅

Aiswarya has earned recognition for her impactful research and innovative contributions in artificial intelligence. Her paper titled “GenAI Empowered Script to Storyboard Generator” was presented at the prestigious 2024 IEEE International Conference on Future Machine Learning and Data Science in Sydney. She also co-authored the publication “LangChain and NeMo Guardrail Integrated Ethical Framework for Large Language Model Based Healthcare Chatbot,” which appeared in the Journal of AI and Ethics. These accolades highlight her dedication to responsible AI and her ability to deliver real-world solutions grounded in research excellence.

Research Interests 🔍

Her primary research interests lie at the intersection of artificial intelligence, human-centered design, and ethical machine learning. She has explored applications of reinforcement learning in education, computer vision in law enforcement and agriculture, and language models in personal assistants and healthcare. Aiswarya’s work is marked by a focus on scalable, ethical, and adaptive AI systems, emphasizing innovation with real-world impact.

Publications Top Notes: 📝

Title: An Integrated Framework for Ethical Healthcare Chatbots Using LangChain and NeMo Guardrails
Authors: G. Arun, R. Syam, A. A. Nair, S. Vaidya
Year: 2025
Journal: AI and Ethics, Pages 1–12

 Title: GenAI Empowered Script to Storyboard Generator
Authors: A. Govind, A. Anzar, A. A. Nair, R. Syam
Year: 2024
Journal: 2024 IEEE International Conference on Future Machine Learning and Data Science

Wen-Chung Tsai | Computer Science and Artificial Intelligence | Best Researcher Award

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Prof. Dr. Wen-Chung Tsai | Computer Science and Artificial Intelligence | Best Researcher Award

Associate Professor National Taichung University of Science and Technology Taiwan

Dr. Wen-Chung Tsai is an esteemed academic and researcher specializing in electronics engineering and computer science. He obtained his Ph.D. from National Taiwan University and has extensive experience in both academia and industry. Currently, he serves as an Associate Professor at the National Taichung University of Science and Technology, focusing on embedded systems, AI, and information security.

Profile

Scopus

Google Scholar

Orcid

🎓 Education

  • Ph.D. in Electronics Engineering – National Taiwan University (2006–2011)

  • M.S. in Electrical Engineering – National Cheng Kung University (1996–1998)

  • B.S. in Computer Science & Information Engineering – Tamkang University (1992–1996)

💼 Experience

  • Associate Professor – National Taichung University of Science and Technology (2022–present)

  • Associate Professor – Chaoyang University of Technology (2020–2022)

  • Assistant Professor – Chaoyang University of Technology (2013–2020)

  • Engineer – Industrial Technology Research Institute (2011–2013)

  • Visiting Scholar – University of Wisconsin-Madison (2010)

  • Deputy Manager – VIA Technologies (2000–2009)

🔬 Research Interests

  • Embedded Systems & Internet of Things

  • Software & Hardware Design Integration

  • Artificial Intelligence & Information Security

  • Wireless Networks & Communication Protocols

📚 Publications Top Notes:

Field-Programmable Gate Array-Based Implementation of Zero-Trust Stream Data Encryption for Enabling 6G-Narrowband Internet of Things Massive Device Access

Anticipative QoS Control: A Self-Reconfigurable On-Chip Communication

Automatic Key Update Mechanism for Lightweight M2M Communication and Enhancement of IoT Security: A Case Study of CoAP Using Libcoap Library

Network-Cognitive Traffic Control: A Fluidity-Aware On-Chip Communication

Implementatons of Health-Promotion IoT Devices for Secure Physiological Information Protection

Anticipative QoS Control: A Self-Reconfigurable On-Chip Communication

3D Bidirectional-Channel Routing Algorithm for Network-Based Many-Core Embedded Systems

Bi-routing: a 3D bidirectional-channel routing algorithm for network-based many-core embedded systems

A Configurable Networks-on-Chip Router Using Altera FPGA and NIOS2 Embedded Processor

Analysis of the relationship between the radial pulse and photoplethysmography based on the spring constant method

Abdelrhman BASSIOUNY | Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Abdelrhman BASSIOUNY | Computer Science and Artificial Intelligence | Best Researcher Award

University of Bremen Germany

Abdelrhman Bassiouny is a passionate Egyptian robotics researcher specializing in marine robotics, autonomous systems, and AI-powered disassembly. With international experience across Germany, France, and Egypt, he combines technical mastery in robotics with a strong academic background. He thrives in hands-on innovation, contributing to cutting-edge projects from underwater VSLAM to robotic e-waste disassembly. 🌊🤖

Profile

Research Gate

Scopus

🎓 Education

Abdelrhman is currently completing his Erasmus Mundus Joint Master’s Degree in Marine & Maritime Intelligent Robotics (MIR), where he studied at Université de Toulon (France) and Universidad Jaume I (Spain). He graduated with honors in Mechatronics & Automation Engineering from Ain Shams University, Egypt. He also expanded his knowledge through specialized online courses in Deep Learning, Self-Driving Cars, and Project Management. 📘🌍
🔗 Master MIR Program
🔗 Ain Shams University

🛠️ Experience

Abdelrhman brings versatile research and teaching experience:

  • Master Thesis Intern at University of Bremen (Germany): Developed a query interface and machine learning pipeline for NEEMs robotics database.

  • Underwater VSLAM Intern at Laboratoire COSMER (France): Benchmarked SLAM algorithms using BlueROV in collaboration with IFREMER.

  • Research Assistant at Ain Shams University (Egypt): Led autonomous robotic disassembly projects, winning 3rd place in Robothon 2021.

  • Teaching Assistant at Ain Shams University: Taught ROS-based robotic control and supervised final-year projects.
    🌐 LinkedIn | 🌍 Personal Website

🔬 Research Interests

Abdelrhman’s research centers on:

  • Autonomous Robotics & Human-Robot Interaction 🤝

  • Symbolic Reasoning & Knowledge Representation 🧠

  • Underwater SLAM and Marine Robotics 🌊

  • E-waste Disassembly Automation using AI ♻️

  • ROS, TensorFlow, and Vision-based Robotics 📷

🏆 Awards

  • 🥇 Best Scientific Methodology Award – RoboCup MSL 2022 (Thailand)
    ➤ RoboCup 2022 History

  • 🥈 Runner-Up – MIR Championship – Guerledus Challenge 2022
    ➤ Challenge Info

  • 🥉 3rd Place + Lightning Speed Award – Robothon Grand Challenge 2021 (TUM, Germany)
    ➤ Robothon Video

📚 Publications Top Notes: 

Prompt: Publications with hyperlinks, published year, journal (if applicable), and citation details in paragraph form.

Abdelrhman has authored two impactful research publications related to robotic disassembly of electronic waste:

“Comparison of Different Computer Vision Approaches for E-waste Components Detection to Automate E-waste Disassembly” (2021) – This paper evaluates vision-based algorithms for component detection, supporting more efficient and sustainable e-waste recycling.
🔗 View Publication
📈 Cited by: Google Scholar results

“Autonomous Non-Destructive Assembly/Disassembly of Electronic Components using A Robotic Arm” (2021) – Introduced a robotic system for semi-destructive disassembly using ROS and vision systems.
🔗 View Publication
📈 Cited by: Google Scholar results