Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

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Mrs. Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

North Dakota State University(NDSU) | United States

Umme Habiba is a dedicated researcher and educator in computer science whose work centers on machine learning, deep learning, transformer-based architectures, explainable AI, and swarm intelligence, particularly within medical data analysis. She is pursuing her Ph.D. and M.Sc. in Computer Science at North Dakota State University, where she has gained extensive teaching experience as an instructor of record and graduate teaching assistant across several undergraduate courses. Her research contributions span clinical text mining, medical risk prediction, brain–computer interface modeling, IoT security, and usability analysis of mHealth applications, with publications in reputable international journals. She has also collaborated on projects involving mobile sensor–based spatial analysis, voice-controlled IoT automation systems, and hybrid ML models for network intrusion detection. Her academic journey began with a bachelor’s degree in Computer Science and Engineering, where she developed a strong foundation in data-driven system design and intelligent applications. She has received consistently high teaching evaluations and has demonstrated a commitment to interdisciplinary research and student learning. Her long-term goal is to contribute impactful solutions at the intersection of artificial intelligence and healthcare while advancing as both a researcher and an educator.

Profile : Orcid

Featured Publication

PSO-optimized TabTransformer architecture with feature engineering for enhanced cervical cancer risk prediction, 2026

Basharat Ali | Cybersecurity Data Analysis | Best Researcher Award

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Dr. Basharat Ali | Cybersecurity Data Analysis | Best Researcher Award

Nanjing University | China

Dr. Basharat Ali is a dedicated researcher and PhD scholar in Computer Science at Nanjing University, China, with a strong academic foundation in Software Engineering from Northeastern University, China, and the University of Swat, Pakistan. His professional journey includes roles as a Software Developer at Neusoft (China) and RaidIT Solution (Pakistan), where he gained hands-on expertise in programming, system architecture, and cross-border e-commerce platforms. His research focuses on network security, blockchain development, IoT infrastructure protection, and the integration of deep learning techniques for cyber defense. Dr. Ali has published influential works such as “An Efficient E-Voting Algorithm and DApp Using Blockchain Technology” and “Towards a Secure Infrastructure for the IoT’s Using Deep Learning.” His scholarly contributions have achieved an h-index of 4, with 79 citations and 2 indexed documents, reflecting the growing impact of his work in secure digital ecosystems. He has also been recognized for his innovation and technical creativity in decentralized systems and smart contract applications. Combining academic research with practical software engineering and design expertise, Dr. Ali aims to advance global cybersecurity through intelligent, transparent, and scalable blockchain-based systems that shape the next generation of secure digital environments.

Profiles : Orcid | Google Scholar

Featured Publications

Ali, B., & Chen, G. (2025). Next-generation AI for advanced threat detection and security enhancement in DNS over HTTPS. Journal of Network and Computer Applications.

Ali, B. (2022). An Efficient E-Voting Algorithm and DApp Using Blockchain Technology.

Ali, B. (2021). Towards a Secure Infrastructure for the IoT’s Using Deep Learning. Multidisciplinary International Journal of Research and Development.

Rajesh Kumar Chaudhary | Artificial Intelligence | Best Researcher Award

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Mr. Rajesh Kumar Chaudhary | Artificial Intelligence | Best Researcher Award

Thapar Institute of Engineering and Technology | India

Mr. Rajesh Kumar Chaudhary is a dedicated and result-oriented academician, serving as an Assistant Professor in the Department of Computer Science and Engineering. With over five years of academic and research experience, he has established expertise in clustered federated learning, wireless sensor networks, nature-inspired optimization algorithms, and privacy-preserving distributed artificial intelligence. His professional journey reflects a blend of strong teaching acumen, impactful research contributions, and a commitment to student mentorship. By integrating cutting-edge research with pedagogical innovation, he has significantly contributed to both the academic and practical realms of computer science. His scholarly work has been published in leading international journals, positioning him as an emerging voice in the domain of distributed and intelligent systems.

Education

Mr. Chaudhary holds a solid academic foundation in Computer Science and Engineering. He is currently pursuing a doctoral degree in the discipline from a reputed institute, with his research focusing on advancing clustered federated learning through nature-inspired optimization techniques and privacy-preserving mechanisms. Prior to his doctoral studies, he completed a Master of Technology in Computer Science and Engineering from a recognized university, where he specialized in developing optimization-based solutions for networked systems. His undergraduate studies in Computer Science and Engineering laid the groundwork for his expertise in networking, algorithms, and distributed computing. His academic trajectory has been characterized by consistent excellence, deep engagement with emerging technologies, and a passion for continuous learning.

Experience

Mr. Chaudhary has served as an Assistant Professor in the Department of Computer Science and Engineering at a well-regarded university, where he played a pivotal role in both academic delivery and extracurricular technical initiatives. He has taught core and advanced subjects including Computer Networks, Cryptography, Theory of Automata, and Operating Systems. Beyond classroom teaching, he has supervised multiple student research projects in clustered federated learning, wireless sensor networks, and optimization algorithms, guiding them toward impactful academic outputs. He has also organized workshops, industrial training programs, and technical seminars to bridge the gap between academic knowledge and industry expectations. Recognized for his commitment to institutional development, he has twice received the Best Training Coordinator award for his exceptional coordination of student training and placement activities.

Research Interest

Mr. Chaudhary’s research interests encompass a range of advanced computing topics, with a central focus on clustered federated learning (CFL) — an emerging paradigm in distributed artificial intelligence. He is particularly interested in integrating nature-inspired optimization algorithms, such as grey wolf optimization, real-coded genetic algorithms, and artificial bee colony optimization, to enhance the performance, scalability, and efficiency of CFL systems. His work also delves into privacy-preserving machine learning frameworks, aiming to ensure data security while maintaining high accuracy in distributed environments. Additionally, his research contributions to wireless sensor networks include the development and optimization of energy-efficient communication protocols, making significant strides toward sustainable IoT deployments. His scholarly output in reputed IEEE and Springer journals reflects both depth and breadth in these domains, combining theoretical rigor with practical applicability.

Awards

In recognition of his professional excellence, Mr. Chaudhary has been honored with multiple accolades. He was awarded the Best Training Coordinator on two occasions for his outstanding contributions to student training programs. His postgraduate studies were marked by top academic performance, earning him institutional recognition for his achievements. He has also been acknowledged for his contributions to sports, having represented his district in senior state-level football championships. Furthermore, his research dissemination activities, including paper presentations at national conferences, highlight his active engagement with the wider academic community.

Publications

Review paper on energy-efficient protocols in wireless sensor networks

Authors: R Chaudhary, S Vatta, P No
Journal: IOSR Journal of Engineering 4 (02), 01-07
Year: 2014

A tutorial of routing protocols in wireless sensor networks

Authors: R Chaudhary, DS Vatta
Journal: International Journal of Computer Science and Mobile Computing 3 (6), 971-979
Year: 2014

Performance optimization of WSN using deterministic energy efficient clustering protocol: A review

Authors: R Chaudhary, S Vatta
Journal: International Organization of Scientific Research Journal of Engineering 4 …
Year: 2014

A systematic review on federated learning system: a new paradigm to machine learning

Authors: RK Chaudhary, R Kumar, N Saxena
Journal: Knowledge and Information Systems 67 (2), 1811-1914
Year: 2025

Enhancing clustered federated learning using artificial bee colony optimization algorithm for consumer IoT devices

Authors: RK Chaudhary, R Kumar, K Aurangzeb, J Bedi, MS Anwar, A Choi
Journal: IEEE Transactions on Consumer Electronics
Year: 2024

Ameliorating clustered federated learning using real-coded genetic algorithm

Authors: RK Chaudhary, R Kumar, N Saxena
Journal: Cluster Computing 28 (6), 1-18
Year: 2025

Ameliorating clustered federated learning using grey wolf optimization algorithm for healthcare IoT devices

Authors: RK Chaudhary, R Kumar, N Saxena
Journal: The Journal of Supercomputing 81 (8), 976
Year: 2025

Conclusion

Mr. Rajesh Kumar Chaudhary exemplifies the qualities of a committed educator, innovative researcher, and proactive mentor. His expertise in clustered federated learning, optimization algorithms, and privacy-preserving distributed AI positions him at the forefront of technological advancements in distributed computing systems. With a career that blends academic excellence, impactful research, and active student engagement, he continues to contribute to the development of intelligent, secure, and efficient computing frameworks. His vision aligns with the future of intelligent systems, where collaborative machine learning and optimization strategies will play a crucial role in shaping secure and high-performance applications across domains.

Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

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Mr. Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Jamia Millia Islamia | India

Author Profile

Google Scholar

Mr. Mohammad Zahid

Junior Research Fellow | Ph.D. Scholar in Computer Science | Cybersecurity & AI Researcher

Summary

Mohammad Zahid is a motivated and research-focused computer science professional currently pursuing a Ph.D. in Computer Science at Jamia Millia Islamia, New Delhi. He is working as a Junior Research Fellow (JRF) with a specialization in IoT security, machine learning, deep learning, and federated learning. With strong analytical and technical skills, he is actively engaged in AI-driven cybersecurity research, aiming to develop intelligent systems for threat detection. Zahid is passionate about contributing to innovative and interdisciplinary projects in both academia and the tech industry.

Education

Mr. Zahid is currently enrolled in a Ph.D. program at Jamia Millia Islamia (Central University), New Delhi, with a research focus in computer science and AI. He holds a Master of Computer Applications (MCA) from Maulana Azad National Urdu University (MANUU), Hyderabad, where he graduated with an excellent academic record (87.6%). He also completed a Bachelor of Science (Hons) in Chemistry, Mathematics, and Physics from Aligarh Muslim University (AMU), Aligarh.

Professional Experience

As a Junior Research Fellow, Mr. Zahid is engaged in cutting-edge research related to cybersecurity and artificial intelligence. During his postgraduate studies, he developed a web-based fraud detection system that utilized machine learning algorithms to identify and visualize suspicious banking transactions. His hands-on experience includes technologies such as Java, MySQL, JavaScript, and HTML/CSS, with a strong foundation in data preprocessing and anomaly detection.

Research Interests

Mr. Zahid’s research interests span across IoT security, federated learning, machine learning, and deep learning. His current Ph.D. research is centered on AI-based cybersecurity frameworks, especially for detecting and mitigating threats in decentralized and IoT-based environments. He is particularly interested in applying federated learning models to preserve data privacy while improving detection efficiency in real-world systems.

Honors and Awards

Mr. Zahid was awarded the UGC Junior Research Fellowship (JRF) in Computer Science by the National Testing Agency (NTA) in March 2022, recognizing him among the top national-level researchers eligible for academic and research roles across Indian universities. He also received the Merit-cum-Means Scholarship for Professional Courses from the Ministry of Minority Affairs, Government of India, during his MCA studies (2018–2021), in acknowledgment of his academic performance and financial need.

Publications

 Empowering IoT Networks

Author: M Zahid, TS Bharati

Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Enhancing Cybersecurity in IoT Systems: A Hybrid Deep Learning Approach for Real-Time Attack Detection

Author: M Zahid, TS Bharati
Journal: Discover Internet of Things, Volume 5(1), Page 73
Year: 2025

 Comprehensive Review of IoT Attack Detection Using Machine Learning and Deep Learning Techniques

Author: M Zahid, TS Bharati
Journal: 2024 Second International Conference on Advanced Computing & Communication
Year: 2024

Empowering IoT Networks: A Study on Machine Learning and Deep Learning for DDoS Attack

Author: M Zahid, TS Bharati
Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Martin Andreoni – Network Security – Best Researcher Award

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Dr. Martin Andreoni - Network Security - Best Researcher Award

Technology Innovation Institute - United Arab Emirates

Author Profile

Early Academic Pursuits

Dr. Martin Andreoni embarked on his academic journey with a Bachelor of Science in Electronic Engineering from the National University of San Juan, Argentina, from March 2004 to November 2011. This laid the groundwork for his subsequent academic pursuits. Following this, he pursued a Master of Science in Electrical Engineering at the Federal University of Rio de Janeiro, Brazil, from June 2012 to March 2014, further deepening his understanding of engineering principles.

His academic trajectory culminated in a joint Ph.D. in Computer Science and Electrical Engineering from Sorbonne University in Paris, France, and the Federal University of Rio de Janeiro, Brazil, from June 2014 to July 2018. This interdisciplinary approach fostered a comprehensive understanding of both theoretical and practical aspects of computer science and electrical engineering, providing a solid foundation for his future research endeavors.

Professional Endeavors

Dr. Andreoni seamlessly transitioned from academia to industry, commencing his professional career as an External Consultant at ASINELSA SA, San Juan, Argentina, from October 2013 to June 2018. During this period, he provided invaluable IT consulting services, honing his expertise in Big Data, cloud computing, networking, and programming.

Subsequently, he joined Samsung Electronics, Campinas, Brazil, as a Senior Security Researcher from July 2018 to October 2020. Here, he spearheaded research and development efforts to enhance the security of flagship Samsung devices, leveraging machine learning techniques and coordinating multifaceted teams.

His career trajectory led him to the Technology Innovation Institute (TII) in Abu Dhabi, United Arab Emirates, where he assumed the role of Lead Network Security Researcher from October 2020 to April 2023 and later transitioned to the position of Principal Researcher in April 2023. At TII, Dr. Andreoni has been instrumental in driving applied research and development initiatives focused on security and distributed systems, particularly for secure autonomous systems.

Contributions and Research Focus

Dr. Andreoni's contributions extend across a spectrum of domains, including machine learning, mobile networks, cloud computing, cyber-security, software-defined networks, big data, and the Internet of Things (IoT). His research endeavors have addressed real-world security challenges through innovative approaches such as cloud computing, big data analytics, and intrusion detection techniques.

He has actively participated in international collaborations and research projects, contributing to initiatives like the SecuriTy in Real-time with Elasticity, Analytic, and Monitoring (STREAM) Project and the Secure and Unified Network Infrastructure (SUNI) Project. His research outcomes have been disseminated through numerous journal publications, conference papers, and patents, reflecting his commitment to advancing knowledge in the field.

Accolades and Recognition

Throughout his career, Dr. Andreoni has garnered widespread recognition for his contributions. Noteworthy accolades include the TII Nova Award in Q2 2022 for outstanding performance, as well as several Best Paper and Demo Awards for his research contributions. His work has been acknowledged by prestigious organizations and conferences, underscoring the significance of his contributions to the field of computer science and engineering.

Impact and Influence

Dr. Andreoni's research has had a tangible impact on both industry and academia, with his innovations deployed in products such as Samsung smartphones, thereby enhancing the security of resource-constrained devices. His leadership in international research collaborations and engagement with renowned universities have facilitated knowledge exchange and technological advancements, contributing to the global research ecosystem.

Legacy and Future Contributions

As Dr. Andreoni continues to pursue his research interests in machine learning, mobile networks, cloud computing, cyber-security, and beyond, his legacy of excellence and innovation will endure. Through mentorship and collaboration, he seeks to inspire the next generation of researchers and engineers, leaving an indelible mark on the field and shaping the future of secure autonomous systems and beyond.

Notable Publication