Nitin Goyal | Computer Science | Research Excellence Award

Central University of Haryana | India

Dr. Nitin Goyal is a faculty member in the Department of Computer Science and Engineering at the Central University of Haryana, India, and holds a PhD in Computer Engineering from NIT Kurukshetra. His expertise lies in underwater wireless sensor networks (UWSN) with applications in military operations, along with research interests in machine learning, deep learning, IoT, and wireless sensor networks. With over 16 years of academic and teaching experience, he has published around 175 research works across SCI, SCOPUS, conference proceedings, and book chapters, filed nearly 30 patents, and edited multiple books with leading international publishers. He has successfully guided postgraduate and doctoral researchers, led an AICTE-funded project, delivered numerous expert and keynote lectures, chaired sessions at reputed international conferences, and actively contributes to the academic community as a Senior Member of IEEE, lifetime member of IAENG, guest editor, reviewer, and editorial board member of several high-impact journals.

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Featured Publications

Early Detection and Classification of Tomato Leaf Disease Using High‑Performance Deep Neural Network

– Sensors, 2021

Secure and Energy‑Efficient Smart Building Architecture with Emerging IoT Technology

– Computer Communications, 2021

Design and Implementation of an ML and IoT‑Based Adaptive Traffic Management System for Smart Cities

– Sensors, 2022

Underwater Wireless Sensor Networks: Enabling Technologies for Node Deployment and Data Collection Challenges

– IEEE Internet of Things Journal, 2022

SAPDA: Secure Authentication with Protected Data Aggregation Scheme for Improving QoS in Scalable and Survivable UWSNs

– Wireless Personal Communications, 2020

Shiping Wang | Computer Science | Research Excellence Award

Fuzhou University | China

Prof. Shiping Wang is a Full Professor in the field of computer and data science and serves as the Director of a provincial key laboratory focused on intelligent metro systems. His research centers on machine learning, deep learning, graph neural networks, feature representation, and graph foundation models. He has published over 200 papers in leading journals and conferences, accumulating more than 6,200 citations, and his work appears in top venues such as IEEE TPAMI, TIP, TMM, CVPR, AAAI, and ACM MM. He has held key leadership and organizational roles in international conferences, including general chair, regional chair, and session chair positions, and regularly serves as a program committee member and reviewer for major AI and computer vision conferences and journals. His research has been supported by multiple projects funded by the National Natural Science Foundation of China.

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