Dr. M.K.Kirubakaran | Sensor Networks | Best Researcher Award

Professor at St.Joseph’s Institute of Technology, India.

Dr. M.K. Kirubakaran is a distinguished professor of Computer Science and Engineering at St. Joseph’s Institute of Technology, Chennai, India. With over two decades of academic experience, he is recognized for his contributions in cyber security, big data analytics, wireless sensor networks, and web services. His teaching philosophy blends technical expertise with industry engagement, enabling students to align theoretical knowledge with practical innovations. He has held key institutional roles fostering industry-academia collaboration and is known for his commitment to curriculum enrichment and value-added learning.

Professional Profile

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Education 🎓📚

Ph.D. in Computer Science and Engineering
Sathyabama University, Chennai – October 2018
Thesis Area: Cyber Security / Advanced Computing Systems
M.E. in Computer Science and Engineering
Vinayaka Mission University, Salem – July 2006
B.Tech. in Computer Science and Engineering
Pondicherry University – May 2003

Professional Experience 🧑‍🏫💼

Professor, St. Joseph’s Institute of Technology, Chennai (Jun 2024 – Present)
Associate Professor, St. Joseph’s Institute of Technology, Chennai (Jun 2019 – May 2024)
Associate Professor, St. Joseph’s College of Engineering, Chennai (Jun 2005 – May 2019)

Key Roles and Responsibilities:

Industry–Institution Interaction Coordinator
Coordinator for Industrial Visits, Symposiums, Value-Added Courses, and Soft Skills Programs
Lab sessions and technical training for industry professionals (CTS, Infosys)

Research Interest 🔬📈

Cyber Security & Secure Web Technologies
Big Data Analytics & Data Privacy
Wireless Sensor Networks and IoT
Web Services and Middleware Architectures

Publications Top Noted

Blockchain-enabled precision agricultural system using IoT and edge computing
Int’l Conf. on Smart Trends in Computing and Communications, 2023 — [Cited: 7]
Deep CNN Framework for Brain Tumor Classification using MRI
2nd Int’l Conf. on Automation, Computing and Renewable Systems, 2023 — [Cited: 6]
Blockchain-based Internet of Vehicles for ITS using Fog Computing
ICCBI 2021 Proceedings, Springer, pp. 827–835 — [Cited: 6]
A Self-Adaptive Duty Cycle MAC Protocol for WSNs
Indian Journal of Science and Technology, 2016 — [Cited: 5]
IW-MAC: Invite and Wait Protocol for Energy-Efficient WSNs
Journal of Ambient Intelligence and Humanized Computing, 2018 — [Cited: 4]

Conclusion 🌟🎯

Dr. M.K. Kirubakaran is a strong candidate for the Best Researcher Award, especially in the field of Sensor Networks and cyber-physical systems. His blend of technical depth, academic leadership, and impactful research makes him a deserving nominee. With focused efforts on global collaboration and innovation dissemination, he is poised for even broader impact in the coming years.

Dr Shengkai Zhang | Smart Sensing | Best Researcher Award

Dr Shengkai Zhang, Wuhan University of Technlogy, China

Dr. Shengkai Zhang is a distinguished researcher in the field of smart sensing technologies. Renowned for his innovative contributions, he has significantly advanced the development of intelligent sensor systems that are widely used in various industries. Dr. Zhang’s work integrates cutting-edge technologies with practical applications, earning him recognition as a leading expert in the field. His research has not only led to numerous publications in top-tier journals but has also resulted in several patents, underscoring his impact on both academia and industry. His excellence and dedication have been recognized with the prestigious Best Researcher Award, highlighting his role as a pioneer in smart sensing.

Professional Profile:

Google Scholar

Education

Dr. Shengkai Zhang holds a Ph.D. in Information Engineering from Huazhong University of Science and Technology (HUST), where he conducted his research under the guidance of Prof. Tao Jiang at the School of Electronic Information and Communications, completing his degree in June 2021. Prior to this, he earned an M.Phil. in Computer Science and Engineering from the Hong Kong University of Science and Technology (HKUST) in November 2014, where he was advised by Prof. Bo Li in the Department of Computer Science and Engineering. Dr. Zhang also holds an M.Sc. in Communication and Information System, completed in March 2012 at HUST, under the mentorship of Prof. Hongbo Jiang. He began his academic journey with a B.Eng. in Communication Engineering from Central China Normal University (CCNU), graduating in June 2009.

Research Interest

Dr. Shengkai Zhang is a distinguished researcher specializing in aerial robotics, wireless sensing, and mobile computing. His work focuses on innovative applications of Gaussian splatting and Simultaneous Localization and Mapping (SLAM) to enhance the accuracy and efficiency of autonomous systems. With a strong background in both theoretical and applied aspects of these technologies, Dr. Zhang has contributed significantly to the development of advanced algorithms and sensing techniques that push the boundaries of what’s possible in mobile computing and robotics. His research has not only advanced academic knowledge but also paved the way for practical implementations in various industries.

Research And Industry Experience

Dr. Shengkai Zhang is currently an Associate Professor at Wuhan University of Technology, China, a position he has held since July 2022. Before this, he served as an Assistant Professor at the same institution from June 2021 to June 2022. Earlier in his career, Dr. Zhang gained valuable research experience as a Research Assistant at the HKUST-DJI Joint Innovation Laboratory in Hong Kong, where he worked from December 2014 to August 2016, contributing to cutting-edge advancements in smart sensing technologies.

Teaching Experience

Dr. Shengkai Zhang has an extensive teaching portfolio, having delivered courses across several key areas of information engineering and computer science. In the Spring of 2024, he is instructing Indoor Localization Technology and Digital Electronics at Wuhan University of Technology (WUT) within the School of Information Engineering. His recent teaching includes Introduction to Information Technology during the Fall of 2022 at WUT. Earlier in his career, Dr. Zhang taught foundational courses in Computer Communication Networks I and Operating Systems at the Hong Kong University of Science and Technology (HKUST) from 2013 to 2014, contributing to the education of future professionals in the Department of Computer Science and Engineering. His dedication to teaching reflects his commitment to advancing the knowledge and skills of his students in these crucial fields.

Honours and Awards

Dr. Shengkai Zhang has received numerous accolades throughout his academic and professional career, highlighting his exceptional contributions to his field. In 2021, he was honored with the Excellent Paper Award by the Chinese Institute of Electronics. He has also been recognized by Huawei, receiving the prestigious First Class of Huawei Scholarship in 2020, the same year he was awarded the National Scholarship for Postgraduates. His innovative spirit was acknowledged with the First Prize in the Future Aircraft Competition at HUST in 2019, along with the Graduates’ Innovation Fund of HUST. Dr. Zhang was also a recipient of the HUST Ph.D. Fellowship in 2017. Earlier in his career, he received a Student Travel Grant for the ICC conference in London in 2015 and was awarded the HKUST Postgraduate Studentship in 2012. His academic excellence dates back to his undergraduate years, where he was named an Outstanding Undergraduate Student at CCNU in 2009 and received both Second-Class and Third-Class Scholarships in 2009 and 2008, respectively.

Publication

Cong Fan, Shengkai Zhang, Kezhong Liu, Shuai Wang, Zheng Yang, and Wei Wang. “Enhancing mmWave Radar Point Cloud via Visual-inertial Supervision.” IEEE International Conference on Robotics and Automation (ICRA), 2024.

Danyang Li, Yishujie Zhao, Jintao Xu, Shengkai Zhang, Longfei Shangguan, and Zheng Yang. “edgeSLAM2: Rethinking Edge-Assisted Visual SLAM with On-Chip Intelligence.” IEEE International Conference on Computer Communications (INFOCOM), pp. 1-10, 2024.

Hongzhou Li, Sijie Yu, Shengkai Zhang, and Guang Tan. “Resolving Loop Closure Confusion in Repetitive Environments for Visual SLAM through AI Foundation Models Assistance.” IEEE International Conference on Robotics and Automation (ICRA), 2024.

Zheng Li, Jun Ma, Feifeng Jiang, and Shengkai Zhang. “Assessing the Impacts of Urban Morphological Factors on Urban Building Energy Modeling Based on Spatial Proximity Analysis and Explainable Machine Learning.” Journal of Building Engineering, vol. 85, no. 7, article no. 108675, 2024.

Dashuai Pei, Danei Gong, Kezhong Liu, Xuming Zeng, Shengkai Zhang, Mozi Chen, and Kai Zheng. “mmCTD: Concealed Threat Detection for Cruise Ships Via Mmwave Radar.” IEEE Transactions on Vehicular Technology, Early Access, DOI: 10.1109/TVT.2024.3352039.

Pengen Gao, Shengkai Zhang, Wei Wang, and Chris Xiaoxuan Lu. “Robust Metric Localization in Autonomous Driving via Doppler Compensation with Single-chip Radar.” IEEE Transactions on Intelligent Transportation Systems (TITS), vol. 25, no. 1, pp. 491-502, 2024.

Danei Gong, Kezhong Liu, Dashuai Pei, Haoran Zhang, Shengkai Zhang, and Mozi Chen. “Wi-Watch: Wi-Fi-Based Vigilant-Activity Recognition for Ship Bridge Watchkeeping Officers.” IEEE Transactions on Instrumentation and Measurement, vol. 73, no. 9503717, 2023.

Kezhong Liu, Dashuai Pei, Shengkai Zhang, Mozi Chen, Xuming Zeng, Kai Zheng, and Chunshen Li. “WiCrew: Gait-based Crew Identification for Cruise Ships Using Commodity WiFi.” IEEE Internet of Things Journal, vol. 10, no. 8, pp. 6960-6972, 2022.

Fei Xiao, Shengkai Zhang, Sheyang Tang, Shaojie Shen, Huixin Dong, and Yi Zhong. “WiSion: Bolstering MAV 3D Indoor State Estimation by Embracing Multipath of WiFi.” IEEE Transactions on Vehicular Technology, vol. 72, no. 1, pp. 253-266, 2023.

Shengkai Zhang, Wei Wang, Ning Zhang, and Tao Jiang. “LoRa Backscatter Assisted State Estimator for Micro Aerial Vehicles with Online Initialization.” IEEE Transactions on Mobile Computing (TMC), vol. 21, no. 11, pp. 4038-4050, 2022.