Mr. chao zheng | computer science | Best Researcher Award

Mr. chao zheng | computer science | Best Researcher Award

Mr. chao zheng, manager, tencent, China.

Chao Zhen is a leading researcher in computer vision and artificial intelligence, currently heading the Computer Vision Research team at Tencent Map. He is widely recognized for his expertise in autonomous driving and machine perception. Over the years, he has driven innovation in 3D perception and semantic understanding within autonomous systems. His work regularly appears in prestigious conferences such as AAAI, ICCV, ECCV, and WACV. With a growing impact in AI and computer vision, he continues to push the boundaries of real-world applications. His collaborative research has earned accolades like the IAAI Application Innovation Award.

Publication Profile

Scopus

Google Scholar

🎓 Education Background

Chao Zhen holds a solid academic foundation in artificial intelligence and computer vision. While specific institutional details of his degrees are not publicly listed, his prolific publication record in high-impact conferences like ICCV, ECCV, and AAAI indicates deep formal training, likely at top-tier universities or research institutes. His education has equipped him with advanced theoretical and practical knowledge in machine learning, 3D scene understanding, and multimodal AI—forming the cornerstone of his success in autonomous driving research. Through continuous learning and collaboration, he has established himself as a technical leader in AI and robotics.

💼 Professional Experience

Chao Zhen currently leads the Computer Vision Research team at Tencent Map, focusing on enabling intelligent mapping and scene understanding for autonomous vehicles. His professional journey spans several years of active involvement in cutting-edge research and development of AI-powered vision systems. Under his leadership, the team contributes to next-gen perception modules and vision-language systems for driving environments. He actively collaborates with academic and industrial partners, guiding projects from prototype to deployment. His role integrates both technical depth and strategic foresight in aligning AI research with scalable real-world applications.

🏆 Awards and Honors

Chao Zhen’s outstanding contributions have been recognized with several prestigious honors, most notably the IAAI Application Innovation Award, awarded for impactful AI-driven applications. His co-authored work has gained traction in premier AI and computer vision conferences, a testament to its relevance and innovation. These accolades highlight his contributions to advancing practical autonomous driving solutions using sophisticated machine perception models. Beyond awards, his publications continue to receive high citation counts, reflecting his influence in the research community and his pivotal role in shaping the future of AI-driven transportation systems.

🔬 Research Focus

Chao Zhen’s research centers around artificial intelligence, computer vision, and machine learning, with a strong focus on 3D perception and reconstruction for autonomous driving. His work bridges data-driven learning techniques with real-world challenges, such as lidar-based segmentation, topological reasoning, and vision-language integration. He explores multimodal systems that combine point cloud data, semantic maps, and language to build robust scene understanding. Through projects like MapLM and 2DPASS, he advances scalable solutions for urban mobility. His innovations pave the way for safer, smarter, and more interpretable autonomous systems leveraging the synergy of AI modalities.

📌 Conclusion

Chao Zhen stands out as a forward-thinking AI researcher and industry leader in the realm of autonomous driving. His innovative vision and commitment to research excellence have resulted in influential publications, impactful industry contributions, and prestigious recognitions. By fusing deep technical insights with real-world needs, he is helping shape the next generation of intelligent vehicles. His ongoing efforts in 3D scene understanding, multimodal AI, and semantic modeling are not only transforming how machines perceive the world but also driving the future of intelligent transportation.

📚 Top Publications Notes

  1. A Survey on Multimodal Large Language Models for Autonomous Driving
    Year: 2024
    Journal/Conference: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
    Cited by: 426 articles

  2. 2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
    Year: 2022
    Journal/Conference: European Conference on Computer Vision (ECCV)
    Cited by: 326 articles

  3. MapLM: A Real-World Large-Scale Vision-Language Dataset for Map and Traffic Scene Understanding
    Year: 2024
    Journal/Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    Cited by: 10 articles

  4. MapLM Benchmark: Real-World Vision-Language Benchmark for Traffic Scene Understanding
    Year: 2024
    Journal/Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    Cited by: 35 articles

  5. RelTopo: Enhancing Relational Modeling for Driving Scene Topology Reasoning
    Year: 2025
    Journal: arXiv preprint
    Cited by: In press (citation data to be updated)

  6. Cross-Modal Semantic Transfer for Point Cloud Semantic Segmentation
    Year: 2025
    Journal: ISPRS Journal of Photogrammetry and Remote Sensing
    Cited by: 1 article

  7. Topo2Seq: Enhanced Topology Reasoning via Topology Sequence Learning
    Year: 2025
    Journal: arXiv preprint
    Cited by: 1 article

  8. Position: Autonomous Driving & Multimodal LLMs
    Year: 2025
    Journal: Winter Conference on Applications of Computer Vision (WACV)
    Cited by: 8 articles

 

SEKAR C | Internet of Things | Best Researcher Award

Dr. SEKAR C | Internet of Things | Best Researcher Award

Reserach Scholar, NIT Trichy, India

Dr. C. Sekar is a dedicated researcher, educator, and technologist specializing in IoT, cryptography, and secure data transactions. With a passion for innovation, he has contributed significantly to the development of IoT-enabled lightweight encryption algorithms for industry, healthcare, and forensic applications. Currently serving as an Assistant Professor at SRM IST, Trichy Campus, he is committed to mentoring and guiding students in cutting-edge technologies like Full Stack Development, AR/VR, and Advanced Computer Networks. His extensive hands-on experience in real-world IoT applications and cybersecurity makes him a valuable asset in the field of computer science.

Publication Profile

🎓 Education

Dr. C. Sekar earned his Ph.D. in Computer Science and Engineering from the National Institute of Technology, Tiruchirappalli, in July 2024, with a specialization in IoT and Embedded Systems, Cryptography, and Network Security. His research focused on “Investigations on IoT-Enabled Lightweight Image Encryption Algorithms for Industry, Healthcare, and Forensic Applications.” Prior to his doctorate, he completed his Master of Engineering in Computer Science and Engineering at the Indian Institute of Information Technology, Trichy, in 2016. His academic journey began with a Bachelor of Engineering from the Coimbatore Institute of Engineering and Technology, Coimbatore, in 2013, where he worked on network security-based projects.

💼 Experience

Dr. Sekar has amassed extensive experience in research, academia, and industry. Before joining SRM IST, he worked on multiple government-sponsored research projects. As a Senior Research Fellow at NIT Trichy, he contributed to projects like the CMPDI-sponsored “Electronification of GWC and Conveyor Systems in Mines” and the C-DAC-sponsored “Emergency Response Support System.” He also played a key role in the DST-funded project for women’s digital empowerment. In addition to research, he worked as a Database Administrator at Bharat Electronics Limited, Bangalore, managing large-scale database operations for the National Population Register and Aadhaar Card Project. His expertise extends to freelancing, where he has been developing IoT-based home automation systems.

🏆 Awards and Honors

Dr. Sekar’s contributions to IoT security and digital transformation have earned him recognition in the research community. His work has been published in high-impact journals and international conferences. His research on secure IoT-enabled medical record sharing and real-time image encryption for Industry 4.0 has been widely cited. He is also a Microsoft Certified Technology Specialist, reflecting his deep expertise in software development, cybersecurity, and advanced networking protocols.

🔬 Research Focus

Dr. Sekar’s research primarily revolves around IoT-enabled real-world applications, lightweight cryptography, and secure data transactions in distributed networks. His work integrates emerging technologies like AI/ML with IoT to create smart solutions for industries and healthcare. He has significant expertise in advanced computer networking protocols, including 5G, LoRa, and ZigBee. His research contributions have led to the development of patent-worthy prototype models for real-time security applications, particularly in data encryption and cybersecurity.

🔗 Publications

Smart camera with image encryption: a secure solution for real-time monitoring in Industry 4.0 

Secure IoT-enabled sharing of digital medical records: An integrated approach with reversible data hiding, symmetric cryptosystem, and IPFS 

Development of predictive model-based mobile application for maturity stage identification of Indian traditional red bananas

Secure App Login Authorization for IoT Devices Using OAuth 2.0

TKBG — The knowledge-based grep using self-key discovery and semantic linking for online resources 

🔚 Conclusion

Dr. C. Sekar is an accomplished academician and researcher with deep expertise in IoT security, cryptography, and network protocols. His innovative contributions to secure data transactions and IoT-enabled applications have made a significant impact in the field of computer science. With a strong background in academia, research, and industry, he continues to inspire students and researchers by bridging the gap between theoretical knowledge and real-world applications. His work in developing AI-integrated IoT solutions and encryption technologies is poised to shape the future of cybersecurity and smart systems. 🚀