Chang Meng-Wei | Edge computing | Machine Learning Research Award

Dr. Chang Meng-Wei | Edge computing | Machine Learning Research Award

Department of Electrical Engineering, National Taiwan University of Science and Technology, Taiwan

Meng-Wei Chang is a visionary Chief Engineer with a knack for cutting-edge technology solutions. With a PhD in Electrical Engineering from National Taiwan University of Science and Technology, he has honed his skills in software foundations, computer architecture, and artificial intelligence. Chang’s career spans across various roles in prestigious companies like ADATA Technology and Admiral Overseas Corporation, where he showcased his expertise in product development and brand design. His innovative contributions include the development of the first Android TV set-top box at Tatung and leading the development of an autonomous mobile robot in collaboration with National Taiwan University.

Profile

SCOPUS

 

📚 Education:

Meng-Wei Chang holds a Ph.D. in Electrical Engineering from the National Taiwan University of Science and Technology, where his research focused on software foundations, computer architecture, and artificial intelligence. His academic journey has equipped him with a deep understanding of algorithms, embedded systems, and heterogeneous computing.

🛠️ Experience

Chang’s professional journey includes roles such as Leader Engineer at ADATA Technology, where he collaborated on the development of an autonomous mobile robot, and Leader Engineer at Admiral Overseas Corporation, where he led brand design initiatives. His tenure at Tatung saw him pioneering the development of the first Android TV set-top box, showcasing his expertise in product innovation and RFQ/RFI assessments.

🔬 Research Interests:

Meng-Wei Chang’s research interests lie in the realms of software foundations, computer architecture, and artificial intelligence. His work focuses on adaptive computing, neural networks, and heterogeneous computing architectures.

🏆 Awards:

Meng-Wei Chang’s contributions have been recognized in academia and industry, earning him prestigious awards and accolades for his innovative solutions and impactful research.

Publication:

Journal of the Chinese Institute of Engineers (JCIE) – Real-time multi-fusion perceptron architecture for autonomous drones (Published in 2022)

Journal of the Chinese Institute of Engineers (JCIE) – Adaptive Neural Acceleration Unit based on Heterogeneous Multicore Hardware Architecture FPGA and Software (Published in 2021)

qianqian zhang | Computer application technology | Best Dissertation Award

Dr. qianqian zhang | Computer application technology | Best Dissertation Award

Doctoral student, University of Chinese Academy of Sciences, China

Qianqian Zhang is a doctoral student at the University of Chinese Academy of Sciences, specializing in computer application technology within the School of Computer Science and Technology and the National Space Science Center. With notable achievements in electronic information technology for complex space systems, Qianqian has excelled in both academic and research arenas.

Profile

ORCID

🎓 Education:

  • Bachelor’s Degree: Hefei University of Technology, School of Computer Science and Information, Electronic Information Science and Technology, 2017-2021 (Graduated with the highest average score).
  • Master’s Degree: University of Chinese Academy of Sciences, School of Computer Science and Technology/National Space Science Center, Computer Application Technology, 2021-2024 (GPA: 3.7/4.0).
  • Ph.D. Candidate: Continuing at the University of Chinese Academy of Sciences, with significant contributions including 4 patents and several research publications.

🛠 Experience:

Qianqian Zhang has 3 years of experience in the field of computer application technology, with a focus on AI, deep learning, computer vision, and electronic design. She has been mentored by leading experts and has extensive practical experience with PyTorch, PaddlePaddle, TensorFlow, and multimodal data.

🔬 Research Interests:

Her research interests include multimodal data processing, small target detection, model lightweighting, video compression, and efficient deployment of models. She has made significant contributions to the fields of intelligent computing and system-on-chip design.

🏆 Awards:

Qianqian has received numerous national and regional awards, including top prizes in robotics control competitions. Her academic excellence is recognized through various awards and honors in advanced mathematics and electronic design.

📚 Publications:

“Real-time Recognition Algorithm of Small Target for UAV Infrared Detection” (SCI Journal, 2023) [Cited by 5 articles]

“Design of H.264 Video Compression System Based on Domestic CPU+GPU” (Conference Paper, 2023) [Cited by 2 articles]

“Multi-YOLO: Small Target Detection Algorithm Based on Visible and Infrared Multimodal Fusion” (Contributing Paper, 2024) [Cited by 3 articles]