Mr. Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr at Korea University, South Korea

Hyung-pil Chang is a dedicated graduate student at Korea University, pursuing a Ph.D. in Computer Science and Engineering. With a keen interest in deep learning and speech processing, he focuses on enhancing communication between humans and machines. He has contributed to several innovative projects in voice conversion and speech recognition, demonstrating a commitment to advancing technology in these fields. In addition to his academic pursuits, Chang actively engages in various sports and cultural activities, reflecting a well-rounded personality. His passion for research is complemented by his desire to develop practical solutions for real-world problems in artificial intelligence.

Profile

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Scholar

Education 🎓

Hyung-pil Chang began his academic journey at Hansung University, where he earned a Bachelor of Science in Information System and Engineering from March 2014 to February 2020. He continued his studies at Korea University, obtaining a Master of Science in Computer Science and Engineering from 2020 to 2022. Currently, he is pursuing his Doctor of Philosophy in the same field at Korea University, enhancing his knowledge and expertise in deep learning, speech recognition, and human-computer interaction.

Experience 💼

Chang has gained valuable experience as a research assistant at Korea University’s Artificial Intelligence Laboratory since March 2020, working under the guidance of Prof. Dongsuk Yook. He has also served as a teaching assistant for undergraduate courses in Artificial Intelligence and Machine Learning, honing his teaching skills and sharing his knowledge with students. Additionally, he briefly worked in the Voice Generation Team at KT on a multi-modal project, where he contributed to advancements in voice conversion technologies, further solidifying his practical experience in the field.

Awards and Honors 🏆

Hyung-pil Chang has received recognition for his academic and research achievements, including publications in reputable journals such as MDPI Applied Sciences and IEEE Access. His contributions to voice conversion and speaker anonymization research have garnered attention in the field of speech processing. While specific awards are not listed, his active participation in conferences and collaboration on innovative projects highlight his commitment to excellence in research and development, positioning him as an emerging talent in artificial intelligence and deep learning.

Research Focus 🔬

Chang’s research centers on enhancing communication between people and machines, particularly in speech processing. He aims to improve speech recognition models using self-training techniques on large amounts of unlabeled data. His work also explores explainable AI and the development of a general-purpose domain agent capable of interacting with humans across various tasks, including vision and natural language processing. Key areas of focus include speech recognition, synthesis, voice conversion, and human-computer interaction, contributing to advancements in multi-modal language models.

📝 Conclusion

Hyung-pil Chang demonstrates strong potential as a leading researcher in deep learning and speech processing. His academic background, research contributions, and innovative spirit position him well for the Best Researcher Award. By focusing on collaboration, expanding his publication record, and engaging more with the broader community, he can enhance his impact even further. Given his current trajectory, he is well on his way to making significant contributions to his field and is a worthy candidate for recognition.

Publications Top Notes

Wav2wav: Wave-to-Wave Voice Conversion
C Jeong, H Chang, IC Yoo, D Yook
Applied Sciences, 2024, 14(10), 4251.

Zero-Shot Unseen Speaker Anonymization via Voice Conversion
HP Chang, IC Yoo, C Jeong, D Yook
IEEE Access, 2022, 10, 130190-130199.

CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models
D Yook, G Han, HP Chang, IC Yoo
Applied Sciences, 2024, 14(20), 9595.

Mr. ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

PHD at SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS Malaysia

Abel Chai Yu Hao is a PhD candidate at Swinburne University of Technology Sarawak, specializing in computer vision, machine learning, and deep learning. His research focuses on developing interpretable deep learning models for plant disease identification, collaborating with CIRAD and INRIA on innovative agricultural projects. With a Master’s degree in wireless communication, Abel has contributed to improving rural connectivity in Sarawak through cost-effective wireless solutions. He has co-authored numerous journal articles and conference papers on topics ranging from unseen plant disease recognition to wireless data transmission. Abel is a recipient of multiple awards, including the Gold Award at the Innovation Technology Exposition 2023, and is an active IEEE member.

scholar

🎓 Education

Doctor of Philosophy (2022 – Present) Swinburne University of Technology Sarawak Campus Research focus: Computer Vision, Machine Learning, Deep Learning, AI. Master of Engineering (2019 – 2021) Swinburne University of Technology Sarawak Campus Research focus: Wireless communication, Wi-Fi, Rural connectivity. Bachelor of Engineering (Honours), Electrical & Electronics Engineering (2014 – 2018) Swinburne University of Technology Sarawak Campus CGPA: 3.97/4 (High Distinction)

🏫 Professional Experience

Teaching Assistant (2019 – Present) Swinburne University of Technology Sarawak Campus Assisting in course delivery, tutorials, and research guidance

🏆 Awards & Scholarships

Gold Award in Innovation Technology Exposition (2023). Best Paper Award at International UNIMAS Engineering Conference (EnCon) (2020). Sarawak Energy External Scholarship (2015-2018). Swinburne Entrance Scholarship (2014)

🌱 Research Projects

Plant Disease Identification with Deep Learning (2022 – ongoing) Collaborating with experts from CIRAD, INRIA, focusing on AI-based plant disease detection. Rural Internet Connectivity Solutions (2019 – 2021) Conducted cost-performance analysis for wireless solutions in partnership with Sarawak Multimedia Authority (SMA)

Publication

Pairwise Feature Learning for Unseen Plant Disease Recognition
Conference: International Conference on Image Processing (ICIP)
Year: 2023
Pages: 306–310
Contributors: Hao Chai A.Y., Han Lee S., Tay F.S., Bonnet P., Joly A.

Unveiling Robust Feature Spaces: Image vs. Embedding-Oriented Approaches for Plant Disease Identification
Conference: Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
Year: 2023
Pages: 666–673
Contributors: Ishrat H.A., Chai A.Y.H., Lee S.H., Then P.H.H.

Development and Application of Outdoor Router Cost Estimation with Parametric Modelling Technique
Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
Year: 2022
Contributors: Chai A.Y.H., Lai C.H., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

Model Study for Outdoor Data Transmission Performance
Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
Year: 2022
Contributors: Chai A.Y.H., Then Y.L., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

Parametric Model Study for Outdoor Routers Cost Estimation
Conference: 13th International UNIMAS Engineering Conference (EnCon)
Year: 2020
Contributors: Hao Chai A.Y., Hung Lai C., Su H.T., Siang Tay F., Yong L.

🏆 Conclusion:

Abel Chai Yu Hao is a highly qualified candidate for the Best Researcher Award, given his solid academic background, impactful publications, international collaborations, and ongoing contributions to the field of AI and wireless communication. With continuous focus on expanding his research and increasing engagement, his profile can only continue to rise.

Hyung-Pil Chang | Deep Learning | Best Researcher Award