Dr Juan Zhang | Additive manufacturing | Young Scientist Award

Assistant researcher, Tsinghua, China

Dr. Juan Zhang is an Assistant Researcher at Tsinghua University, specializing in the applications of additive manufacturing and deep learning in various engineering fields. With a background in biomaterials and precision machinery, Dr. Zhang’s research focuses on fitness technology, specifically the integration of personalized exercise gear with deep learning algorithms for real-time feedback and injury prevention. Dr. Zhang has published extensively in top journals and has made significant contributions to the development of advanced materials and biomedical devices. 🌟

Profile

Google Scholar

Education

Dr. Zhang completed her Ph.D. in Biomaterials from the University of Science and Technology of China (2017-2022), with a focus on advanced materials for medical applications. She also holds a Bachelor’s degree in Biotechnology from Hefei Normal University (2013-2017). Her academic journey has been shaped by her mentors and her work in precision machinery, furthering her expertise in cutting-edge technologies in materials science. 🎓

Experience

Dr. Zhang’s professional career includes her current position as a Postdoctoral Fellow at Tsinghua University’s Department of Mechanical Engineering. Since March 2023, she has been involved in projects related to additive manufacturing and deep learning applications in exercise state discrimination. She previously worked at the University of Science and Technology of China as a researcher, where she published more than ten papers in prestigious journals. Her work bridges the gap between engineering, healthcare, and fitness technology. 💼

Research Interest

Dr. Zhang’s research focuses on the integration of additive manufacturing with deep learning to design personalized exercise equipment. She is particularly interested in using advanced materials for biomedical applications, such as drug delivery systems, wound healing, and blood plasma separation. Her innovations have the potential to improve health, fitness, and medical treatment efficiency. 🔬🤖

Awards

Dr. Zhang’s contributions to research in the fields of biomaterials, additive manufacturing, and deep learning have been recognized by her peers and in various publications. Her innovative approaches to exercise state discrimination and wound healing have garnered attention from international journals, and she is a nominee for the International Environmental Scientists Award. 🏆

Publication

Zhang J, Liu B, Chen C, et al. Ultrafast Laser-Ablated Bioinspired Hydrogel-Based Porous Gating System for Sustained Drug Release. ACS Applied Materials & Interfaces, 2022, 14(31): 35366-35375. Link

Zhang J, Liu B, Liu X, et al. Laser ablated Janus hydrogel composite membrane for draining excessive blood and biofluid around wounds. Macromolecular Materials and Engineering, 2022, 307(8): 2200026. Link

Xu B, Zhang J, Pan D, et al. High-performance blood plasma separation based on a Janus membrane technique and RBC agglutination reaction. Lab on a Chip, 2022, 22(22): 4382-4392. Link

Xinb M, Zhang J, Pan D, et al. Photo-crosslinking injectable Photothermal antibacterial hydrogel based on quaternary ammonium grafted chitosan and hyaluronic acid for infected wound healing. Materials Today Bio, 2024, 101265. Link

Conclusion

Juan Zhang showcases significant research accomplishments in biomaterials and additive manufacturing, making her a strong candidate for the Young Scientist Award. Addressing citation impact and professional networking would further solidify her candidacy.

Mr Tanmay Ghodeswar | Computer Science and Engineering | Best Researcher Award

Technology Intern, VIT, Vellore, India 

Tanmay Ghodeswar is a talented B.Tech student specializing in Computer Science and Engineering from VIT Vellore, India. With a strong passion for technology, he has worked as a Technology Intern at Thomson Reuters and a Data Science Intern at ADL Coordinates Pvt. Ltd. His work has demonstrated his capability in web scraping, data processing, and machine learning. Tanmay is also a leader in the Apple Developers Group, where he heads R&D, contributing to modern technology integration. His expertise spans a wide range of programming languages and tools, including Python, TensorFlow, and AWS. 🚀

Profile

Orcid

Education

Tanmay completed his B.Tech in Computer Science and Engineering at VIT Vellore, India, with a GPA of 7.95/10 from September 2020 to May 2024. Before his university education, he graduated with a 94.2% in high school from The Samhita Academy in Bengaluru, India. His strong academic foundation laid the groundwork for his deep interest in data science and technology. 🎓

Experience

Currently working as a Technology Intern at Thomson Reuters, Tanmay has contributed significantly to product development, web scraping with Selenium, and content management through Python and AWS services like Lambda and S3. He previously worked as a Data Science Intern at ADL Coordinates Pvt. Ltd., where he developed advanced deep learning models using LSTM and RNN architectures to analyze satellite imagery and enhance disaster management systems. 🌍💻

Research Interest

Tanmay’s research interests revolve around deep learning, machine learning, data science, and their applications in areas like time-series prediction, satellite image analysis, and automated diagnosis. His work on the Alzheimer’s disease diagnosis model, Alzh-Net, showcases his innovative use of CNN architectures. He is also passionate about developing models to predict real-world events, such as the success of SpaceX Falcon9 landings. 🔬🤖

Awards

Throughout his academic journey, Tanmay has demonstrated excellence in both his coursework and internships. His development of deep learning models and their successful applications in real-world problems highlights his capability and dedication. Tanmay has also been actively involved in leadership roles and technical sessions in the Apple Developers Group at VIT. 🏆

Publication

Tanmay contributed to the publication of his research on Alzheimer’s disease diagnosis using his CNN-based model, Alzh-Net, in a well-reputed journal by Elsevier. His research has been widely recognized for its impact on the healthcare and AI fields.

“MRI-based Automated Diagnosis of Alzheimer’s Disease using Alzh-Net Deep Learning Model”
Published: 2024
Elsevier Journal