Sheng Ye | Computer Science | Best Researcher Award

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Sheng Ye | Computer Science | Best Researcher Award

Mr Sheng Ye, Tsinghua University, China

Mr. Sheng Ye 🎓 is a talented researcher in advanced computer science, specializing in deep learning and computer vision. Graduating in the top 15% from Tsinghua University with a GPA of 3.89/4.0, under the guidance of Prof. Liu Yongjin, he quickly established himself as a promising talent. His award-winning project on real-time video stylization 🏅 received the “Best Practice Award” from Kuaishou and Tsinghua University, and he has been honored with multiple scholarships, including the prestigious “Jiukun Scholarship.” Known for his impactful publications 📑 and contributions to academic conferences, Mr. Sheng Ye is well-positioned to excel in research.

Publication Profile

Scopus

Education Background 🎓

The candidate holds a strong academic record in advanced computer science, focusing on deep learning and computer vision. Graduating among the top 15% from Tsinghua University with a GPA of 3.89/4.0, they were supervised by Prof. Liu Yongjin. Recognized as an exemplary graduate, their academic achievements reflect a dedication to excellence. Early accolades include ranking within the top 10 of their grade and excelling in the national entrance exam with a score of 703. This foundation underlines their exceptional knowledge base and capability in scientific research.

Research Focus and Achievements 🔬

The candidate’s research spans innovative deep learning techniques and computer vision applications. A notable project on real-time video stylization was awarded the “Best Practice Award” by Kuaishou and Tsinghua University. Additional distinctions include winning first prize at the 16th Image and Graphics Technology and Applications Conference (IGTA). Their publication record is further strengthened by multiple scholarship awards and recognitions, including the prestigious “Tsinghua Friends – Jiukun Scholarship” in 2022–2023. This research-oriented focus positions the candidate as a strong contender for the Best Researcher Award.

Professional Experience and Contributions 💼

Through internships and student roles, the candidate has significantly impacted Tsinghua’s computing community. Leading publicity efforts in the computer science department, they manage the “JiXiaoYan” public account, curating content across various academic themes. Their professional involvement also extends to reviewing for prominent conferences and journals like CVPR, AAAI, NeurIPS, and ECCV. This experience illustrates their commitment to academic development and a thriving research community.

Key Publications 📑

  • 2024: DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation – ACM Transactions on Graphics, 43(4) 📊
  • 2024: O2-Recon: 3D Reconstruction of Occluded Objects – AAAI Conference on AI, 38(3) 🖼️
  • 2024: Online Exhibition Halls with Virtual Agents – Journal of Software, 35(3) 🌐
  • 2024: Fine-Grained Indoor Scene Reconstruction – IEEE Transactions on Visualization 📐
  • 2023: Virtual Digital Human for Customer Service – Computers and Graphics, 115 🎭
  • 2022: Audio-Driven Gesture Generation – Lecture Notes in Computer Science, 13665 🎶

Publication Top Notes

DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation and Head Pose Generation via Diffusion Models

O2-Recon: Completing 3D Reconstruction of Occluded Objects in the Scene with a Pre-trained 2D Diffusion Model

Indoor Scene Reconstruction with Fine-Grained Details Using Hybrid Representation and Normal Prior Enhancement

Generation of virtual digital human for customer service industry

Audio-Driven Stylized Gesture Generation with Flow-Based Model

Conclusion 🏆

The candidate’s robust educational background, innovative research, and active participation in academic communities distinguish them as a prime candidate for the Best Researcher Award. With numerous accolades, impactful publications, and a track record of community engagement, they are set to make meaningful contributions to the fields of deep learning and computer vision.

K ASHWINI | Computer Science | Best Researcher Award

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K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.

Dinesh Sharma | Computer Science | Best Researcher Award

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Dr. Dinesh Sharma | Computer Science | Best Researcher Award

Dr. Dinesh Sharma, Manipal University Jaipur, India

Dr. Dinesh Sharma holds a Ph.D. in Computer Science and Engineering from Uttarakhand and an M.E. from C-DAC, Pune. With over 14 years of experience in technical and engineering education, he currently serves as an Associate Professor at Manipal University Jaipur. He has published multiple patents, including innovations in animal wellbeing and waste management. Dr. Sharma is a technical committee member for various international conferences and has acted as a guest editor for respected journals. He is also an AICTE High-Performance Computing Master Trainer, dedicated to advancing technology in education. 🌍✨

 

Publication profile

Scopus

Qualification

Dr. Dinesh Sharma is an accomplished academic in the field of Computer Science and Engineering, holding a Ph.D. from Uttarakhand Technical University. He also earned a Master’s degree in CSE from C-DAC, Pune, and a Bachelor’s degree from R.G.P.V., Bhopal. With over 14 years of experience in technical education, he currently serves as an Associate Professor at Manipal University Jaipur. Dr. Sharma has a strong research background, with multiple patents and publications focusing on innovative technologies. His contributions to academia include serving as a reviewer for numerous journals and as a technical committee member for various international conferences. 🌍✨

 

Professional Achievements 🏆

Dr. Dinesh Sharma has made significant contributions to academia and industry, serving as a Guest Editor for a special issue on “Industrial System Pioneering in Industry 4.0” in the Journal of New Materials and Electrochemical Systems. He is an AICTE High-Performance Computing Master Trainer and has been invited as a session chair at numerous international conferences, including IEEE CSNT and CICN. Dr. Sharma coordinated a five-day Faculty Development Program on IoT at Amity University and served as an Associate Editor for Pragyan Journal of Information Technology. Additionally, he reviews for various SCI, IEEE, and Scopus-indexed journals. 🌐✨

 

Awards & Guided Projects 🏅

Dr. Dinesh Sharma has successfully mentored CSE students who achieved remarkable milestones, including securing international funding of $1,000 and $250 from Latrobe University Technology Grand Challenge, where one project also won the 1st runner-up prize. Under his guidance, Mr. Ashish Kumar Mishra developed a “Smart Attendance System,” earning 1st position in a national challenge organized by Amazon and receiving ₹35,000. Additionally, Ms. Priyanshi Gupta won ₹30,000 and the runner-up prize at the “Gwalior Smart City Tech Challenge 2020.” Dr. Sharma also led the development of the web conferencing platform “Bharat Live” for online activities. 🌍🎉

 

Professional Experience 📚

Dr. Dinesh Sharma brings over 14 years of expertise in technical and engineering education, specializing in software development with 8 years of freelance experience in C#, ASP.Net, PHP, Java, and Android app development. Currently, he serves as an Associate Professor in Data Science and Engineering at Manipal University Jaipur since August 2023, where he is also a software developer, KPI coordinator, and E-cell coordinator. Previously, he worked as an Assistant Professor at Amity University Madhya Pradesh and IMS Unison University, contributing significantly as a software developer and coordinator for various academic initiatives. His journey began as the Head of the Computer Science & Engineering Department at Amardeep College of Engineering and Management. 🎓💻

 

Conclusion

Dr. Dinesh Sharma’s qualifications, innovative research contributions, professional achievements, and mentorship make him an exemplary candidate for the Best Researcher Award. His commitment to advancing technology and educating future generations in the field of computer science is commendable, and he is well-deserving of this recognition.

 

Publication Top Notes

  • Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network – Cited by: 0 (2024) 🐾
  • Automatic detection and classification of plant leaf diseases using image processing: A survey – Cited by: 1 (2023) 🌱
  • Enhancing Feature Extraction in Plant Image Analysis through a Multilayer Hybrid DCNN – Cited by: 0 (2023) 🖼️
  • Comparative Analysis of Skin Cancer Detection Using Classification Algorithms – Cited by: 1 (2023) 🎗️
  • Face Mask Detection Analysis for Covid19 Using CNN and Deep Learning – Cited by: 3 (2022) 😷
  • Energy Efficient Multitier Random DEC Routing Protocols for WSN: In Agricultural – Cited by: 18 (2021) 🌾
  • A new energy efficient multitier deterministic energy-efficient clustering routing protocol for wireless sensor networks – Cited by: 34 (2020) 💡
  • Comparative energy evaluation of lEACH protocol for monitoring soil parameter in wireless sensors network – Cited by: 7 (2018) 🌍
  • Enhance PeGASIS algorithm for increasing the life time of wireless sensor network – Cited by: 6 (2018) ⚡