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) ⚡

Larbi Boubchir | Computer Science Award | Best Researcher Award

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Prof. Larbi Boubchir | Computer Science Award | Best Researcher Award

Prof. Larbi Boubchir, University of Paris 8, France

Prof. Larbi Boubchir appears to be a strong candidate for the “Research for Best Researcher Award” based on several key factors:

Publication profile

Academic and Professional Achievements

Prof. Boubchir is a Full Professor of Computer Science at the University of Paris 8, France, where he has held multiple significant roles, including Deputy Director of the LIASD laboratory and Head of the IUSD research group. His academic background includes a Ph.D. in Signal and Image Processing and an HDR degree in Computer Science, showcasing a solid foundation in his field.

Research Expertise

His research interests are diverse and highly relevant, covering artificial intelligence, biometrics, biomedical signal processing, and image processing. His expertise in advanced areas such as machine learning, deep learning, and feature engineering, coupled with practical applications in biometric security and health-related fields, highlights his significant contributions to cutting-edge technology.

Publication 

  • Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities 📉 – Cited by 155, 2005
  • Face–iris multimodal biometric identification system 🕵️‍♂️ – Cited by 104, 2020
  • Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters ✋ – Cited by 89, 2016
  • Multivariate statistical modeling of images with the curvelet transform 📊 – Cited by 79, 2005
  • A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with … ⏱️ – Cited by 74, 2012
  • A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-stable prior 📈 – Cited by 64, 2006
  • Wavelet Denoising Based on the MAP Estimation Using the BKF Prior With Application to Images and EEG Signals 🧠 – Cited by 57, 2013
  • EEG epileptic seizure detection and classification based on dual-tree complex wavelet transform and machine learning algorithms ⚡ – Cited by 50, 2020
  • A review of feature extraction for EEG epileptic seizure detection and classification 🔬 – Cited by 49, 2017
  • Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states 🔍 – Cited by 45, 2020
  • Robust model-free gait recognition by statistical dependency feature selection and globality-locality preserving projections 🚶‍♂️ – Cited by 39, 2016
  • Human gait recognition based on Haralick features 🚶‍♀️ – Cited by 38, 2017
  • Face–iris multi-modal biometric system using multi-resolution Log-Gabor filter with spectral regression kernel discriminant analysis 📸 – Cited by 37, 2018
  • Palm vein recognition based on competitive coding scheme using multi-scale local binary pattern with ant colony optimization 🖐️ – Cited by 36, 2020
  • Human gait recognition using GEI-based local multi-scale feature descriptors 🕺 – Cited by 36, 2019

Awards and Recognition

He has received several prestigious awards, including IEEE Access Outstanding Associate Editor accolades and Best Paper awards at international conferences. These honors reflect his high impact and recognition in the research community.

Leadership and Teaching

In addition to his research, Prof. Boubchir has made substantial contributions to education as the head of Master’s programs in Cyber Security, Data Science, and Big Data. His leadership in these programs demonstrates his commitment to advancing knowledge and mentoring future professionals.

Conclusion

Prof. Boubchir’s extensive research contributions, leadership roles, and accolades make him a highly suitable candidate for the Research for Best Researcher Award.

Mr. Shofiqul Islam | Computer Science | Best Researcher Award

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Mr. Shofiqul Islam | Computer Science | Best Researcher Award

Mr Shafiqul Islam ,    Deakin University , Australia

Md. Shofiqul Islam, born in May 1989, is a resident of Highton, Geelong, Australia. Originally hailing from Chutipur, Notipota, Dhamuruda-7220, Chuadanga, Bangladesh, he has established himself in Australia while maintaining ties to his permanent address in Bangladesh. Shofiqul Islam is the son of Md. Abdul Khaleque. He stands 5 feet 7.5 inches tall and weighs 78 kilograms. As a male citizen of Bangladesh, he holds a National ID with the number 1813183458130.

Publication profile
Educational Background

Md. Shofiqul Islam is currently pursuing a Ph.D. in AI-Based Haptic Robotic Control in Medical Tele-Surgery at Deakin University, Australia, a program he began in May 2024. Prior to this, he completed a Master of Science (M.Sc) by Research at the Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), Pahang, Malaysia, in November 2022, achieving an impressive 80% mark. He earned his Bachelor of Science (B.Sc) in Computer Science and Engineering from Islamic University, Kushtia, Bangladesh, in 2014, where he graduated with a CGPA of 3.69 out of 4.00, securing 2nd position among 45 students. His academic journey began at Notipota High School in Dhamurhuda, Chuadanga, Bangladesh, where he obtained his Secondary School Certificate (SSC) in Science in 2005 with a GPA of 4.06 out of 5.00. He then completed his Higher Secondary Certificate (HSC) in Science at Chuadanga Govt. College in 2007, with a GPA of 4.70 out of 5.00.

Research and Work Experience

Md. Shofiqul Islam is currently pursuing a Ph.D. in AI-Based Haptic Robotic Control in Medical Tele-Surgery at Deakin University, Australia, a journey he began in May 2024. Before embarking on his Ph.D., he served as an Assistant Professor in the Department of Computer Science and Engineering at the Military Institute of Science and Technology (MIST) in Dhaka, Bangladesh, from March 2023 to April 15, 2024. Prior to this role, he was a Senior Lecturer at the World University of Bangladesh (WUB) for a brief period from January 2023 to April 2023. His academic career also includes a significant tenure as a Graduate Research Assistant at the Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), where he contributed to research from October 2018 to June 2022. Earlier, he held positions as a Lecturer in Computer Science and Engineering at Atish Dipankar University of Science and Technology from October 2016 to September 2018, and at First Capital University of Bangladesh (FCUB) from February 2015 to June 2016. His extensive experience in academia reflects his deep commitment to advancing knowledge in computer science and engineering.

 

Awards and Recognitions

Md. Shofiqul Islam has been awarded a prestigious fully funded Ph.D. scholarship from the Australian Government, supporting his research at Deakin University from May 2022 to May 2027. This scholarship enables him to pursue advanced studies in AI-Based Haptic Robotic Control in Medical Tele-Surgery. Prior to this, he received a Graduate Research Assistantship (GRA) at Universiti Malaysia Pahang, Malaysia, where he contributed to significant research projects from March 2018 to November 2022. His academic excellence was also recognized during his undergraduate studies, where he received a Merit Scholarship each year from 2009 to 2014 while pursuing a B.Sc. in Computer Science and Engineering at Islamic University, Bangladesh. These achievements reflect his consistent dedication and outstanding performance throughout his academic career.

Publication Top Notes

  • HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention-based dual structured RNN with dilated CNN
    Authors: MS Islam, KF Hasan, S Uddin, JMW Quinn, MA Moni
    Journal: Neural Networks, Volume 162, Pages 271-287, 2023
    Citations: 30
  • A review on video classification with methods, findings, performance, challenges, limitations and future work
    Authors: MS Islam, U Kumar Roy, J Al Mahmud
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 6, Pages 47-57, 2020
    Citations: 30
  • New hybrid deep learning approach using BiGRU-BiLSTM and multilayered dilated CNN to detect arrhythmia
    Authors: MS Islam, MN Islam, N Hashim, M Rashid, BS Bari, F Al Farid
    Journal: IEEE Access, Volume 10, Pages 58081-58096, 2022
    Citations: 26
  • A review on recent advances in Deep learning for Sentiment Analysis: Performances, Challenges and Limitations
    Authors: MS Islam, N Ab Ghani, MM Ahmed
    Journal: Journal of COMPUSOFT, 2020
    Citations: 16
  • A Novel BiGRUBiLSTM Model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM
    Authors: MS Islam, NA Ghani
    Book Series: Lecture Notes in Electrical Engineering (LNEE), Springer, 2021
    Citations: 15
  • HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text
    Author: MS Islam
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, April 2021
    Citations: 14
  • Machine Learning-Based Music Genre Classification with Pre-Processed Feature Analysis
    Authors: MS Islam, MM Hasan, MA Rahim, AM Hasan, M Mynuddin, I Khandokar, …
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, Issue 3, Pages 491-502, 2021
    Citations: 10
  • Applications of Artificial Neural Networks in Engine Cooling System
    Authors: MM Hasan, MS Islam, SA Bakar, MM Rahman, MN Kabir
    Conference: 2021 International Conference on Software Engineering & Computer Systems (ICSECS), IEEE
    Citations: 7
  • Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach
    Authors: MS Islam, MN Kabir, NA Ghani, KZ Zamli, NSA Zulkifli, MM Rahman, …
    Journal: Artificial Intelligence Review, Volume 57, Issue 3, Pages 62, 2024
    Citations: 6
  • Machine Learning Methods to Predict and Analyse Unconfined Compressive Strength of Stabilised Soft Soil with Polypropylene Columns
    Authors: HRS Ikramul Hoque, Muzamir Hasan, Shofiqul Islam, Moustafa Houda, Mirvat Houda
    Journal: Cogent Engineering, Volume 10, Issue 1, 2023
    Citations: 6
  • New Hybrid Deep Learning Method to Recognize Human Action from Video
    Authors: MS Islam, MJ Islam
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, Pages 306-313, 2021
    Citations: 4

 

Vipin Bansal | Computer Science Award | Academic Summit Impact Award

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Mr. Vipin Bansal | Computer Science Award | Academic Summit Impact Award

Mr. Vipin Bansal, Cognizant, India

Vipin Bansal is an accomplished Senior Engineering Manager specializing in AI and ML solutions. 📊 His expertise spans computer vision, anomaly detection, and AI-based healthcare innovations. He is proficient in deploying scalable AI models and cloud-based solutions using platforms like AWS and Azure. ☁️ Vipin’s work includes impactful projects in autonomous driving, healthcare, and commercial applications. 🚗 He is pursuing a PhD in Explainable AI and has authored significant research in the field. 📜 Passionate about leading teams and driving technological advancements, he continues to excel in the dynamic tech landscape. 💼

Publication Profile

Orcid

Education 🎓

Vipin is pursuing a PhD in Explainable AI from Chandigarh University and holds a Master’s in Computer Applications from Birla Institute of Technology, Ranchi. 🧑‍🎓

Work Experience 💼

Vipin has served as a Senior Engineering Manager at Cognizant, focusing on computer vision AI solutions and cloud infrastructure. He also worked at Molnlycke HealthCare on business applications and at Altran on autonomous driving technologies and data quality analysis. His earlier roles include leading mobile app development at Imagination Technology and architecting m-commerce solutions at Aricent. 🚗

Research Focus 📚🔬

Vipin Bansal’s research focuses on the application of generative AI techniques for medical imaging, specifically in detecting diabetic retinopathy. His work, showcased in a detailed review published in “Results in Optics,” emphasizes leveraging advanced AI models to improve diagnostic accuracy in ophthalmology. Collaborating with Amit Jain and Navpreet Kaur Walia, Bansal explores the potential of AI to revolutionize disease detection, highlighting the role of technology in enhancing healthcare outcomes. His research aligns with the domains of medical AI and computer vision, contributing significantly to the field of healthcare technology and artificial intelligence. 🧠👁️💡

Publication Top Notes

Diabetic retinopathy detection through generative AI techniques: A review