Yunge Zou | Computer Science | Best Scholar Award

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Dr. Yunge Zou | Computer Science | Best Scholar Award

Dr. Yunge Zou, Chongqing University, China

Dr. Yunge Zou is a Ph.D. scholar at Chongqing University, specializing in hybrid powertrain design and battery degradation in the Department of Automotive Engineering. He is a talent under the Chongqing Excellence Program and a Shapingba Elite Talent (2023–2025). Dr. Zou has led key projects, including the National Key R&D Program, focusing on high-efficiency powertrain technologies. His contributions include innovative methods like Hyper-Rapid Dynamic Programming, which optimizes multi-mode hybrid powertrains. With multiple patents and high-impact publications, he collaborates with leading automotive firms like Chang’an New Energy, advancing sustainable transportation. πŸš—πŸ”‹πŸ“š

 

Publication Profile

Orcid

Google Scholar

Academic and Professional Background πŸ”‹

Dr. Yunge Zou earned his B.E. degree in Automotive Engineering from Chongqing University, China, in 2018. Currently, he is pursuing his Ph.D. in hybrid powertrain design and optimization at the Vehicle Power System Lab, Department of Automotive Engineering, Chongqing University. Recognized for his exceptional talent, Dr. Zou is part of the prestigious Chongqing Excellence Program and was honored as a Shapingba Elite Talent for 2023–2025. His research focuses on hybrid powertrain topology design, battery degradation, energy management systems (EMS), and enhancing battery life, contributing to sustainable transportation innovation. πŸ“šπŸ”§πŸŒ±

 

Research and Innovations πŸš—

Dr. Yunge Zou is leading several groundbreaking research projects in the field of hybrid powertrain design and optimization. His work includes the National Key Research and Development Program of China on high-efficiency range extender assembly and electric vehicle integration (2022-2024), with a funding of 2.5 million yuan. He is also working on optimizing hybrid electric vehicle design through the National Science Fund for Excellent Young Scholars (2023-2025). Additionally, he contributes to various projects focusing on hybrid vehicle dynamics, energy efficiency, and low-emission technologies, backed by substantial funding from multiple prestigious organizations. πŸ› οΈβš‘

 

πŸ› οΈ Research Focus

Dr. Yunge Zou’s research primarily focuses on hybrid powertrain design and optimization for electric and range-extended vehicles. His work includes the development of control strategies and topology design for hybrid systems, aiming to improve fuel economy, efficiency, and reduce emissions. Dr. Zou has made significant advancements in aging-aware optimization and mode-switching mechanisms for multi-mode hybrid vehicles. His contributions also extend to battery degradation, energy management, and the computational efficiency of fuel economy assessment using innovative algorithms like Hyper Rapid Dynamic Programming (HR-DP). His work is instrumental in the evolution of transportation electrification. πŸš—βš‘

 

Publication Top Notes

  • “Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory” – Energy 242, 122944 (Cited by 14, 2022) πŸ”‹
  • “Aging-aware co-optimization of topology, parameter and control for multi-mode input-and output-split hybrid electric powertrains” – Journal of Power Sources 624, 235564 (Cited by 1, 2024) βš™οΈ
  • “Design of optimal control strategy for range extended electric vehicles considering additional noise, vibration and harshness constraints” – Energy 310, 133287 (Cited by 1, 2024) πŸš—
  • “Computationally efficient assessment of fuel economy of multi-modes and multi-gears hybrid electric vehicles: A Hyper Rapid Dynamic Programming Approach” – Energy, 133811 (Cited by 0, 2024) πŸ”§

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.

PublicationΒ 

  • Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities πŸ“‰ – Cited by 155, 2005
  • Face–iris multimodal biometric identification system πŸ•΅οΈβ€β™‚οΈ – Cited by 104, 2020
  • Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters βœ‹ – Cited by 89, 2016
  • Multivariate statistical modeling of images with the curvelet transform πŸ“Š – 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 Ξ±-stable prior πŸ“ˆ – 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 πŸ”¬ – Cited by 49, 2017
  • Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states πŸ” – Cited by 45, 2020
  • Robust model-free gait recognition by statistical dependency feature selection and globality-locality preserving projections πŸšΆβ€β™‚οΈ – Cited by 39, 2016
  • Human gait recognition based on Haralick features πŸšΆβ€β™€οΈ – Cited by 38, 2017
  • Face–iris multi-modal biometric system using multi-resolution Log-Gabor filter with spectral regression kernel discriminant analysis πŸ“Έ – Cited by 37, 2018
  • Palm vein recognition based on competitive coding scheme using multi-scale local binary pattern with ant colony optimization πŸ–οΈ – Cited by 36, 2020
  • Human gait recognition using GEI-based local multi-scale feature descriptors πŸ•Ί – 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 , Β  Β 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. πŸ“Š 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. πŸš— He is pursuing a PhD in Explainable AI and has authored significant research in the field. πŸ“œ Passionate about leading teams and driving technological advancements, he continues to excel in the dynamic tech landscape. πŸ’Ό

Publication Profile

Orcid

Education πŸŽ“

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. πŸ§‘β€πŸŽ“

Work Experience πŸ’Ό

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. πŸš—

Research Focus πŸ“šπŸ”¬

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. πŸ§ πŸ‘οΈπŸ’‘

Publication Top Notes

Diabetic retinopathy detection through generative AI techniques: A review