Larbi Boubchir | Computer Science Award | Best Researcher Award

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.

Huilong Fan | Computer Science | Best Researcher Award

Dr Huilong Fan |  Computer Science |  Best Researcher Award

assistant researcher at  University of Electronic Science and Technology of China

Huilong Fan is a research assistant at the University of Electronic Science and Technology of China, born in December 1992, and residing in Changsha, Hunan. He specializes in Edge Computing and Artificial Intelligence.

profile

Academic Background:

  • Ph.D. in Computer Science and Technology, Central South University (2019-2023)
    • Major: Satellite multi-intelligence collaborative computing, digital twins, swarm intelligence negotiation, multi-intelligence deep reinforcement learning, online scheduling, artificial intelligence, machine learning.
  • Master in Computer Science and Technology, Guizhou University (2015-2018)
    • Major: Medical big data, big data analysis and prediction, deep learning, multi-label data classification, natural language processing.
  • Bachelor in Network Engineering, Nanyang Institute of Technology (2010-2014)
    • Major: Computer Networks, Principles of Computer Composition, Operating Systems, Algorithm Design.

Professional Experience:

  • Data Analyst, Beijing Ark Hospital (June 2014-Sept 2015; Dec. 2023-Present)
    • Responsibilities: Data cleaning, analysis, and visualization, system development and maintenance, research on satellite networks, collaborative computing, and edge computing.
  • R&D Engineer, Hunan Lisen Data Technology Co Ltd (June 2018-Sept 2019)
    • Responsibilities: Algorithm design, multi-platform software architecture design, software development, database management, interface development and design.

Projects and Leadership:

  • Led projects on mixed integer programming for multi-process production scheduling, satellite and management software R&D, and real-time analysis methods for large-scale multi-source data based on supercomputing.
  • Participated in significant research such as intelligent analysis technology for TFDS images and resource allocation technology based on collaborative perception.

Awards and Patents:

  • Second prize in scientific and technological progress (2020)
  • First prize in the Guizhou Province Innovation and Entrepreneurship Competition (2016)
  • National third prize in the ‘Internet +’ College Students Innovation and Entrepreneurship Competition (2016)
  • Invention Patents: Multi-agent Space-based Information Network Task Scheduling Method (2021), Dynamic Reconfigurable Space-based Information Network Simulation and Computing System (2022).

Skills:

  • Proficient in software architecture design, Java, Python, C, and other programming languages.
  • Experienced in leading R&D teams and writing research project applications.

Research Focus in Computer Science:

Huilong Fan’s research in Computer Science spans several advanced and interdisciplinary areas, primarily focusing on:

  1. Satellite Multi-Intelligence Collaborative Computing:
    • Developing systems that allow multiple intelligent agents to work together effectively in satellite networks.
    • Utilizing collaborative algorithms to improve the efficiency and reliability of satellite communications and operations.
  2. Digital Twins:
    • Creating digital replicas of physical systems to simulate and analyze their real-world counterparts.
    • Applying digital twin technology to monitor, diagnose, and optimize satellite and network operations.
  3. Swarm Intelligence Negotiation:
    • Investigating algorithms that enable decentralized agents to coordinate and negotiate within a swarm.
    • Using swarm intelligence for tasks such as resource allocation and scheduling in dynamic environments.
  4. Multi-Intelligence Deep Reinforcement Learning:
    • Developing deep learning models that enable multiple intelligent agents to learn and adapt to complex environments.
    • Applying these models to solve problems in satellite networks and edge computing.
  5. Online Scheduling:
    • Researching methods for real-time scheduling of tasks and resources in dynamic and distributed systems.
    • Focusing on optimizing the allocation of contact windows in satellite communication networks.
  6. Artificial Intelligence and Machine Learning:
    • Applying AI and ML techniques to solve complex problems in big data analysis, prediction, and decision-making.
    • Emphasizing multi-label data classification and natural language processing for diverse applications.
  7. Medical Big Data:
    • Analyzing and predicting trends in medical data using big data technologies.
    • Developing models for deep learning and multi-label classification to enhance medical data interpretation and application.
  8. Graph-Driven Resource Allocation:
    • Utilizing graph theory and cooperative game theory to optimize resource allocation in Internet of Things (IoT) and satellite networks.
    • Developing adaptive scheduling algorithms for real-time and dynamic environments.

Through his extensive research, Huilong Fan aims to push the boundaries of what is possible in satellite communication, edge computing, and AI, contributing significantly to advancements in these fields.

Publication Top Notes:

  • Dynamic Network Resource Autonomy Management and Task Scheduling Method Li, X., Yang, J., Fan, H.
    Mathematics, 2023, 11(5), 1232. Citations: 6
  • A novel multi-satellite and multi-task scheduling method based on task network graph aggregation Fan, H., Yang, Z., Zhang, X., Long, J., Liu, L.
    Expert Systems with Applications, 2022, 205, 117565. Citations: 15
  • A Spatio-Temporal Graph Neural Network Approach for Traffic Flow Prediction Li, Y., Zhao, W., Fan, H.
    Mathematics, 2022, 10(10), 1754. Citations: 6
  • Quantum Digital Signature with Continuous-Variable Deng, X., Zhao, W., Shi, R., Ding, C., Fan, H.
    International Journal of Theoretical Physics, 2022, 61(5), 144. Citations: 3

 

Vipin Bansal | Computer Science Award | Academic Summit Impact Award

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