Ruochen Li | Artificial Intelligence | Best Researcher Award

Posted on by Global Sensor Awards

Ruochen Li | Artificial Intelligence | Best Researcher Award

Dr. Ruochen Li, BOHUA UHD Co., Ltd. , China.

Ruochen Li, PhD candidate at Macau University of Science and Technology, specializes in Artificial Intelligence with a focus on no-reference video quality assessment, cross-modal audio-visual retrieval, and image-based sound source localization. With expertise in cutting-edge AI technologies like PyTorch, TensorFlow, and MindSpore, Li has achieved groundbreaking research in video quality evaluation and audio-visual content correlation, earning recognition in top-tier journals. He has also received a prize in the National Artificial Intelligence Competition for his contributions to ultra-high-definition video processing.Β πŸ“ŠπŸ“ΉπŸ”

Publication Profile

Scopus

Education and Experience

  • πŸŽ“Β PhD in Artificial IntelligenceΒ (2021-2024), Macau University of Science and Technology.
  • πŸŽ“Β Master’s in Control EngineeringΒ (2016-2019), Jiangsu University of Science and Technology.
    • Supervisor: Associate Prof. Shuxia Ye.
  • πŸŽ“Β Bachelor’s in Control EngineeringΒ (2012-2016), Jiangsu University of Science and Technology.
  • πŸ“‘Β Research Participant: National Ultra-High Definition Video Innovation Center.
  • πŸ“‘Β Research Contributor: China Science and Technology Information Research Institute.

Suitability For The Award

Dr. Ruochen Li is an accomplished researcher specializing in artificial intelligence, video quality assessment, and audio-visual event retrieval. With a Ph.D. in Artificial Intelligence from Mauca University of Science and Technology and extensive expertise in PyTorch, TensorFlow, and MindSpore, Li has contributed significantly to advancing multimedia technologies. Their innovations include state-of-the-art datasets, algorithms like Reformer, and multimodal fusion techniques with applications in accessibility, entertainment, and surveillance. Recognized through high-impact publications and awards, including third prize in the National Artificial Intelligence Competition, Ruochen Li exemplifies excellence in research and innovation, making them a strong candidate for prestigious honors such as the Best Researcher Award.

Professional Development

Ruochen Li’s professional journey is defined by innovations in AI and deep learning. He developed the UHD-VQ5k dataset and proposed novel algorithms for ultra-high-definition video quality assessment, utilizing advanced models like Resformer. His work in audio-visual content analysis, featured in his doctoral dissertation, emphasizes the integration of audio-visual features using deep neural networks. As a key participant in national projects, he has contributed to cloud-based UHD video platforms and AI policy analysis. His collaborations and publications underscore his commitment to advancing AI research and applications.Β πŸ“ŠπŸ€–πŸ“ˆ

Research Focus

Ruochen Li’s research revolves around Artificial Intelligence applications in multimedia. His expertise spans no-reference video quality assessment, where he develops datasets and benchmarks for UHD video, to cross-modal audio-visual retrieval, enhancing machine understanding of multimodal content. His work also extends to image-based sound source localization, integrating audio-visual data for precise event detection. Through pioneering algorithms, Li bridges gaps between modalities, advancing the interplay of audio and video content in deep learning applications. His contributions drive progress in multimedia AI.Β πŸŽ₯πŸ”ŠπŸ§ 

Awards and Honors

  • πŸ†Β Prize Winner: National Artificial Intelligence Competition.
  • πŸ…Β CET-6 Certificate: Scored 490.
  • πŸ…Β CET-4 Certificate: Scored 552.

Publication Top Notes

  • πŸ“œΒ SgLFT: Semantic-guided Late Fusion Transformer for Video Corpus Moment RetrievalΒ – Neurocomputing, 2024.Β πŸ“š
  • πŸ“œΒ Ultrahigh-definition Video Quality Assessment: A New Dataset and BenchmarkΒ – Neurocomputing, 2024,Β πŸ“Š
  • πŸ“œΒ TA2V: Text-Audio Guided Video GenerationΒ – IEEE Transactions on Multimedia, 2024,Β πŸŽ₯🎢
  • πŸ“œΒ Cross-Modality Knowledge Calibration Network for Video Corpus Moment RetrievalΒ – IEEE Transactions on Multimedia, 2024,Β Β πŸŒπŸ“‘
  • πŸ“œΒ Maximizing Mutual Information Inside Intra- and Inter-Modality for Audio-Visual Event RetrievalΒ – International Journal of Multimedia Information Retrieval, 2023,Β πŸ”—πŸŽ§

Prof. Yuguo Yu | Artificial Neural Awards | Best Researcher Award

Posted on by Global Sensor Awards

Prof. Yuguo Yu | Artificial Neural Awards | Best Researcher AwardΒ Β 

Prof. Yuguo Yu, Fudan University, China

Yuguo Yu, Ph.D., is a distinguished professor in Brain-inspired Artificial Intelligence and Computational Neuroscience at Fudan University, where he has been a faculty member since 2011. He currently serves as a professor at both the Research Institute of Intelligent Complex Systems and the National Key Laboratory of Medical Neurobiology. Yu obtained his Bachelor’s degree in Physics from Lanzhou University in 1995 and completed his Ph.D. in Condensed Matter Physics at Nanjing University in 2001. He pursued postdoctoral training in Computational/Behavior Neuroscience at Carnegie Mellon University from 2001 to 2004 and was an Associate Research Scientist at Yale University from 2005 to 2011, where he continues to contribute as a visiting Research Scientist since 2021. Yu has been recognized for his academic excellence through prestigious awards, including the Shanghai Eastern Scholar Professorship in 2013 and the Shanghai Excellent Academic Leader award in 2021. He is an active member of the Chinese Society of Computational Neuroscience and serves as an associate editor for several prominent journals, including IEEE Transactions on Cognitive and Developmental Systems and Frontiers in Computational Neuroscience. His research interests encompass brain-inspired neural networks, cellular mechanisms of energy-efficient cortical dynamics, synaptic learning mechanisms, and large-scale cortical network modeling, with over 100 publications in leading journals such as Nature and Neuron. Yu has also led or participated in numerous national foundation projects, advancing the field of computational neuroscience.

Professional Profile:

GOOGLE SCHOLAR

Research for Best Researcher Award

Candidate Overview: Dr. Yuguo Yu is a prominent researcher and professor in Brain-inspired artificial intelligence and computational neuroscience at Fudan University. With extensive academic and research experience, he is a strong candidate for the Best Researcher Award due to his significant contributions to the field, impactful publications, and leadership roles.

Education

  • B.Sc. in Physics
    Lanzhou University, 1995
  • Ph.D. in Condensed Matter Physics
    Nanjing University, 2001
  • Postdoctoral Researcher in Computational Neuroscience
    Carnegie Mellon University, 2001–2004
  • Research Scientist in Neurobiology
    Yale University, 2005–2011

Work Experience

  • Professor
    Research Institute of Intelligent Complex Systems, Fudan University, 2020–Present
  • Professor
    National Key Laboratory of Medical Neurobiology, Fudan University, 2013–Present
  • Visiting Research Scientist
    Yale University School of Medicine, 2021–Present
  • Associate Research Scientist
    Department of Neuroscience, Yale University, 2005–2011

Research Interests:

  • Brain-inspired Intelligence and Computational Neuroscience
  • Neural Computation Model
  • Neural Coding Theory
  • Network Topology Analysis
  • Sensory Fusion Mechanism
  • Brain Connectome Atlas
  • Self-organizing Learning Algorithm
  • Multi-sensory Fusion Model
  • Low-power Mechanism of the Human Brain πŸ”

PublicationΒ Top Notes

CITED:1904
CITED:444
CITED:300
CITED:238
CITED:219

CITED:216

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award

Posted on by Global Sensor Awards

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher AwardΒ 

Prof. Dr. Tamara Gajic, Geographical Institute “Jovan Cvijic” Serbian Academy of Sciences and Arts, Belgrade, Serbia

Tamara GajiΔ‡ is a distinguished Senior Research Associate at the Geographical Institute “Jovan CvijiΔ‡” of the Serbian Academy of Sciences and Arts (SASA), specializing in social geography. She holds a Ph.D. in Geosciences from the University of Novi Sad and has extensive experience in research and education across various institutions. Her academic career spans several positions, including Senior Researcher at the Institute of Environmental Engineering, People’s Friendship University of Russia (RUDN University), and Associate Professor at Singidunum University in Belgrade. She has also served as a professor and assistant professor at various universities in Serbia, Bosnia, and Herzegovina. Gajić’s research focuses on rural development, tourism management, and sustainable practices in agritourism, gastrotourism, and sport tourism. She has contributed to numerous projects, including the modernization of tourism study programs in Serbia and feasibility studies for spa tourism. GajiΔ‡ is an active member of various professional organizations, including the Serbian Geographical Society and the Tourist Organization of Serbia, and has mentored numerous graduate and doctoral students. Her expertise in integrating economics, service quality, and human resources in tourism management has earned her recognition as one of the top 10% of distinguished scientists in Serbia in 2024.

Professional Profile:

SCOPUS

ORCID

GOOGLE SCHOLAR

Suitability of Tamara Gajić for the Top Researcher Award

Tamara Gajić is highly qualified for the Top Researcher Award due to her extensive academic and professional achievements in the fields of Geography, Rural Studies, and Tourism Management. Below are the key reasons why she is a suitable candidate for this prestigious award:

Academic Degrees:

πŸŽ“ Ph.D. in Geosciences
πŸ“… 2010
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia πŸ‡·πŸ‡Έ

πŸŽ“ M.Sc. in Tourism Management
πŸ“… 2007
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia πŸ‡·πŸ‡Έ

πŸŽ“ B.Sc. in Tourism Management
πŸ“… 2001
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia πŸ‡·πŸ‡Έ

Research & Teaching Interests:

🌍 Research Areas:

  • Geography 🌍
  • Rural Studies 🌾
  • Tourism Management 🌐
    Focus on Agrotourism, Gastrotourism, and Sport Tourism πŸžοΈπŸ΄πŸƒβ€β™€οΈ
    Intersection of Economics in Tourism, Service Quality, and Human Resources πŸ’Ό
    Sustainability in Environment and Tourism 🌱

Previous Employment:

  • Associate Professor
    πŸ“… February 2021 – September 2021
    Faculty of Tourism and Hotel Management, Singidunum University, Belgrade, Serbia πŸ‡·πŸ‡Έ
  • Assistant Professor
    πŸ“… October 2018 – February 2022
    University for Business Studies, Banja Luka, Bosnia and Herzegovina πŸ‡§πŸ‡¦
  • Professor of Vocational Studies
    πŸ“… October 2008 – February 2021
    Novi Sad Business School, Novi Sad, Serbia πŸ‡·πŸ‡Έ

Publication top Notes:

Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability

The Contribution of the Farm to Table Concept to the Sustainable Development of Agritourism Homesteads

Fostering Sustainable Urban Tourism in Predominantly Industrial Small-Sized Cities (SSCs)β€”Focusing on Two Selected Locations

Leveraging digital platforms for responsible sports tourism: Budapest’s role in the 2020 European football championship

Tourists’ Willingness to Adopt AI in Hospitalityβ€”Assumption of Sustainability in Developing Countries

The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice

Prof. Hsin-Yuan Chen | AI Awards | Outstanding Scientist Award

Posted on by Global Sensor Awards

Prof. Hsin-Yuan Chen | AI Awards | Outstanding Scientist Award

Prof. Hsin-Yuan Chen, Zhejiang University, China

H.Y. J. Chen is an accomplished researcher with expertise spanning multiple fields including bioengineering, materials science, and guidance system technologies. Holding a Web of Science ResearcherID (JSL-7102-2023) , Chen has an impressive H-index of 58, with over 11,000 citations accumulated from works published between January 2000 and March 2024. Some of Chen’s notable contributions include studies on biochar anodes for lithium-ion batteries, computational fluid dynamics (CFD) analysis of cormorant takeoff mechanisms, and innovations in van der Waals semiconductor photodetectors. Chen’s interdisciplinary work also extends into preprints and collaboration on machine learning applications in conformal field theories.

Professional Profile:

Scopus

Suitability Summary for Research for Outstanding Scientist Award

Researcher: H.Y. J. Chen

Summary:

H.Y. J. Chen stands out as a highly suitable candidate for the Research for Outstanding Scientist Award due to his exceptional contributions and interdisciplinary expertise across multiple scientific domains. Chen’s research spans bioengineering, materials science, and guidance system technologies, showcasing a profound impact on these fields.

πŸŽ“Education:

H.Y. J. Chen is an accomplished researcher with expertise in bioengineering, materials science, and guidance system technologies. Chen earned both his Master’s and Bachelor’s degrees, as well as a Ph.D., from National Cheng Kung University, Taiwan.

Publication Top Notes:

  • Protective Effects of an Oligo-Fucoidan-Based Formula Against Osteoarthritis Development via iNOS and COX-2 Suppression Following Monosodium Iodoacetate Injection
    • Citations: 0
  • Hinokitiol Inhibits Breast Cancer Cells In Vitro Stemness-Progression and Self-Renewal with Apoptosis and Autophagy Modulation via the CD44/Nanog/SOX2/Oct4 Pathway
    • Citations: 1
  • Alleviating 3-MCPD-Induced Male Reproductive Toxicity: Mechanistic Insights and Resveratrol Intervention
    • Citations: 1
  • Hinokitiol as a Modulator of TLR4 Signaling and Apoptotic Pathways in Atopic Dermatitis
    • Citations: 1
  • Integrating Explainable Artificial Intelligence and Blockchain to Smart Agriculture: Research Prospects for Decision Making and Improved Security
    • Citations: 7

 

 

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher AwardΒ 

Mr. Omer Tariq, Korea Advanced Institute of Science and Technology, KAIST, South Korea

Omer Tariq is a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), specializing in efficient and privacy-preserving deep learning for AIoT and autonomous systems. With a strong foundation in digital ASIC design, embedded systems, and hardware design, Omer has over seven years of experience in developing and deploying innovative machine learning solutions using TensorFlow, TensorRT, and PyTorch. His research includes advanced robotics software systems, autonomous navigation, and state-of-the-art motion planning algorithms. He has led teams in high-performance SoC/RTL design and verification at the National Electronics Complex, Pakistan, and contributed to satellite imaging systems at SUPARCO. Omer holds a BSc in Electrical Engineering from the University of Engineering and Technology, Taxila, and has published several papers in prominent journals. His technical skills are complemented by a range of certifications in machine learning, data science, and digital signal processing.

Professional Profile:

Summary of Suitability for Best Researcher Award

Omer Tariq is a Ph.D. candidate specializing in efficient and privacy-preserving deep learning for AIoT and Autonomous Systems. His work is highly relevant to current technological advancements and addresses significant challenges in machine learning, robotics, and autonomous systems. His research includes:

Education

Korea Advanced Institute of Science and Technology (KAIST)
Doctor of Philosophy (Ph.D.) in Computer Science
May 2021 – July 2025

  • Majors: Machine Learning & AI
  • CGPA: 3.74/4.3
  • Coursework: Programming for AI, Introduction to Artificial Intelligence, Design and Analysis of Algorithms, Intelligent Robotics, Human-Computer Interaction, Artificial Intelligence and Machine Learning, Technical Writing for Computer Science, Advanced Machine Learning, IoT Datascience

University of Engineering and Technology (UET), Taxila
Bachelor of Science in Electrical Engineering
Nov 2010 – July 2014

  • CGPA: 3.25/4.0
  • Thesis: Computer Vision-Assisted Object Detection and Control Framework for 3-DoF Robotic Arm
  • Area: Microelectronics, Control Systems, and Advanced Computer Architecture

Work Experience

Department of Industrial & Systems Engineering (ISysE), KAIST
Research Assistant
Nov. 2023 – March 2024

  • Designed and developed the electronics and power management module for the DAIM-Autonomous Mobile Robot, enhancing operational efficiency and reliability.
  • Engineered advanced robotics software systems for autonomous navigation and task execution.
  • Implemented state-of-the-art robot motion planning, mapping, and localization (SLAM) algorithms to improve real-time navigation accuracy.

National Electronics Complex, Pakistan (NECOP)
Engineering Manager & Team Lead
Apr. 2019 – Sep. 2022

  • Led verification and validation of high-performance SoC/RTL designs, ensuring system performance and reliability.
  • Spearheaded RTL development and optimization for high-performance IC designs, including logic synthesis, DFT, scan chain insertion, formal verification, and static timing analysis.
  • Managed the use of Synopsys and Cadence EDA tools for front-end and back-end digital IC design processes.

National Space Agency, Pakistan (SUPARCO)
Assistant Manager
Oct. 2014 – Apr. 2019

  • Designed and developed satellite imaging payload systems for national satellite missions.
  • Engineered high-speed, multi-layer PCB designs and conducted signal/power integrity simulations for satellite systems.
  • Developed embedded systems for the Satellite Ku-Band Positioning Unit, enhancing communication and positioning capabilities.

Publication top Notes:

2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation

TabCLR: Contrastive Learning Representation of Tabular Data Classification for Indoor-Outdoor Detection

Compact Walsh–Hadamard Transform-Driven S-Box Design for ASIC Implementations

DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors

 

 

Mr. Lianfa Li | Artificial Intelligence Award | Top Researcher Award

Posted on by Global Sensor Awards

Mr. Lianfa Li | Artificial Intelligence Award | Top Researcher AwardΒ 

Mr. Lianfa Li, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, ChinaΒ 

Dr. Lianfa Li is a distinguished Senior Research Associate and Lead Data Scientist at the University of Southern California’s Department of Population and Public Health Sciences. Since August 2017, he has been at the forefront of innovations in data science and machine learning, with a particular focus on remote sensing and air pollution modeling to study exposure and health effects. Dr. Li’s academic journey began with a Bachelor of Science in Resources, Planning, and Management from Nanjing University in 1998, followed by a Ph.D. in Geographical Information Science from the Institute of Geographical Sciences and Natural Resources Research at the Chinese Academy of Sciences in 2005. His career includes significant roles such as Associate Professor at the Chinese Academy of Sciences, Postdoctoral Scholar and Associate Specialist at the University of California, Irvine, and Research Associate at USC’s Department of Preventive Medicine.

Professional Profile:

 

ORCID

 

Summary of Suitability for the Top Researcher Award

Lianfa Li, PhD, currently a Senior Research Associate and Lead Data Scientist at the University of Southern California’s Department of Population and Public Health Sciences, is an exemplary candidate for the Top Researcher Award. His extensive background in data science and machine learning, particularly in the realm of remote sensing and air pollution exposure, positions him as a leader in his field. Below are the reasons why Dr. Li is suitable for this prestigious award:

EDUCATION πŸŽ“πŸ“š

  • PhD in Geographical Information Science (June 2005)
    Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
    Advisor: Prof. Jinfeng Wang
  • Bachelor of Science in Resources, Planning and Management (Aug 1998)
    Nanjing University, Nanjing, Jiangsu Province, China
    Advisor: Prof. Yunliang Shi

ACADEMIC EMPLOYMENT πŸ›οΈπŸ’Ό

  • Senior Research Associate, Lead Data Scientist (Aug 2017-Present)
    Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
    Leading innovations in data science and machine learning, and the modeling efforts in remote sensing and air pollution (exposure and health effects)
  • Research Associate (Aug 2017-July 2014)
    Department of Preventive Medicine, University of Southern California, Los Angeles, CA
  • Associate Specialist (June 2013-June 2014)
    Program in Public Health, University of California, Irvine, CA

HONORS AND AWARDS πŸ†πŸŽ–οΈ

  1. 2010.6
    The paper about Bayesian risk modeling (Risk Analysis, 30(7), 1157-1175) selected for a media outreach campaign in 2010 by Society for Risk Analysis
  2. 2007.5
    Chinese Academy of Sciences KC Wong Work Incentive Fund
  3. 2004.3
    The Excellent Presidential Scholarship of Chinese Academy of Sciences, 2004

WORKSHOP AND PRESENTATION πŸŽ€πŸ“…

  1. Biweekly workshop: β€œAir pollution and exposure modeling” (2015-present, University of Southern California, California, USA)
  2. Invited presentation: β€œGCN-assisted U-Net for segmentation of OCT images” (Bay area data science workshop, Mar. 27, 2021)
  3. Invited presentation: β€œEnhancing semantic segmentation with contextual information” (Bay area data science workshop, Dec. 07, 2019)

Publication top Notes:

Geocomplexity Statistical Indicator to Enhance Multiclass Semantic Segmentation of Remotely Sensed Data with Less Sampling Bias

Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation

Generating Fine-Scale Aerosol Data through Downscaling with an Artificial Neural Network Enhanced with Transfer Learning

Encoder–Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation

Multi-Scale Residual Deep Network for Semantic Segmentation of Buildings with Regularizer of Shape Representation

Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation

Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award

Posted on by Global Sensor Awards

Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher AwardΒ 

Prof. Changgyun Kim, Department of Artificial Intelligence & Software/Samcheok,South Korea

Changgyun Kim is an esteemed academic and researcher associated with Kangwon National University, Department of Artificial Intelligence & Software, and Dongguk University’s Industrial Engineering department in South Korea. His research expertise spans deep learning, healthcare, and data mining. He has made significant contributions to the field, including developing AI-based systems for detecting betting anomalies in sports, diagnosing tooth-related diseases using panoramic images, and creating models for obesity diagnosis using 3D body information. His work is published in renowned journals such as Scientific Reports, Annals of Applied Sport Science, JMIR Medical Informatics, Sensors, Sustainability, the International Journal of Distributed Sensor Networks, and Applied Sciences. Dr. Kim’s notable projects include establishing IoT-based smart factories for SMEs in Korea and developing web applications for obesity diagnosis using data mining methodologies. His extensive research portfolio underscores his commitment to advancing AI applications in various domains

Professional Profile:

ORCID

 

Education

No specific details about Changgyun Kim’s educational background are provided in the provided information. To give a more comprehensive overview, details such as degrees obtained, institutions attended, and fields of study would be needed.

Work Experience

  1. Dongguk University: Jung-gu, Seoul, KR
    • Department: Industrial Engineering
    • Position: Not specified in the provided information.
  2. Kangwon National University
    • Department: Artificial Intelligence & Software
    • Position: Not specified in the provided information.

Publication top Notes:

 

AI-based betting anomaly detection system to ensure fairness in sports and prevent illegal gambling

Detectability of Sports Betting Anomalies Using Deep Learning-based ResNet: Utilization of K-League Data in South Korea

Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values

Development of a Web Application Based on Human Body Obesity Index and Self-Obesity Diagnosis Model Using the Data Mining Methodology

Establishment of an IoT-based smart factory and data analysis model for the quality management of SMEs die-casting companies in Korea