Prof. Dr. Cedric Sueur | Artificial intelligence | Best Researcher Award

Prof. Dr. Cedric Sueur | Artificial intelligence | Best Researcher Award 

Prof. Dr. Cedric Sueur, Université de Strasbourg, France

Cédric Sueur is a French ethologist and primatologist renowned for his contributions to the study of animal behavior and social ecology. He is a Full Professor at the University of Strasbourg and a Fellow of the Institute for Advanced Study, as well as a member of the French Academic Institute. He holds a Ph.D. in Ethology from Louis Pasteur University, Strasbourg, and the Free University of Brussels, along with an HDR qualification to supervise doctoral theses. Throughout his career, he has held prestigious academic positions, including Associate Professor at the University of Strasbourg, Visiting Professor at Kyoto University, Sun Yat-sen University, and Lille Catholic University. His research has been widely recognized, earning him numerous accolades such as the Changjiang Scholar Program award, the Adolphe Wetrems Award from the Royal Academies for Science and the Arts of Belgium, and recognition among the world’s top 2% of scientists by Stanford University. With a strong academic and research background, Sueur continues to contribute significantly to the field of ethology and primatology.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Cédric Sueur

Cédric Sueur is a highly accomplished researcher in Ethology and Primatology, making him a strong contender for the Best Researcher Award. His outstanding academic background, extensive research contributions, prestigious honors, and leadership in the scientific community establish him as an influential figure in his field.

🎓 Education

  • 2014: HDR, Habilitation to Supervise Doctoral Theses

  • 2008: PhD in Ethology – Primatology, Louis Pasteur University, Strasbourg & Free University of Brussels

  • 2005: Master’s Degree, University Louis Pasteur, Strasbourg (With Honours)

  • 2003: Bachelor’s in Organisms’ Biology, University 14USTL, Lille (With Honours)

💼 Work Experience

  • Since 2024: Full Professor, University of Strasbourg

  • Since 2021: Invited Professor, Lille Catholic University

  • 2011-2024: Associate Professor, University of Strasbourg (Outstanding since 2022)

  • 2022 (Jan-Mar): Invited Professor, Kyoto University Institute for Advanced Study

  • 2016 (Jul-Aug): Invited Professor, Sun-Yat Sen University, China (Changjiang Scholar Program award)

  • 2008-2012: Research Associate, Unit of Social Ecology, Free University of Brussels

  • 2010-2011: Research Fellow, Primate Research Institute, Kyoto University

  • 2009-2010: Research Associate, Ecology & Evolutionary Biology, Princeton University

  • 2007-2008: Lecturer in Ethology, Strasbourg University

🏆 Awards & Honors

  • 2025: Selected for the Lumexplore Prize by the French Society of Explorers 🏅

  • 2025: Selected for the François Sommer Prize 🏆

  • 2024-2029: Member of the “Institut Universitaire de France” 🎖️

  • 2023: Best Communication Prize at Aramos Congress 🏅

  • 2023: Named Best Scientist by Research.com 🌍

  • 2022: Listed among the World’s Top 2% of Scientists by Stanford University 📊

  • 2022: Named Best Scientist by Research.com 🏅

  • 2019: Adolphe Wetrems Award from the Royal Academies for Science and the Arts of Belgium 🏆

  • 2019-2024: Fellow of the Institut Universitaire de France 🎖️

  • 2017: Primates Social Impact Award 🏅

  • 2016: Changjiang Scholar Program Award (Visiting Professor at Sun-Yat Sen University, China) 🇨🇳

  • 2014: Excellence Award from the French Minister of Higher Education and Research 🎓

  • 2013: Young Scientist Award from the French Society for the Study of Animal Behaviour (SFECA) 🏅

  • 2012: 3 papers among the Top 5 Cited Papers in International Journal of Primatology 📜

  • 2012: Fellow of the University of Strasbourg Institute for Advanced Study (USIAS) 🎓

  • 2010: JSPS Alumni (Japan Society for the Promotion of Science) 🇯🇵

  • 2009: Fulbright Alumni 🇺🇸

  • 2009: Prize of the Society of Biology of Strasbourg for Best Thesis 📜

  • 2009: “Le Monde de la Recherche Universitaire” Prize for Best Thesis 🎓

  • 2006-2010: Member of the European Doctoral College of Strasbourg 🌍

Publication Top Notes:

GITED:775
GITED:364
GITED:278
GITED:262
GITED:192
GITED:179
GITED:168

Mr. Xi Tianyu | Automation Award | Best Researcher Award

Mr. Xi Tianyu | Automation Award | Best Researcher Award

Mr. Xi Tianyu, Northeastern University, China

Dr. Xi Tianyu is a professor and doctoral supervisor at the Northeastern University School of Architecture, specializing in sustainable architecture, architectural technology, and green living. He has led over 10 national and provincial research projects, published more than 50 papers, and holds three authorized patents. He has contributed to national and industry standards, authored textbooks, and received multiple awards for teaching and research excellence. Dr. Xi is actively involved in several professional committees, including the China Urban Science Research Association and the China Engineering Construction Standardization Association, and is a member of international organizations such as ISIAQ and AIJ.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Xi Tianyu is a highly accomplished researcher in sustainable architecture, with extensive contributions to green building technologies, energy conservation, and thermal comfort optimization. His leadership in over 10 national and provincial research projects, along with 50+ published papers and multiple patents, demonstrates his strong research impact. His involvement in national standards development, textbook authorship, and architectural design competitions further highlights his influence in academia and industry. Given his outstanding research, academic leadership, and numerous accolades, Dr. Xi Tianyu is a highly suitable candidate for the Best Researcher Award.

📚 Education & Work Experience

🎓 Doctor of Engineering
🏫 Professor & Doctoral Supervisor at Northeastern University School of Architecture

🏆 Achievements

🔬 Led 10+ research projects (national, provincial, and local), including:

  • 🇨🇳 National Natural Science Foundation Key Project sub-projects
  • 🎯 National Natural Science Foundation Youth Fund

📄 Published 50+ research papers
📜 3 authorized patents
📘 Co-authored 5 national & industry standards
📖 Contributed to 2 textbooks & authored 1 book (funded by National Publishing Fund)

🎨 Guided 10+ international & domestic architectural design competitions, winning:
🥇 Gu Yu Cup First Prize
🏅 AIM Cup Special Prize
🥉 China Habitat Environment Design Annual Award Bronze Award (2023)

🎖️ Awards & Honors

🏆 Northeastern University Teaching Achievement Awards:

  • 🥇 First Prize (2024)
  • 🥈 Second Prize (2022)
    🎓 Excellent Teaching Plan Award
    📜 Excellent Homework Guide Award
    📖 Excellent Paper Award (Chinese Higher Education Architecture Teaching Guidance Committee)

Publication Top Notes:

Analysis of the Characteristics of Heat Island Intensity Based on Local Climate Zones in the Transitional Season of Shenyang

 

Optimization of Residential Indoor Thermal Environment by Passive Design and Mechanical Ventilation in Tropical Savanna Climate Zone in Nigeria, Africa

 

A preliminary study of multidimensional semantic evaluation of outdoor thermal comfort in Chinese

 

Preliminary Research on Outdoor Thermal Comfort Evaluation in Severe Cold Regions by Machine Learning

A Review of Thermal Comfort Evaluation and Improvement in Urban Outdoor Spaces

Ahmet Güneyli | Artificial intelligence Awards | Best Researcher Award

Prof. Dr. Ahmet Güneyli | Artificial intelligence Awards | Best Researcher Award 

Prof. Dr. Ahmet Güneyli, European University of Lefka, Cyprus.

Ahmet GÜNEYLİ is a Professor of Turkish Language Teaching at the European University of Lefke in North Cyprus. With over two decades of academic experience, he has made significant contributions to Turkish language education, educational sciences, and teacher training. His career spans roles from Assistant Professor at Near East University to his current position as Professor. He supervises numerous master’s and Ph.D. theses, fostering research in multilingual education, instructional strategies, and educational management. Prof. GÜNEYLİ is an active participant in academic publishing and conference presentations, establishing himself as a leading figure in his field.

Professional Profile

Scopus

ORCID

Researcher Suitability Summary for Best Researcher Award

Professor Ahmet Güneyli exhibits exceptional academic and research credentials, positioning him as a strong candidate for the Research for Best Researcher Award. His scholarly achievements, significant contributions to Turkish language education, and commitment to mentoring young researchers underscore his suitability for this recognition.

Education 🎓

  • Undergraduate: Bachelor’s in Preschool & Primary School Education, Teachers Training College, Cyprus (2000).
  • Master’s: M.A. in Educational Sciences with a focus on Turkish Language Teaching, Ankara University, Turkey (2003).
  • Ph.D.: Educational Sciences specializing in Turkish Language Teaching, Ankara University, Turkey (2007).

Ahmet’s academic journey reflects his dedication to Turkish language education and instructional methodologies. His rigorous training has equipped him to address complex educational challenges effectively.

Experience 💼

Ahmet began his career as an Assistant Professor at Near East University in 2009, rising to Associate Professor in 2015. By 2021, he achieved full professorship at the European University of Lefke. His leadership includes supervising theses on multilingual education, bilingual instructional methods, and organizational analysis in education. His work combines practical applications with theoretical frameworks, enhancing education quality in Northern Cyprus.

Research Interests 🔬

Prof. GÜNEYLİ focuses on Turkish language education, bilingual instructional methods, and educational program evaluation. His interdisciplinary approach integrates educational sciences with language studies, aiming to advance instructional techniques and organizational efficiency in schools. His research supports inclusive and multilingual education policies.

Awards 🏆

Ahmet has earned numerous awards for his contributions to Turkish language teaching and educational sciences, underscoring his academic and professional excellence. These honors recognize his innovative teaching methods, impactful research, and dedication to advancing education.

Publications Top Notes 📚

Understanding University Students’ Foreign Language Learning Attitudes: An Analysis Based on Stereotypes

Exploring Teacher Awareness of Artificial Intelligence in Education: A Case Study from Northern Cyprus

Turkish Language Teachers’ Perspectives on Listening Skills Education in Turkey and Northern Cyprus

The effectiveness of virtual reality-based technology on foreign language vocabulary teaching to children with attention deficiency hyperactivity disorder

Examining Conjoint Behavioral Consultation to Support 2e-Autism Spectrum Disorder and Gifted Students in Preschool with Academic and Behavior Concerns

 

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science. 📚💻🌍

Publication Profiles 

Googlescholar

Education and Experience

  • Visiting Research Fellow – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present) 🎓
  • Senior Lecturer (Computer Science) – South Eastern University of Sri Lanka (2020 – Present) 🏫
  • Sessional Academic – School of Electrical Engineering & Computer Science, QUT (2016 – 2019) 📖
  • Lecturer (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015) 🧑‍🏫
  • Assistant Lecturer – South Eastern University of Sri Lanka (2010 – 2012) 🔍
  • Demonstrator in Computer Science – South Eastern University of Sri Lanka (2009 – 2010) 👨‍🔬

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement. 🏅📈📚

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research. 🔬⚙️🌐

Awards and Honors

  • Senate Honours Award for High Impact Publications – SEUSL (2022 & 2023) 🏆
  • Queensland University of Technology Postgraduate Award (QUTPRA) (2015) 📜
  • Faculty Write Up (FWU) Scholarship – QUT, Australia (2019) 📚
  • Effective Communication in Teaching and Learning – QUT, Australia (2019) 🗣️
  • Foundation of Teaching and Learning – QUT (2018) 🎓

Publication Top Notes 

  • Locating tables in scanned documents for reconstructing and republishing | Cited by: 46 | Year: 2014 📄🔍
  • Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14) | Cited by: 37 | Year: 2014 📊✏️
  • AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments | Cited by: 34 | Year: 2014 📄🛡️
  • Plagiarism detection tools and techniques: A comprehensive survey | Cited by: 23 | Year: 2021 🔎📚
  • Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges | Cited by: 11 | Year: 2023 🖐️📷
  • Contactless finger recognition using invariants from higher order spectra of ridge orientation profiles | Cited by: 10 | Year: 2018 ✋📏
  • Accelerating text-based plagiarism detection using GPUs | Cited by: 10 | Year: 2015 ⚡💻
  • Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants | Cited by: 9 | Year: 2018 🖐️🔗

Masoud DANESHTALAB | deep learning | Best Researcher Award

Prof. Masoud DANESHTALAB | deep learning | Best Researcher Award 

Prof. Masoud DANESHTALAB, Mälardalen University, Sweden.

Masoud Daneshtalab, Ph.D., Docent, Full Professor
Masoud Daneshtalab is a globally recognized scholar and Full Professor at Mälardalen University (MDU), Sweden. With over two decades of academic and professional excellence, he has made significant contributions to computer science and engineering, specializing in dependable systems, AI, and hardware/software co-design. A prolific researcher with an H-index of 35 and over 5,100 citations, Dr. Daneshtalab is included in the prestigious World’s Top 2% Scientists Ranking. He serves as the Scientific Director of Fundamental AI at MDU and collaborates internationally, holding adjunct professorships and contributing to cutting-edge research initiatives.

Professional Profile:

Google Scholar

Suitability of Masoud Daneshtalab for the Best Researcher Award

Dr. Masoud Daneshtalab is a highly suitable candidate for the “Research for Best Researcher Award,” based on his exceptional academic achievements and professional contributions. Here are the key reasons

Education

🎓 Academic Journey

  • Docent (2018): Qualified in Computer Science and Electronics, Mälardalen University, Sweden.
  • Ph.D. (2008–2011): Information and Communication Technology, University of Turku, Finland. Dissertation: Adaptive Implementation of On-Chip Networks under Prof. Hannu Tenhunen.
  • M.Sc. (2004–2006): Computer Engineering, University of Tehran, Iran. Thesis: Low Power Methods in Network-on-Chips under Prof. Ali Afzali-Kusha.
  • B.Sc. (1998–2002): Computer Engineering, Shahid Bahonar University of Kerman, Iran.

Experience

💼 Professional Contributions

  • Scientific Director (2024–Present): Fundamental AI, Mälardalen University, Sweden.
  • Full Professor (2020–Present): Innovation, Design & Engineering, MDU.
  • Adjunct Professor (2019–Present): Computer Systems, Tallinn University of Technology, Estonia.
  • Previous Roles: Associate Professor at MDU (2016–2020), EU Marie Curie Fellow at KTH Royal Institute of Technology (2014–2016), Lecturer at the University of Turku (2011–2014), and Researcher at the University of Tehran (2006–2008).

Research Interests

🔬 Key Areas

  • Optimization and robustness in deep learning models.
  • HW/SW co-design and heterogeneous computing.
  • Dependable systems, memory architectures, and interconnection networks.
  • Cutting-edge projects include sustainable AI, federated learning, and reliable autonomous systems.

Awards

🏆 Recognitions

  • Best Paper Awards: IEEE ECBS (2019), IEEE MCSoC (2018), and multiple HiPEAC Paper Awards (2013–2017).
  • Research Grants: Marie Skłodowska-Curie Fellowship (2014), Nokia Foundation (2009), and others.
  • Top Reviewer: IEEE Transactions on Computers (2013).
  • Fellowships: GETA, Helsinki University of Technology (2008–2011).

Publications

A review on deep learning methods for ECG arrhythmia classification

CITIED: 490

Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities

CITIED: 147

Routing algorithms in networks-on-chip

CITIED: 136

Smart hill climbing for agile dynamic mapping in many-core systems

CITIED: 125

EDXY–A low cost congestion-aware routing algorithm for network-on-chips

CITIED: 124

Deep Maker: A multi-objective optimization framework for deep neural networks in embedded systems

CITIED: 122

 

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Assoc. Prof. Dr. Mahmoud Bayat, Research Institute of Forests and Rangelands, Iran

Mahmoud Bayat is an Assistant Professor at the Research Institute of Forests and Rangelands, part of the Agricultural Research, Education, and Extension Organization (AREEO) in Tehran, Iran. He earned his B.A., M.Sc., and Ph.D. degrees from the University of Tehran, specializing in forestry science. Mahmoud has collaborated with renowned researchers, including Dr. Charles P.-A. Bourque, Dr. Pete Bettinger, Dr. Eric Zenner, Dr. Aaron Weiskittel, Dr. Harold Burkhart, and Dr. Timo Pukkala. His research focuses on forest modeling and inventory, with particular interest in applying artificial intelligence and machine learning techniques in forestry. Currently, he is working on projects related to growth and yield models for uneven-aged and mixed broadleaf forests using neural networks and the monitoring and mapping of tree species richness in northern Iran’s forests through symbolic regression and artificial neural networks. Mahmoud is proficient in statistical tools such as SPSS and MATLAB, and he is eager to share his expertise and discuss potential collaborations. For more information, his profiles can be found on ResearchGate, Google Scholar, and Scopus.

Professional Profile:

SCOPUS

 

Mahmoud Bayat’s Suitability for the Research for Best Researcher Award

Based on the provided details, Mahmoud Bayat demonstrates a strong candidacy for the Research for Best Researcher Award due to his extensive academic and professional contributions. Below is a summary supporting his suitability

Education 🎓

  • Ph.D. in Forestry Science
    University of Tehran, Iran
  • M.Sc. in Forestry Science
    University of Tehran, Iran
  • B.A. in Forestry Science
    University of Tehran, Iran

Work Experience 🏢

  • Assistant Professor
    Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO)
    Tehran, Iran
    Year: [Specify Year] – Present
  • Research Collaborator
    Worked with:

    • Dr. Charles P.-A. Bourque
    • Dr. Pete Bettinger
    • Dr. Eric Zenner
    • Dr. Aaron Weiskittel
    • Dr. Harold Burkhart
    • Dr. Timo Pukkala

Research Interests 🔍

  • Forest modeling and inventory
  • Application of artificial intelligence and machine learning in forestry

Current Projects 📊

  1. Growth and Yield Models for Uneven-Aged and Mixed Broadleaf Forest
    • Method: Neural Network
  2. Monitoring, Mapping, and Modeling Variation in Tree Species Richness
    • Method: Symbolic Regression and Artificial Neural Networks
    • Location: Northern Iran Forests

Publication Top Notes:

Comparison of Random Forest Models, Support Vector Machine and Multivariate Linear Regression for Biodiversity Assessment in the Hyrcanian Forests

Projected biodiversity in the Hyrcanian Mountain Forest of Iran: an investigation based on two climate scenarios

Recreation Potential Assessment at Tamarix Forest Reserves: A Method Based on Multicriteria Evaluation Approach and Landscape Metrics

Comparison between graph theory connectivity indices and landscape connectivity metrics for modeling river water quality in the southern Caspian sea basin

Development of multiclass alternating decision trees based models for landslide susceptibility mapping

Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests

 

Ruochen Li | Artificial Intelligence | Best Researcher Award

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. 📊📹🔍

Publication Profile

Scopus

Education and Experience

  • 🎓 PhD in Artificial Intelligence (2021-2024), Macau University of Science and Technology.
  • 🎓 Master’s in Control Engineering (2016-2019), Jiangsu University of Science and Technology.
    • Supervisor: Associate Prof. Shuxia Ye.
  • 🎓 Bachelor’s in Control Engineering (2012-2016), Jiangsu University of Science and Technology.
  • 📑 Research Participant: National Ultra-High Definition Video Innovation Center.
  • 📑 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. 📊🤖📈

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. 🎥🔊🧠

Awards and Honors

  • 🏆 Prize Winner: National Artificial Intelligence Competition.
  • 🏅 CET-6 Certificate: Scored 490.
  • 🏅 CET-4 Certificate: Scored 552.

Publication Top Notes

  • 📜 SgLFT: Semantic-guided Late Fusion Transformer for Video Corpus Moment Retrieval – Neurocomputing, 2024. 📚
  • 📜 Ultrahigh-definition Video Quality Assessment: A New Dataset and Benchmark – Neurocomputing, 2024, 📊
  • 📜 TA2V: Text-Audio Guided Video Generation – IEEE Transactions on Multimedia, 2024, 🎥🎶
  • 📜 Cross-Modality Knowledge Calibration Network for Video Corpus Moment Retrieval – IEEE Transactions on Multimedia, 2024,  🌐📑
  • 📜 Maximizing Mutual Information Inside Intra- and Inter-Modality for Audio-Visual Event Retrieval – International Journal of Multimedia Information Retrieval, 2023, 🔗🎧

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

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

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 🔍

Publication Top Notes

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

CITED:216

Mr. Seyed matin malakouti | Deep learning Awards | Best Researcher Award

Mr. Seyed matin malakouti | Deep learning Awards | Best Researcher Award

Mr. Seyed matin malakouti, University of Rijeka, Croatia

Seyed Matin Malakouti is an accomplished electrical engineer and researcher specializing in control systems engineering and machine learning. He completed his Master of Science in Electrical Engineering from the University of Tabriz, Iran, after earning his Bachelor’s degree from Isfahan University of Technology. His research spans various applications of machine learning, including wind power generation prediction, heart disease classification using ECG data, and solar farm power generation forecasting. Seyed’s work has resulted in several high-impact publications in prestigious journals, with his research on wind energy and machine learning techniques receiving significant citations. He has also been involved in cutting-edge projects such as predicting global temperature change and advancing renewable energy solutions. In recognition of his contributions, Seyed has received multiple awards, including the Best Researcher Award at the International Conference on Cardiology and Cardiovascular Medicine in 2023, and nominations for Best Paper and Best Researcher Awards in other international conferences. Additionally, he actively contributes to the scientific community as a peer reviewer for numerous journals in the fields of artificial intelligence, environmental sciences, and electrical engineering.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Seyed Matin Malakouti is a highly qualified and accomplished researcher in the field of Electrical Engineering, specializing in Control Systems, Machine Learning, and Data Science. His impressive academic background includes a Master’s degree in Electrical Engineering from the University of Tabriz and a Bachelor’s degree from Isfahan University of Technology.

Education & Training 🎓

  • 2020 – 2022: M.Sc. in Electrical Engineering – Control System Engineering, University of Tabriz, Iran
  • 2014 – 2019: B.Sc. in Electrical Engineering, Isfahan University of Technology, Iran

Awards & Honors 🏆

  • 2023: Best Researcher, International Conference on Cardiology and Cardiovascular Medicine
  • 2023: Nominated for Best Paper Award, International Research Awards on Mathematics and Optimization Methods
  • 2024: International Young Scientist Awards, Best Researcher Category

Technical Skills 🛠️

  • Machine Learning 🤖
  • Data Science 📊
  • Programming Languages: MATLAB, Python 💻

Peer Review Activities 🧐

Seyed has reviewed articles for prestigious journals, such as:

  • IEEE Access
  • Artificial Intelligence Review
  • BMC Public Health
  • Environmental Monitoring and Assessment 🌱

Publication top Notes:

Machine learning and transfer learning techniques for accurate brain tumor classification

ML: Early Breast Cancer Diagnosis

Advanced techniques for wind energy production forecasting: Leveraging multi-layer Perceptron + Bayesian optimization, ensemble learning, and CNN-LSTM models

Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in predicting wind speed and energy generation

Discriminate primary gammas (signal) from the images of hadronic showers by cosmic rays in the upper atmosphere (background) with machine learning

Estimating the output power and wind speed with ML methods: A case study in Texas

Gabriel Danciu | Intelligent sensing | Excellence in Research

Mr. Gabriel Danciu | Intelligent sensing | Excellence in Research

Lecturer at Transilvania University, Romania

Danciu Gabriel is a prominent researcher and educator from Romania, specializing in electrical engineering and computer science. Currently serving as a Şef lucrări at the University of Transilvania in Brașov, he combines his academic role with practical experience as an engineer and manager at Siemens. With a robust publication record exceeding 50 papers, Gabriel is recognized for his contributions to artificial intelligence, image processing, and software architecture. He is an active member of the IEEE and has presented at numerous international conferences. His commitment to education is reflected in his mentoring roles and project coordination, making him a vital part of the academic community. Gabriel’s expertise in developing algorithms for RGB-D cameras and his innovative research approaches have earned him respect in the field. He aims to bridge theoretical knowledge with practical applications, enhancing technological advancements and shaping the next generation of engineers.

Profile:

Google Scholar Profile

Strengths for the Award:

  1. Extensive Experience: Gabriel has over 15 years of experience in academia and industry, demonstrating a strong commitment to both education and research.
  2. Publication Record: With over 50 published works, he shows a robust contribution to fields such as AI, image processing, and software architectures, indicating high productivity and impact in his research area.
  3. Diverse Skill Set: His competencies in various programming languages (C++, C#, Python) and expertise in software architecture showcase his technical proficiency, which is critical for modern research.
  4. Leadership Roles: As a Şef lucrări (Head of Department) and an engineer at Siemens, he has proven leadership capabilities, indicating his ability to manage projects and mentor others effectively.
  5. International Engagement: Participation in over 5 European projects and presentations at numerous conferences reflects his active engagement with the global research community.
  6. Research Innovation: His focus on cutting-edge topics like AI and image processing highlights his relevance and adaptability to current technological trends.

Areas for Improvement:

  1. Language Proficiency: While he is proficient in English, improving his German skills could enhance his collaboration opportunities in Europe, particularly in multilingual environments.
  2. Broader Collaboration: Expanding his research network beyond existing affiliations could lead to more interdisciplinary projects and greater innovation.
  3. Public Engagement: Increasing visibility through popular science publications or community outreach could enhance his impact beyond the academic sphere.
  4. Mentoring: Actively seeking to mentor younger researchers or students could foster new talent in the field and enhance his leadership profile.

Education:

Danciu Gabriel pursued his academic journey at the University of Transilvania in Brașov, where he obtained his Bachelor’s degree in Automatică și Informatică Industrială in 2004. He continued his studies at the same institution, completing a Master’s degree in Electrical Engineering and Telecommunications in 2006. Gabriel then earned his Ph.D. in 2014, focusing on developing algorithms for image processing using RGB-D cameras. His educational background laid a solid foundation for his future roles in academia and industry. As an Asistent universitar from 2007 to 2022, he dedicated himself to teaching and research, culminating in his current position as Șef lucrări, where he engages in educational leadership, research activities, and administrative duties. Gabriel’s academic achievements are complemented by ongoing professional development, ensuring that he stays at the forefront of technological advancements and educational methodologies in his field.

Experience:

Danciu Gabriel boasts extensive professional experience spanning over 15 years in both academia and industry. He began his career as a Software Engineer at Dynamic Ventures from 2005 to 2017, where he focused on research, mentorship, and software development. In 2018, he transitioned to Siemens as an Engineer, Researcher, and Manager, where he continues to work on innovative research projects while mentoring emerging talent. Concurrently, he has held various academic positions at the University of Transilvania, serving as an Asistent universitar for 15 years before advancing to Şef lucrări in 2022. His dual role allows him to integrate theoretical knowledge with practical applications, contributing to the growth of his students and the advancement of technology. Gabriel’s experience is characterized by a commitment to education, research innovation, and leadership, positioning him as a key figure in the fields of electrical engineering and computer science.

Research Focus:

Danciu Gabriel’s research primarily revolves around artificial intelligence, image processing, and software architecture, with a specific emphasis on RGB-D cameras. His work in developing innovative algorithms for depth image analysis has significantly contributed to advancements in computer vision and signal processing. Gabriel has published over 50 papers in renowned journals and conferences, exploring various topics, including noise pollution monitoring, functional verification in digital designs, and object tracking methods. He actively participates in European projects, collaborating with interdisciplinary teams to address real-world challenges through technology. Gabriel is passionate about integrating theoretical concepts with practical applications, aiming to improve the efficiency and accuracy of image processing techniques. His ongoing research endeavors focus on enhancing machine learning models and exploring new avenues in automated systems, positioning him at the cutting edge of technological innovation in the fields of engineering and computer science.

Publication Top Notes:

  • Shadow removal in depth images morphology-based for Kinect cameras 🌌
  • Objective erythema assessment of Psoriasis lesions for PASI evaluation 🌿
  • A novel approach for face expressions recognition 😊
  • Improved contours for ToF cameras based on vicinity logic operations 🖼️
  • Cost-efficient approaches for fulfillment of functional coverage during verification of digital designs 💻
  • Coverage fulfillment automation in hardware functional verification using genetic algorithms 🔍
  • Extended control-value emotional agent based on fuzzy logic approach 🤖
  • Scale and rotation-invariant feature extraction for color images of iris melanoma 🌈
  • Level up in verification: Learning from functional snapshots 📊
  • Noise pollution monitoring using mobile crowd sensing and SAP analytics 📱
  • Debugging FPGA projects using artificial intelligence 🧩
  • Debug FPGA projects using machine learning 📈
  • Efficient analysis of digital systems’ supplied data ⚙️
  • Method proposal for blob separation in segmented images 🔍
  • Solutions for Roaming and Interoperability Problems Between LTE and 2G or 3G Networks 📶
  • Methods of Object Tracking 🕵️‍♂️
  • Adaptive Scaling for Image Sensors in Embedded Security Applications 🔒
  • A method proposal of scene recognition for RGB-D cameras 🌍
  • Genetic algorithm for depth images in RGB-D cameras 🔧
  • Hierarchical contours based on depth images 🗺️

Conclusion:

Gabriel Danciu demonstrates a strong profile as a candidate for the Best Researcher Award, with a solid foundation in research, a wealth of experience, and a proven track record of publications and collaborations. By addressing the suggested areas for improvement, particularly in broader engagement and mentorship, he could further strengthen his candidacy and impact in the research community.