Chongyuan Wang | Deep learning | Best Researcher Award

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Dr. Chongyuan Wang | Deep learning | Best Researcher Award

Dr. Chongyuan Wang, a Ph.D. researcher at Hohai University, specializes in artificial intelligence šŸ¤– and neural computation šŸ§ . He completed his B.S. at Jiangsu University šŸ‡ØšŸ‡³ and M.S. in Energy and Power from Warwick University šŸ‡¬šŸ‡§. His research journey is centered around biologically inspired learning algorithms, with notable contributions to dendritic neuron modeling and evolutionary optimization. Through innovative algorithms like Reinforced Dynamic-grouping Differential Evolution (RDE), Dr. Wang advances the understanding of synaptic plasticity in AI systems. His patent filings and international publications reflect a strong commitment to academic innovation and impact šŸŒ.

Profile

Education šŸŽ“

šŸŽ“ B.S. in Engineering ā€“ Jiangsu University, China šŸ‡ØšŸ‡³
šŸŽ“ M.S. in Energy and Power ā€“ University of Warwick, UK šŸ‡¬šŸ‡§ (2018)
šŸŽ“ Ph.D. Candidate ā€“ Hohai University, majoring in Artificial Intelligence šŸ¤–
Dr. Wang’s educational path bridges engineering and intelligent systems. His strong technical foundation and global exposure foster advanced thinking in machine learning and neuroscience. His current doctoral research integrates deep learning, dendritic neuron models, and biologically plausible architectures for improved learning accuracy and model efficiency. šŸ“˜šŸ§ 

Experience šŸ‘Øā€šŸ«

Dr. Wang is currently pursuing his Ph.D. at Hohai University, where he investigates dendritic learning algorithms and synaptic modeling. šŸ§¬ He proposed the RDE algorithm, enhancing dynamic learning in artificial neurons. His hands-on experience includes research design, algorithm optimization, patent writing, and international publication. He has contributed to projects such as “Toward Next-Generation Biologically Plausible Single Neuron Modeling” and “RADE for Lightweight Dendritic Learning.” šŸ“Š His work balances theoretical depth and applied research, particularly in neural computation, classification systems, and resource-efficient AI. šŸ”¬šŸ’”

Awards & Recognitions šŸ…

šŸ… Patent Holder (CN202410790312.0, CN202410646306.8, CN201510661212.9)
šŸ“„ Published in SCI-indexed journal Mathematics (MDPI)
šŸŒ Recognized on ORCID (0009-0002-6844-1446)
šŸ§  Nominee for Best Researcher Award 2025
His inventive research has earned him national patents and global visibility. His SCI publications in computational modeling reflect both novelty and academic rigor. His continued innovation in biologically inspired AI learning systems has established his position as an emerging researcher in intelligent systems. šŸš€šŸ“˜

Research Interests šŸ”¬

Dr. Wangā€™s research fuses deep learning šŸ¤– and dendritic modeling šŸ§  to create biologically plausible AI. He developed the RDE algorithm to mimic synaptic plasticity, improving convergence and adaptability in neural networks. His research areas include evolutionary optimization, adaptive grouping, resource-efficient models, and dendritic learning. He explores how artificial neurons can reflect real-brain behavior, leading to faster, more accurate AI systems. Current projects like RADE aim to make AI lightweight and biologically relevant. šŸŒ±šŸ“Š His vision is to bridge the gap between neuroscience and AI through interpretable, high-performance algorithms. šŸ§ šŸ’”

Publications

  • Toward Next-Generation Biologically Plausible Single Neuron Modeling: An Evolutionary Dendritic Neuron Model

    Mathematics
    2025-04-29 |Ā Journal article
    DOI:Ā 10.3390/math13091465
    CONTRIBUTORS:Ā Chongyuan Wang;Ā Huiyi Liu

Alvaro Garcia | Computer vision | Best Researcher Award

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Dr. Alvaro Garcia | Computer vision | Best Researcher Award

Ɓlvaro GarcĆ­a MartĆ­n es Profesor Titular en la Universidad AutĆ³noma de Madrid, especializado en visiĆ³n por computadora y anĆ”lisis de video. šŸŽ“ Obtuvo su tĆ­tulo de Ingeniero de TelecomunicaciĆ³n en 2007, su MĆ”ster en IngenierĆ­a InformĆ”tica y Telecomunicaciones en 2009 y su Doctorado en 2013, todos en la Universidad AutĆ³noma de Madrid. šŸ« Ha trabajado en detecciĆ³n de personas, seguimiento de objetos y reconocimiento de eventos, con mĆ”s de 22 artĆ­culos en revistas indexadas y 28 en congresos. šŸ“ Ha realizado estancias en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. šŸŒ Su investigaciĆ³n ha contribuido al desarrollo de sistemas de videovigilancia inteligentes, anĆ”lisis de secuencias de video y procesamiento de seƱales multimedia. šŸ“¹ Ha sido reconocido con prestigiosos premios y ha participado en mĆŗltiples proyectos europeos de innovaciĆ³n tecnolĆ³gica. šŸš€

Profile

Education šŸŽ“

šŸŽ“ Ingeniero de TelecomunicaciĆ³n por la Universidad AutĆ³noma de Madrid (2007). šŸŽ“ MĆ”ster en IngenierĆ­a InformĆ”tica y Telecomunicaciones con especializaciĆ³n en Tratamiento de SeƱales Multimedia en la Universidad AutĆ³noma de Madrid (2009). šŸŽ“ Doctor en IngenierĆ­a InformĆ”tica y TelecomunicaciĆ³n por la Universidad AutĆ³noma de Madrid (2013). Su formaciĆ³n ha sido complementada con estancias en reconocidas universidades internacionales, incluyendo Carnegie Mellon University (EE.UU.), Queen Mary University (Reino Unido) y la Technical University of Berlin (Alemania). šŸŒ Durante su doctorado, recibiĆ³ la beca FPI-UAM para la realizaciĆ³n de su investigaciĆ³n. Su sĆ³lida formaciĆ³n acadĆ©mica le ha permitido contribuir significativamente al campo del anĆ”lisis de video y visiĆ³n por computadora, consolidĆ”ndose como un experto en la detecciĆ³n, seguimiento y reconocimiento de eventos en secuencias de video. šŸ“¹

Experience šŸ‘Øā€šŸ«

šŸ”¬ Se uniĆ³ al grupo VPU-Lab en la Universidad AutĆ³noma de Madrid en 2007. šŸ“” De 2008 a 2012, fue becario de investigaciĆ³n (FPI-UAM). šŸŽ“ Entre 2012 y 2014, trabajĆ³ como Profesor Ayudante. šŸ‘Øā€šŸ« De 2014 a 2019, fue Profesor Ayudante Doctor. šŸ“š De 2019 a 2023, ocupĆ³ el cargo de Profesor Contratado Doctor. šŸ›ļø Desde septiembre de 2023, es Profesor Titular en la Universidad AutĆ³noma de Madrid. šŸ† Ha participado en mĆŗltiples proyectos europeos sobre videovigilancia, transmisiĆ³n de contenido multimedia y reconocimiento de eventos, incluyendo PROMULTIDIS, ATI@SHIVA, EVENTVIDEO y MobiNetVideo. šŸš€ Ha realizado estancias de investigaciĆ³n en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. šŸŒ Su experiencia docente abarca asignaturas en IngenierĆ­a de Telecomunicaciones, IngenierĆ­a InformĆ”tica e IngenierĆ­a BiomĆ©dica.

Research Interests šŸ”¬

šŸŽÆ Su investigaciĆ³n se centra en la visiĆ³n por computadora, el anĆ”lisis de secuencias de video y la inteligencia artificial aplicada a entornos de videovigilancia. šŸ“¹ Especialista en detecciĆ³n de personas, seguimiento de objetos y reconocimiento de eventos en video. šŸ§  Desarrolla algoritmos de aprendizaje profundo y visiĆ³n artificial para mejorar la seguridad y automatizaciĆ³n en ciudades inteligentes. šŸ™ļø Ha trabajado en proyectos sobre videovigilancia, transmisiĆ³n multimedia y detecciĆ³n de anomalĆ­as en video. šŸ”¬ Su investigaciĆ³n incluye procesamiento de imĆ”genes, anĆ”lisis semĆ”ntico y redes neuronales profundas. šŸš€ Participa activamente en proyectos internacionales y colabora con universidades como Carnegie Mellon, Queen Mary y TU Berlin. šŸŒ Ha publicado en IEEE Transactions on Intelligent Transportation Systems, Sensors y Pattern Recognition, consolidĆ”ndose como un referente en el campo de la visiĆ³n por computadora. šŸ“œ

Awards & Recognitions šŸ…

šŸ„‡ Medalla “Juan LĆ³pez de PeƱalver” 2017, otorgada por la Real Academia de IngenierĆ­a. šŸ“œ Reconocimiento por su contribuciĆ³n a la ingenierĆ­a espaƱola en el campo de la visiĆ³n por computadora y anĆ”lisis de video. šŸ›ļø Ha recibido financiaciĆ³n para mĆŗltiples proyectos de investigaciĆ³n europeos y nacionales. šŸ”¬ Ha participado en iniciativas de innovaciĆ³n en videovigilancia y anĆ”lisis de video para seguridad. šŸš€ Sus contribuciones han sido publicadas en las principales conferencias y revistas cientĆ­ficas del Ć”rea. šŸ“š Su trabajo ha sido citado mĆ”s de 4500 veces y cuenta con un Ć­ndice h de 16 en Google Scholar. šŸ“Š

PublicationsĀ 

1. Rafael Martƭn-Nieto, Ɓlvaro Garcƭa-Martƭn, Alexander G. Hauptmann, and Jose. M.
MartĆ­nez: ā€œAutomatic vacant parking places management system using multicamera
vehicle detectionā€. IEEE Transactions on Intelligent Transportation Systems, Volume 20,
Issue 3, pp. 1069-1080, ISSN 1524-9050, March 2019.

2. Rafael Martƭn-Nieto, Ɓlvaro Garcƭa-Martƭn, Jose. M. Martƭnez, and Juan C. SanMiguel:
ā€œEnhancing multi-camera people detection by online automatic parametrization using
detection transfer and self-correlation maximizationā€. Sensors, Volume 18, Issue 12, ISSN
1424-8220, December 2018.

3. Ɓlvaro GarcĆ­a-MartĆ­n, Juan C. SanMiguel and Jose. M. MartĆ­nez: ā€œCoarse-to-fine adaptive
people detection for video sequences by maximizing mutual informationā€. Sensors,
Volume 19, Issue 4, ISSN 1424-8220, January 2019.

4. Alejandro LĆ³pez-Cifuentes, Marcos Escudero-ViƱolo, JesĆŗs BescĆ³s and Ɓlvaro GarcĆ­aMartĆ­n: ā€œSemantic-Aware Scene Recognitionā€. Pattern Recognition. Accepted February
2020.

5. Paula Moral, Ɓlvaro Garcƭa-Martƭn, Marcos Escudero ViƱolo, Jose M. Martinez, Jesus
BescĆ³s, Jesus PeƱuela, Juan Carlos Martinez, Gonzalo Alvis: ā€œTowards automatic waste
containers management in cities via computer vision: containers localization and geopositioning in city mapsā€. Waste Management, June 2022.

6. Javier Montalvo, Ɓlvaro GarcĆ­a-MartĆ­n, Jesus BescĆ³s: ā€œExploiting Semantic Segmentation
to Boost Reinforcement Learning in Video Game Environmentsā€. Multimedia Tools and
Applications. September 2022.

7. Paula Moral, Ɓlvaro GarcĆ­a-MartĆ­n, Jose M. Martinez, Jesus BescĆ³s: ā€œEnhancing Vehicle
Re-Identification Via Synthetic Training Datasets and Re-ranking Based on Video-Clips
Informationā€. Multimedia Tools and Applications. February 2023.

8. Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-ViƱolo and Alvaro GarciaMartin: ā€œOn exploring weakly supervised domain adaptation strategies for semantic
segmentation using synthetic dataā€. Multimedia Tools and Applications. February 2023.

9. Juan Ignacio Bravo PĆ©rez-Villar, Ɓlvaro GarcĆ­a-MartĆ­n, JesĆŗs BescĆ³s, Marcos EscuderoViƱolo: ā€œSpacecraft Pose Estimation: Robust 2D and 3D-Structural Losses and
Unsupervised Domain Adaptation by Inter-Model Consensusā€. IEEE Transactions on
Aerospace and Electronic Systems. August 2023.

10. Javier Montalvo, Ɓlvaro GarcĆ­a-MartĆ­n, JosĆ© M. Martinez. “An Image-Processing Toolkit
for Remote Photoplethysmography”, Multimedia Tools and Applications. July 2024.

11. Juan Ignacio Bravo PĆ©rez-Villar, Ɓlvaro GarcĆ­a-MartĆ­n, JesĆŗs BescĆ³s, Juan C. SanMiguel:
ā€œTest-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on
Predicted-View Synthesisā€. IEEE Transactions on Aerospace and Electronic Systems.
May 2024.

12. Kirill Sirotkin, Marcos Escudero-ViƱolo, Pablo Carballeira, Ɓlvaro Garcƭa-Martƭn:
ā€œImproved Transferability of Self-Supervised Learning Models Through Batch
Normalization Finetuningā€. Applied Intelligence. Aug 2024.

13. Javier GalƔn, Miguel GonzƔlez, Paula Moral, Ɓlvaro Garcƭa-Martƭn, Jose M. Martinez:
ā€œTransforming Urban Waste Collection Inventory: AI-Based Container Classification and
Re-Identificationā€. Waste Management, Feb 2025.

Mudassar Raza | Machine Learning | Best Researcher Award

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Prof. Mudassar Raza | Machine Learning | Best Researcher Award

Prof. Dr. Mudassar Raza is a leading AI researcher and academician, serving as a Professor at Namal University, Mianwali, Pakistan. He is a Senior IEEE Member, Chair Publications of IEEE Islamabad Section, and an Academic Editor for PLOS ONE. With 20+ years of teaching and research experience, he has worked at HITEC University Taxila and COMSATS University Islamabad. His research spans AI, deep learning, image processing, and cybersecurity. He has published 135+ research papers with a cumulative impact factor of 215+, 6066+ citations, an H-index of 44, and an I-10 index of 93. He was listed in Elsevierā€™s Worldā€™s Top 2% Scientists (2023) and ranked #11 in Computer Science in Pakistan. Dr. Raza has supervised 3 PhDs, co-supervising 6 more, and mentored 100+ undergraduate R&D projects. He actively contributes to academia, industry collaborations, and curriculum development while serving as a reviewer for prestigious journals. šŸŒšŸ“–

Profile

Education šŸŽ“

  • Ph.D. in Control Science & Engineering (2014-2017) ā€“ University of Science & Technology of China (USTC), China šŸ‡ØšŸ‡³
    • Specialization: Pattern Recognition & Intelligent Systems
  • MS (Computer Science) (2009-2010) ā€“ Iqra University, Islamabad, Pakistan šŸ‡µšŸ‡°
    • CGPA: 3.64 | Specialization: Image Processing
  • MCS (Master of Computer Science) (2004-2006) ā€“ COMSATS Institute of Information Technology, Pakistan
    • CGPA: 3.24 | 80% Marks
  • BCS (Bachelor in Computer Science) (1999-2003) ā€“ Punjab University, Lahore, Pakistan
    • CGPA: 3.28 | 64.25% Marks
  • Higher Secondary (Pre-Engineering) ā€“ Islamabad College for Boys
  • Matriculation (Science) ā€“ Islamabad College for Boys
    Dr. Razaā€™s academic journey is marked by top-tier universities and a strong focus on AI, pattern recognition, and cybersecurity. šŸŽ“šŸ“š

Experience šŸ‘Øā€šŸ«

  • Professor (2024-Present) ā€“ Namal University, Mianwali
    • Teaching AI, Cybersecurity, and Research Supervision
  • Associate Professor/Head AI & Cybersecurity Program (2023-2024) ā€“ HITEC University, Taxila
    • Led AI & Cybersecurity programs, supervised PhDs, and organized industry-academic collaborations
  • Associate Professor (2023) ā€“ COMSATS University, Islamabad
  • Assistant Professor (2012-2023) ā€“ COMSATS University, Islamabad
  • Lecturer (2008-2012) ā€“ COMSATS University, Islamabad
  • Research Associate (2006-2008) ā€“ COMSATS University, Islamabad
    Dr. Raza has 20+ years of experience in academia, R&D, and industry collaborations, contributing significantly to AI, deep learning, and cybersecurity. šŸ«šŸ“Š

Research Interests šŸ”¬

Prof. Dr. Mudassar Razaā€™s research revolves around Artificial Intelligence, Deep Learning, Computer Vision, Image Processing, Cybersecurity, and Parallel Programming. His work includes pattern recognition, intelligent systems, visual robotics, and AI-driven cybersecurity solutions. With 135+ international publications, he has significantly contributed to AIā€™s real-world applications. His research impact includes 6066+ citations, an H-index of 44, and an I-10 index of 93. He leads multiple AI research groups, supervises PhD/MS students, and actively collaborates with industry and academia. His work is frequently cited, placing him among the top AI researchers globally. As an IEEE Senior Member and a PLOS ONE Academic Editor, he is a key figure in AI-driven innovations and technology advancements. šŸ§ šŸ“Š

  • National Youth Award 2008 by the Prime Minister of Pakistan for contributions to Computer Science šŸŽ–ļø
  • Listed in Worldā€™s Top 2% Scientists (2023) by Elsevier šŸŒ
  • Ranked #11 in Computer Science in Pakistan by AD Scientific Index šŸ“Š
  • Senior IEEE Member (ID: 91289691) šŸ”¬
  • HEC Approved PhD Supervisor šŸŽ“
  • Best Research Productivity Awardee at COMSATS University multiple times šŸ†
  • Recognized by ResearchGate with a Research Interest Score higher than 97% of members šŸ“ˆ
  • Reviewer & Editor for prestigious journals including PLOS ONE šŸ“
    Dr. Raza has received numerous accolades for his contributions to AI, research excellence, and academia. šŸŒŸ

Publications šŸ“š

Xin SU | Multi-temporal remote sensing information extraction | Best Researcher Award

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Prof Dr. Xin SU | Multi-temporal remote sensing information extraction | Best Researcher Award

Xin Su, PhD, is an Associate Professor at the School of Artificial Intelligence, Wuhan University. He supervises both masterā€™s and PhD students. He earned his doctorate in Signal and Image Processing from Telecom ParisTech in 2015. He then worked as a postdoctoral researcher at INRIA, France, from 2015 to 2018. His research focuses on intelligent analysis of time-series images, spatiotemporal target recognition, and large-scale remote sensing models. He has led and participated in multiple national research projects, publishing extensively in top-tier journals such as IEEE TIP, IEEE TGRS, ISPRS, and JAG. šŸ“ššŸŽ“

Profile

Education šŸŽ“

  • PhD (2015): Telecom ParisTech, France ā€“ Signal and Image Processing šŸŽ“
  • Masterā€™s Studies (2008-2011, uncompleted): Wuhan University ā€“ Signal and Information Processing šŸ«
  • Bachelorā€™s (2004-2008): Wuhan University ā€“ Electronic Science and Technology (Engineering) šŸŽ“

Experience šŸ‘Øā€šŸ«

  • 2015-2018: Postdoctoral Researcher, INRIA, France šŸ‡«šŸ‡·
  • 2015: Postdoctoral Researcher, Telecom ParisTech, France šŸŽ“

Research Interests šŸ”¬

Xin Su specializes in intelligent analysis of time-series remote sensing images, spatiotemporal object recognition, and large-scale AI models for remote sensing. His work spans geospatial applications, UAV-based surveillance, and hyperspectral data processing. He actively contributes to developing advanced AI techniques for satellite video analysis and infrastructure monitoring. šŸš€šŸŒ

Awards & Recognitions šŸ…

Xin Su has been recognized for his contributions to remote sensing and AI, receiving multiple national research grants and awards for excellence in scientific research and innovation. He has secured funding from National Natural Science Foundation projects and defense-related initiatives. His research has been featured in top IEEE and ISPRS journals, reinforcing his position as a leading researcher in the field. šŸŒŸšŸ…

Publications šŸ“š

Vikas Palekar | Machine Leaning | Best Researcher Award

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Mr. Vikas Palekar | Machine Leaning | Best Researcher Award

 

Profile

Education

He is currently pursuing a Ph.D. in Computer Science and Engineering at Vellore Institute of Technology, Bhopal, Madhya Pradesh, since December 2018. His research focuses on developing an Adaptive Optimized Residual Convolutional Image Annotation Model with a Bionic Feature Selection Strategy. He holds a Master of Engineering (M.E.) in Information Technology from Prof. Ram Meghe College of Engineering Technology and Research, Badnera (SGBAU Amravati), which he completed in December 2012 with an impressive 88.00%, securing the first merit position in the university for the summer 2012 examination. Prior to that, he earned a Bachelor of Engineering (B.E.) in Computer Science and Engineering from Shri Guru Gobind Singhji Institute of Engineering Technology and Research, Nanded (SRTMNU, Nanded), in June 2007, achieving a commendable 74.40%.

Work experience

He is currently working as an Assistant Professor in the Department of Computer Engineering at Bajaj Institute of Technology, Wardha, since July 31, 2023. In addition to his teaching responsibilities, he serves as the Academic Coordinator of the department and has worked as a Senior Supervisor for the DBATY Winter-23 Exam at Government College of Engineering, Yavatmal.

Previously, he worked as an Assistant Professor (UGC Approved, RTMNU, Nagpur) in the Department of Computer Science and Engineering at Datta Meghe Institute of Engineering, Technology & Research, Wardha, from June 14, 2011, to June 30, 2023. During this tenure, he held the position of Head of the Department from April 21, 2016, to June 30, 2023. He taught various subjects, including Distributed Operating Systems, TCP/IP, System Programming, Data Warehousing and Mining, Artificial Intelligence, and Computer Architecture and Organization. Additionally, he contributed to university examinations as the Chief Supervisor in the Winter-2015 Examination and a committee member for the Summer-2013, Summer-2015, and Summer-2018 Examinations. He also played a key role in institutional development as a member of the Admission Committee, NBA & NAAC core committees at the department level, and as the convener of the National Level Technical Symposium “POCKET 16” organized by the CSE Department on March 16, 2016.

Earlier in his career, he served as an Assistant Professor in the Department of Computer Engineering at Bapurao Deshmukh College of Engineering, Wardha, from November 26, 2008, to April 30, 2011. He taught subjects such as Unix and Shell Programming, Object-Oriented Programming, and Operating Systems while also serving as a Department Exam Committee Member.

Achievement

He was the first university topper (merit) in M.Tech (Information Technology) and received the Best Paper Award at the 2021 International Conference on Computational Performance Evaluation (ComPE), organized by the Department of Biomedical Engineering, North Eastern Hill University (NEHU), Shillong, Meghalaya, India, from December 1st to 3rd, 2023. He has actively participated in various conferences, including presenting the paper “Label Dependency Classifier using Multi-Feature Graph Convolution Networks for Automatic Image Annotation” at ComPE 2021 in Shillong, India. He also presented his research on “Visual-Based Page Segmentation for Deep Web Data Extraction” at the International Conference on Soft Computing for Problem Solving (SocProS 2011) held from December 20-22, 2011. Additionally, he contributed to the Computer Science & Engineering Department at Sardar Vallabhbhai National Institute of Technology, Surat, by presenting “A Critical Analysis of Learning Approaches for Image Annotation Based on Semantic Correlation” from December 13-15, 2022. His work on “A Survey on Assisting Document Annotation” was featured at the 19th International Conference on Hybrid Intelligent Systems (HIS) at VIT Bhopal University, India, from December 10-12, 2022. Furthermore, he co-authored a study titled “Review on Improving Lifetime of Network Using Energy and Density Control Cluster Algorithm,” which was presented at the 2018 IEEE International Students’ Conference on Electrical, Electronics, and Computer Science (SCEECS) in Bhopal, India.

 

Publication