Yangyang Ju | Smart gas sensor | Young Scientist Award

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Ms. Yangyang Ju | Smart gas sensor | Young Scientist Award

Yangyang Ju is an Assistant Professor at the Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology. She earned her Ph.D. in Physics and Mathematics from Tomsk Polytechnic University, Russia, in 2019, following her graduation from Jilin University in 2013. Her research focuses on nanomaterials, optoelectronic and gas-sensitive materials, smart gas sensors, and the stability of halide perovskite materials. She has led multiple research projects, including those funded by the National Natural Science Foundation of China and the Beijing Foreign High-level Young Talent Program. With 14 published articles in indexed journals and two patented oxygen sensors, her contributions to material science are significant. She collaborates with global research teams, including ITMO in Russia, and serves as a special issue editor for Materials. She is also a member of the Chinese Institute of Electronics.

Profile

Education 🎓

Yangyang Ju completed her undergraduate studies at Jilin University in 2013. She pursued her Ph.D. in Physics and Mathematics at Tomsk Polytechnic University, Russia, completing it in 2019. Her doctoral research focused on the development and stability of halide perovskite materials for optoelectronic applications. She later conducted postdoctoral research at the Beijing Institute of Technology, where she expanded her expertise in gas-sensitive nanomaterials and smart sensors. Through various academic and industrial collaborations, she has gained in-depth knowledge of material science, sensor technology, and advanced nanomaterials. Her education laid the foundation for her innovative work in trace gas sensors and perovskite-based devices. With a strong interdisciplinary background, she integrates physics, chemistry, and engineering principles to develop cutting-edge materials for environmental and industrial applications.

Experience 👨‍🏫

Yangyang Ju is currently an Assistant Professor at the Beijing Institute of Technology’s Advanced Research Institute of Multidisciplinary Science. She has led multiple national and international research projects, including grants from the National Natural Science Foundation of China and the Beijing Foreign High-level Young Talent Program. As a Principal Investigator, she has successfully managed projects focusing on perovskite materials and gas sensors. Previously, she collaborated with ITMO University in Russia, where she worked on phase purity control in quasi-2D PeLEDs, leading to multiple indexed publications. Additionally, she has held key roles in technology development projects with Zhijing Technology (Beijing) Co., Ltd. Her work has led to two patents on oxygen detection devices. She also serves as a special issue editor for Materials and is a professional member of the Chinese Institute of Electronics.

Research Interests 🔬

Yangyang Ju specializes in trace gas sensors, metal halide perovskites, gas-sensitive materials, and nanomaterials. Her research explores the stability of halide perovskites under different environmental conditions, focusing on their applications in optoelectronics and gas sensing. She has contributed significantly to understanding the impact of oxygen concentration on the fluorescence of 2D tin-based perovskites, leading to the development of fiber-optic trace oxygen sensors with high sensitivityhttps://cognitivescientist.org/?p=12953&preview=true. Her work has been published in Matter, Advanced Functional Materials, and Advanced Science. She has also collaborated with ITMO University in Russia to optimize phase purity control in quasi-2D PeLEDs. Her studies on perovskite-oxygen interactions have provided critical insights into material stability and sensor applications. Through national and international collaborations, she continues to advance research on smart gas sensors and high-performance nanomaterials for industrial and environmental monitoring.

Awards & Recognitions 🏅

Yangyang Ju has received several prestigious awards, including funding from the Beijing Foreign High-level Young Talent Program (2024) and the Young Faculty Startup Program of Beijing Institute of Technology. She was also awarded grants by the National Natural Science Foundation of China for her pioneering research in gas-sensitive materials and nanotechnology. Her work in material stability and sensor development has been recognized through national and international collaborations, including a cooperative exchange project with the Fundamental Research Foundation of Belarus. She has received recognition for her outstanding contributions to perovskite research and gas sensor development, leading to multiple high-impact journal publications. Her patents on oxygen detection devices further demonstrate her innovation in applied material sciences.

Publications 

  • Catalytic Sensor-Based Software-Algorithmic System for the Detection and Quantification of Combustible Gases in Complex Mixtures

    Sensors and Actuators A: Physical
    2025-03 | Journal article
    DOI: 10.1016/j.sna.2025.116458
    CONTRIBUTORS: Tatiana Osipova; Alexander Baranov; Haowen Zhang; Ivan Ivanov; Yangyang Ju

  • Response of Catalytic Hydrogen Sensors at Low and Negative Ambient Temperatures

    IEEE Sensors Letters
    2023-12 | Journal article
    DOI: 10.1109/LSENS.2023.3331376
    CONTRIBUTORS: Vladislav Talipov; Alexander Baranov; Ivan Ivanov; Yangyang Ju

  • Color‐Stable Two‐Dimensional Tin‐Based Perovskite Light‐Emitting Diodes: Passivation Effects of Diphenylphosphine Oxide Derivatives

    Advanced Functional Materials
    2023-07 | Journal article
    DOI: 10.1002/adfm.202301304
    CONTRIBUTORS: Chenhui Wang; Siqi Cui; Yangyang Ju; Yu Chen; Shuai Chang; Haizheng Zhong

  • Fast-Response Oxygen Optical Fiber Sensor based on PEA<sub>2</sub>SnI<sub>4</sub> Perovskite with Extremely Low Limit of Detection

    Advanced Science
    2022 | Journal article
    DOI: 10.1002/advs.202104708

 

Yuanming Zhang | Intelligent data processing and analysis | Best Researcher Award

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Dr. Yuanming Zhang | Intelligent data processing and analysis | Best Researcher Award

Yuanming Zhang is an Associate Professor at the College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China. He earned his Ph.D. in Information Science from Utsunomiya University, Japan, in 2010. His research focuses on data processing, graph neural networks, knowledge graphs, prognostics, health management, and condition monitoring. With expertise in deep learning and artificial intelligence, he has contributed significantly to neural network advancements. His work integrates cutting-edge technologies for intelligent data analysis and predictive maintenance. 📊🧠🔍

Profile

Education 🎓

Yuanming Zhang obtained his Ph.D. in Information Science from Utsunomiya University, Japan, in 2010. His academic journey emphasized computational intelligence, machine learning, and advanced data analytics. He developed expertise in deep learning models, including convolutional and graph neural networks. His education laid a strong foundation for interdisciplinary research, integrating artificial intelligence with real-world applications. 📚🧑‍🎓📈

Experience 👨‍🏫

Yuanming Zhang has been an Associate Professor at Zhejiang University of Technology since completing his Ph.D. in 2010. His professional journey spans over a decade in academia, focusing on AI, neural networks, and knowledge graphs. He has supervised research projects, collaborated on industry applications, and contributed to advancements in predictive analytics and condition monitoring. His expertise extends to teaching, mentoring, and interdisciplinary AI applications. 🏫🤖📡

Research Interests 🔬

Yuanming Zhang specializes in deep learning, attention mechanisms, graph neural networks, and AI-driven predictive analytics. His research explores neural architectures for data processing, knowledge representation, and condition monitoring. His expertise spans convolutional networks, LSTMs, GRUs, and deep belief networks. His work contributes to advancements in AI-driven diagnostics, intelligent systems, and real-time health monitoring applications. 🧠📊🖥️

Awards & Recognitions 🏅

Yuanming Zhang has received recognition for his contributions to AI, machine learning, and data analytics. His work in deep learning and knowledge graphs has earned him accolades from research institutions and conferences. His papers in neural networks and predictive maintenance have been highly cited, solidifying his impact in the field. His research excellence has been acknowledged through grants and academic distinctions. 🎖️📜🔬

Publications 

 

Elsa Pittaras | Neuroscience | Women Researcher Award

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Dr. Elsa Pittaras | Neuroscience | Women Researcher Award

Elsa Pittaras is a Basic Life Research Scientist at Stanford University, specializing in neuroscience, cognition, and sleep research. With expertise in molecular biology, neuroanatomy, pharmacology, and behavior, she has extensively studied decision-making processes in mice. Her research has contributed significantly to understanding sleep deprivation’s effects on cognition and memory in Down Syndrome and Alzheimer’s disease models. She has published multiple papers as both first and last author, showcasing her leadership in neuroscience. Elsa’s goal is to advance research on mood disorders, cognition, and neurochemistry, aspiring to become an independent researcher in the U.S. 🇺🇸🔬🧠

Profile

Education 🎓

Elsa Pittaras earned a B.S. in Physiology from the University of Caen (2010), an M.S. in Neuroscience from the University of Paris Sud and ENS Cachan (2012), and a Ph.D. in Neuroscience from Neuro-PSI and the Biomedical Research Unit of the French Army (2016). Her multidisciplinary foundation in biology, physics, chemistry, and mathematics from Châtelet, Douai (2009) laid the groundwork for her neuroscience expertise. Throughout her education, she focused on decision-making, sleep deprivation, and neurochemical mechanisms in cognition. 🧠📚🎓

Experience 👨‍🏫

Elsa Pittaras has been a Basic Life Research Scientist at Stanford University since 2022, focusing on cognitive enhancement in Down Syndrome and Alzheimer’s disease models. She was a Postdoctoral Fellow at Stanford (2017-2022), investigating sleep and circadian rhythms’ effects on memory. Previously, she conducted research at the Biomedical Research Unit of the French Army (2016-2017) and completed her Ph.D. at Neuro-PSI. Her career includes internships in neuroscience at Neuro-PSI (2011-2012) and clinical observations at CHU Caen (2010). 🏛️🧬🧪

Research Interests 🔬

Elsa’s research explores decision-making, memory, and sleep in neurodevelopmental disorders. She pioneered the Mouse Gambling Task, revealing individual decision-making strategies. Her Ph.D. identified neurochemical markers of decision-making behaviors and the effects of sleep deprivation. At Stanford, she investigates sleep’s impact on cognition in Down Syndrome and Alzheimer’s models, aiming to improve memory and sleep quality through pharmacological interventions. Her work bridges behavioral neuroscience with neurochemistry to enhance cognitive function. 🧠💡🛌

Awards & Recognitions 🏅

Elsa has received prestigious grants, including the Jerome Lejeune Research Grants (2019, 2020), the Fyssen Foundation Research Grant (2017), and travel awards for conferences such as T21RS (2021) and Advances in Sleep and Circadian Science (2019). She was also recognized by the French Society for Research and Sleep Medicine (2014) and received a European Neuroscience Federation travel award (2016). 🏅

Publications 

  • Selectively Blocking Small Conductance Ca2+-Activated K+ Channels Improves Cognition in Aged Mice.

  • Short-term γ-aminobutyric acid antagonist treatment improves long-term sleep quality, memory, and decision-making in a Down syndrome mouse model

  • Behavioral and Neuronal Characterizations, across Ages, of the TgSwDI Mouse Model of Alzheimer’s Disease.

  • Inter-individual differences in cognitive tasks: focusing on the shaping of decision-making strategies

  • Handling, task complexity, time-of-day, and sleep deprivation as dynamic modulators of recognition memory in mice

  • Enhancing sleep after training improves memory in down syndrome model mice

 

Alvaro Garcia | Computer vision | Best Researcher Award

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Dr. Alvaro Garcia | Computer vision | Best Researcher Award

Álvaro García Martín es Profesor Titular en la Universidad Autónoma de Madrid, especializado en visión por computadora y análisis de video. 🎓 Obtuvo su título de Ingeniero de Telecomunicación en 2007, su Máster en Ingeniería Informática y Telecomunicaciones en 2009 y su Doctorado en 2013, todos en la Universidad Autónoma de Madrid. 🏫 Ha trabajado en detección de personas, seguimiento de objetos y reconocimiento de eventos, con más de 22 artículos en revistas indexadas y 28 en congresos. 📝 Ha realizado estancias en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. 🌍 Su investigación ha contribuido al desarrollo de sistemas de videovigilancia inteligentes, análisis de secuencias de video y procesamiento de señales multimedia. 📹 Ha sido reconocido con prestigiosos premios y ha participado en múltiples proyectos europeos de innovación tecnológica. 🚀

Profile

Education 🎓

🎓 Ingeniero de Telecomunicación por la Universidad Autónoma de Madrid (2007). 🎓 Máster en Ingeniería Informática y Telecomunicaciones con especialización en Tratamiento de Señales Multimedia en la Universidad Autónoma de Madrid (2009). 🎓 Doctor en Ingeniería Informática y Telecomunicación por la Universidad Autónoma de Madrid (2013). Su formación 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). 🌍 Durante su doctorado, recibió la beca FPI-UAM para la realización de su investigación. Su sólida formación académica le ha permitido contribuir significativamente al campo del análisis de video y visión por computadora, consolidándose como un experto en la detección, seguimiento y reconocimiento de eventos en secuencias de video. 📹

Experience 👨‍🏫

🔬 Se unió al grupo VPU-Lab en la Universidad Autónoma de Madrid en 2007. 📡 De 2008 a 2012, fue becario de investigación (FPI-UAM). 🎓 Entre 2012 y 2014, trabajó como Profesor Ayudante. 👨‍🏫 De 2014 a 2019, fue Profesor Ayudante Doctor. 📚 De 2019 a 2023, ocupó el cargo de Profesor Contratado Doctor. 🏛️ Desde septiembre de 2023, es Profesor Titular en la Universidad Autónoma de Madrid. 🏆 Ha participado en múltiples proyectos europeos sobre videovigilancia, transmisión de contenido multimedia y reconocimiento de eventos, incluyendo PROMULTIDIS, ATI@SHIVA, EVENTVIDEO y MobiNetVideo. 🚀 Ha realizado estancias de investigación en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. 🌍 Su experiencia docente abarca asignaturas en Ingeniería de Telecomunicaciones, Ingeniería Informática e Ingeniería Biomédica.

Research Interests 🔬

🎯 Su investigación se centra en la visión por computadora, el análisis de secuencias de video y la inteligencia artificial aplicada a entornos de videovigilancia. 📹 Especialista en detección de personas, seguimiento de objetos y reconocimiento de eventos en video. 🧠 Desarrolla algoritmos de aprendizaje profundo y visión artificial para mejorar la seguridad y automatización en ciudades inteligentes. 🏙️ Ha trabajado en proyectos sobre videovigilancia, transmisión multimedia y detección de anomalías en video. 🔬 Su investigación incluye procesamiento de imágenes, análisis semántico y redes neuronales profundas. 🚀 Participa activamente en proyectos internacionales y colabora con universidades como Carnegie Mellon, Queen Mary y TU Berlin. 🌍 Ha publicado en IEEE Transactions on Intelligent Transportation Systems, Sensors y Pattern Recognition, consolidándose como un referente en el campo de la visión por computadora. 📜

Awards & Recognitions 🏅

🥇 Medalla “Juan López de Peñalver” 2017, otorgada por la Real Academia de Ingeniería. 📜 Reconocimiento por su contribución a la ingeniería española en el campo de la visión por computadora y análisis de video. 🏛️ Ha recibido financiación para múltiples proyectos de investigación europeos y nacionales. 🔬 Ha participado en iniciativas de innovación en videovigilancia y análisis de video para seguridad. 🚀 Sus contribuciones han sido publicadas en las principales conferencias y revistas científicas del área. 📚 Su trabajo ha sido citado más de 4500 veces y cuenta con un índice h de 16 en Google Scholar. 📊

Publications 

1. Rafael Martín-Nieto, Álvaro García-Martín, Alexander G. Hauptmann, and Jose. M.
Martínez: “Automatic vacant parking places management system using multicamera
vehicle detection”. IEEE Transactions on Intelligent Transportation Systems, Volume 20,
Issue 3, pp. 1069-1080, ISSN 1524-9050, March 2019.

2. Rafael Martín-Nieto, Álvaro García-Martín, Jose. M. Martínez, and Juan C. SanMiguel:
“Enhancing multi-camera people detection by online automatic parametrization using
detection transfer and self-correlation maximization”. Sensors, Volume 18, Issue 12, ISSN
1424-8220, December 2018.

3. Álvaro García-Martín, Juan C. SanMiguel and Jose. M. Martínez: “Coarse-to-fine adaptive
people detection for video sequences by maximizing mutual information”. Sensors,
Volume 19, Issue 4, ISSN 1424-8220, January 2019.

4. Alejandro López-Cifuentes, Marcos Escudero-Viñolo, Jesús Bescós and Álvaro GarcíaMartín: “Semantic-Aware Scene Recognition”. Pattern Recognition. Accepted February
2020.

5. Paula Moral, Álvaro García-Martín, Marcos Escudero Viñolo, Jose M. Martinez, Jesus
Bescós, Jesus Peñuela, Juan Carlos Martinez, Gonzalo Alvis: “Towards automatic waste
containers management in cities via computer vision: containers localization and geopositioning in city maps”. Waste Management, June 2022.

6. Javier Montalvo, Álvaro García-Martín, Jesus Bescós: “Exploiting Semantic Segmentation
to Boost Reinforcement Learning in Video Game Environments”. Multimedia Tools and
Applications. September 2022.

7. Paula Moral, Álvaro García-Martín, Jose M. Martinez, Jesus Bescós: “Enhancing Vehicle
Re-Identification Via Synthetic Training Datasets and Re-ranking Based on Video-Clips
Information”. Multimedia Tools and Applications. February 2023.

8. Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo and Alvaro GarciaMartin: “On exploring weakly supervised domain adaptation strategies for semantic
segmentation using synthetic data”. Multimedia Tools and Applications. February 2023.

9. Juan Ignacio Bravo Pérez-Villar, Álvaro García-Martín, Jesús Bescós, Marcos EscuderoViñolo: “Spacecraft Pose Estimation: Robust 2D and 3D-Structural Losses and
Unsupervised Domain Adaptation by Inter-Model Consensus”. IEEE Transactions on
Aerospace and Electronic Systems. August 2023.

10. Javier Montalvo, Álvaro García-Martín, José M. Martinez. “An Image-Processing Toolkit
for Remote Photoplethysmography”, Multimedia Tools and Applications. July 2024.

11. Juan Ignacio Bravo Pérez-Villar, Álvaro García-Martín, Jesús Bescós, Juan C. SanMiguel:
“Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on
Predicted-View Synthesis”. IEEE Transactions on Aerospace and Electronic Systems.
May 2024.

12. Kirill Sirotkin, Marcos Escudero-Viñolo, Pablo Carballeira, Álvaro García-Martín:
“Improved Transferability of Self-Supervised Learning Models Through Batch
Normalization Finetuning”. Applied Intelligence. Aug 2024.

13. Javier Galán, Miguel González, Paula Moral, Álvaro García-Martín, Jose M. Martinez:
“Transforming Urban Waste Collection Inventory: AI-Based Container Classification and
Re-Identification”. Waste Management, Feb 2025.

Engy Risha | Clinical Pathology | Best Researcher Award

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Dr. Engy Risha | Clinical Pathology | Best Researcher Award

Prof. Engy Fikry Mohamed Hassan Risha is the Vice Dean for Education and Student Affairs at Mansoura University – Faculty of Veterinary Medicine, Clinical Pathology. She has contributed 75 research publications in clinical pathology and veterinary sciences. With a strong academic background, she has held multiple administrative and academic positions, including Head of the Clinical Pathology Department (2015-2022). She has received numerous awards, including the Best PhD Thesis Award (2011) and International Publications Incentive Awards (2013-present). She actively participates in quality assurance, course standardization, and accreditation processes at her faculty. Additionally, she serves as a reviewer for several prestigious journals in veterinary and environmental sciences. Prof. Engy is proficient in clinical hematology, clinical chemistry, immunology, and molecular biology techniques. She has international research experience in Germany and expertise in statistical analysis, immunohistochemistry, and avian clinical pathology.

Profile

Education 🎓

📌 PhD in Clinical Pathology – Mansoura University, Egypt (2010)
📌 Master’s Degree in Clinical Pathology – Mansoura University, Egypt (2004)
📌 Bachelor of Veterinary Sciences (Honors) – Mansoura University, Egypt (2000)

Prof. Engy has progressively advanced through academic ranks, demonstrating excellence in veterinary clinical pathology. Her PhD research was part of a joint internal mission program between Hannover and Egypt (2008-2009), enhancing her expertise in molecular biology, histology, and immunological techniques. She has also undergone specialized training in avian clinical pathology, clinical hematology, chemistry, and immunology. Additionally, she holds an ICDL certification from UNESCO (2006), reflecting her strong computer skills for academic and research applications.

Experience 👨‍🏫

🔹 Vice Dean for Education and Student Affairs – Mansoura University (2022-2025)
🔹 Head of Clinical Pathology Department – Mansoura University (2015-2022)
🔹 Professor of Clinical Pathology – Mansoura University (2020-Present)
🔹 Assistant Professor of Clinical Pathology – Mansoura University (2015-2020)
🔹 Lecturer of Clinical Pathology – Mansoura University (2010-2015)
🔹 Assistant Lecturer – Mansoura University (2004-2010)
🔹 Demonstrator – Mansoura University (2001-2004)

She has significant expertise in immunohistochemistry, tissue culture, quantitative PCR, and virus infection assays from her research tenure at the University of Veterinary Medicine Hannover, Germany (2008-2009). She is also skilled in statistical analysis (t-test, ANOVA) and photographic histological documentation.

Research Interests 🔬

🔬 Clinical Pathology – Hematology, Chemistry, Immunology
🔬 Molecular Biology – Quantitative PCR, Virus Titration, Immunofluorescence
🔬 Histopathology & Immunohistochemistry – Antigen Retrieval Techniques, Tissue Culture
🔬 Avian Clinical Pathology – Veterinary Diagnostic Applications
🔬 Statistical Analysis – t-test, ANOVA, Data Interpretation

Prof. Engy has 75 research publications in high-impact journals, covering clinical and molecular pathology applications. She is an active reviewer for international journals such as Environmental Toxicology and Pharmacology, Applied Organometallic Chemistry, and the Polish Journal of Veterinary Sciences. She also plays a key role in strategic planning, curriculum development, and accreditation for veterinary education. 🚀

Awards & Recognitions 🏅

🏅 Best PhD Thesis Award – Mansoura University (2011)
🏅 International Publications Incentive Award – Mansoura University (2013-present)
🏅 PhD Joint Internal Mission Program – Hannover & Egypt (2008-2009)

Prof. Engy has been recognized for her outstanding contributions to veterinary medicine and research, particularly in clinical pathology. Her international research collaboration has significantly contributed to advancing veterinary diagnostic techniques.

Publications 

Peng Sun | Cross-cultural studies | Best Researcher Award

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Mr. Peng Sun | Cross-cultural studies | Best Researcher Award

PENG SUN, Ph.D., is a Chinese Canadian academic leader and researcher. He is the Dean of Siming International Academy (SIA) and a distinguished professor at Lincoln University College, Wrexham Glyndwr University, and Asia Metropolitan University. He also serves as a visiting professor at Universidad Europea Miguel de Cervantes. He is a Foreign Fellow of the American Psychological Association, a member of the Canadian Psychological Society, and a lifetime member of the Canadian Chinese Professional Association. Recognized as a high-end foreign talent by China’s Ministry of Science and Technology and Guangdong Province, he holds senior qualifications in human resource management. His expertise spans higher education, human resources, and organizational behavior, contributing significantly to research on trust in Chinese organizations.

Profile

Education 🎓

PENG SUN earned a Ph.D. in Management (Human Resources Management) from Lincoln University College (2018-2021) and a Doctor of Business Administration in Organizational Behavior from Asia Metropolitan University (2016-2018). He obtained an MBA in Management from the University of Sunderland (2009-2010). He holds a Bachelor of Human Resources Management (Hons) from York University (2004-2008) and another Bachelor’s degree in Human Resource Management from the same institution (2004-2007). His qualifications also include certifications as a high-end foreign talent (2017), high-level foreign talent (2018), Level I Human Resources Professional (2018), and Level II Psychiatrist (2014). Additionally, he holds a North American Standard First Aid & CPR Level C certification from Rescue 7 Inc. (2007).

Experience 👨‍🏫

PENG SUN serves as the Dean of Siming International Academy (SIA), where he leads academic initiatives. He is a distinguished professor and doctoral supervisor at Lincoln University College (Shenzhen Center, PRC) and an Associate Academic Director at Wrexham Glyndwr University (China Center). Additionally, he is a distinguished professor at Asia Metropolitan University (China Center) and a visiting professor at Universidad Europea Miguel de Cervantes. He is actively involved in psychological and HR-related associations, including the American Psychological Association, the Canadian Psychological Society, and the Shenzhen Psychological Consultants Association’s Ethics Committee. His career reflects expertise in higher education leadership, human resource management, and organizational behavior.

Research Interests 🔬

PENG SUN’s research explores trust dynamics in Chinese organizations, focusing on superior-subordinate relationships, employer-employee trust, and organizational behavior. His work emphasizes how hierarchical structures impact trust and efficiency in Chinese firms. He has published extensively in journals such as the International Journal of Psychosocial Rehabilitation and the International Journal of Control and Automation. Notable studies include trust-based organizational efficiency, superior behavior structures, and interpersonal trust within hierarchical settings. His findings contribute to improving workplace relationships, organizational efficiency, and employee belonging behavior in corporate environments. His interdisciplinary research integrates psychology, human resource management, and business administration.

Awards & Recognitions 🏅

PENG SUN has received multiple prestigious recognitions, including the “High-End Foreign Talent” qualification from the Foreign Experts Bureau of China’s Ministry of Science and Technology (2017) and “Guangdong Provincial High-Level Foreign Talent” status (2018). He holds a senior professional qualification in human resource management from the Occupational Skills Appraisal Center of China (2018). As a Foreign Fellow of the American Psychological Association and a member of the Canadian Psychological Society, he is acknowledged for his contributions to psychology and HR research. Additionally, he is a lifetime member of the Canadian Chinese Professional Association and an ethics committee member of the Shenzhen Psychological Consultants Association.

Publications 📚

[1] Sun, P. (2020). The Relationship between Superiors and Their Subordinates: A Study ontheTrustFactor in Chinese Organizations. First Joint International Conference ATMIYA-LINCOLN2020.

[2] Sun, P. (2020). Trust Relationship between Employers and Employees: The Context of ChineseOrganizations. MAIMS International Conference (MIC’ 2020).

[3] Sun, P., Raju, V., Bhaumik, A., & Law, K. A. (2020). The Structure of Superior Behavior andIndividual Belonging Behavior Based on Trust Development Direction in Chinese Firms. International Journal of Psychosocial Rehabilitation, 24(6), 73-92. Retrieved fromDOI:
10.37200/IJPR/V24I6/PR260006.

[4] Sun, P., Raju, V., Bhaumik, A., & Law, K. A. (2020). Interpersonal Trust within an Organizationbasedon Hierarchical Context: Towards Improving Organizational Efficiency in China. International
Journal of Psychosocial Rehabilitation, 24(6), 73-92. Retrieved from DOI:
10.37200/IJPR/V24I6/PR260005.

[5] Sun, P., Law, K. A., & Bhaumik, A. (2019). Identifying the Trust Relationship between Employersand Employees: In the Context of Chinese Organizations. International Journal of Control andAutomation, 12(5), 51-62. Retrieved from
http://sersc.org/journals/index.php/IJCA/article/view/1415

[6] Sun, P., Raju, V., Bhaumik, A., & Law, K. A. (2019). Factors Determining the RelationshipbetweenSuperiors and Their Subordinates: Evaluating the Trust Factor in Chinese Organizations. International Journal of Control and Automation, 12(5), 63-76. Retrieved fromhttp://sersc.org/journals/index.php/IJCA/article/view/1416

Aakash Kumar | Path Planning | Best Researcher Award

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Dr. Aakash Kumar | Path Planning | Best Researcher Award

Dr. Aakash Kumar is a Postdoctoral Researcher at Zhongshan Institute of Changchun University of Science and Technology, China. Born in September 1987 in Pakistan, he specializes in Control Science and Engineering with expertise in AI, deep learning, and computer vision. Fluent in English, Chinese, Urdu, and Sindhi, he has worked extensively on spiking neural networks, UAV fault detection, and deep learning optimization. His research contributions span AI-driven robotics, autonomous vehicles, and computational neuroscience. Dr. Kumar has collaborated internationally, guiding Ph.D. and Master’s students, and publishing in renowned journals. He has also worked as a Machine Learning Engineer and Data Scientist. With a strong background in software development, statistical modeling, and GPU parallelization, he actively explores AI advancements. His interdisciplinary work bridges academia and industry, focusing on intelligent automation, efficient deep learning models, and AI applications in healthcare and engineering. 📊🤖🔬

Profile

Education 🎓

Dr. Aakash Kumar earned a Doctor of Engineering (2017–2022) and a Master’s (2014–2017) in Control Science and Engineering from the University of Science and Technology of China, specializing in Control Systems. Both degrees were fully funded by prestigious scholarships, including the Chinese Academy of Sciences-The World Academy of Sciences President’s Fellowship and the Chinese Government Scholarship. He also completed a Diploma in Chinese Language (2013–2014) from Anhui Normal University, achieving HSK-4 proficiency. His academic journey began with a B.S. in Electronic Engineering (2007–2011) from the University of Sindh, Pakistan. His education has been pivotal in shaping his expertise in AI-driven robotics, computational intelligence, and deep learning optimization. Through rigorous research and training, he has honed his skills in deep learning, reinforcement learning, and AI applications in control systems. His academic foundation supports his contributions to AI-powered automation, smart systems, and computational modeling. 🏅📡

Experience 👨‍🏫

Dr. Aakash Kumar has been a Postdoctoral Researcher (2022–Present) at Zhongshan Institute of Changchun University of Science and Technology, China, where he develops AI-driven solutions for robotics and deep learning applications. Previously, he worked remotely as a Machine Learning Engineer (2021–2022) at COSIMA.AI Inc., USA, where he contributed to AI-based cancer detection, sign language translation, and smart vehicle monitoring. Earlier, he was a Data Scientist (2012–2013) at Japan Cooperation Agency, Pakistan, analyzing agriculture and livestock data. His academic career includes a Lecturer role (2011–2012) at The Pioneers College, Pakistan. He has led AI research initiatives, supervised Ph.D. and Master’s students, and optimized neural networks for industrial applications. With expertise in AI model compression, computer vision, and reinforcement learning, he has been instrumental in developing computational techniques for real-world automation, AI-powered robotics, and UAV fault detection. His work integrates deep learning, optimization, and AI-driven automation. 🏢🤖📈

Research Interests 🔬

Dr. Aakash Kumar’s research focuses on AI-driven robotics, deep learning optimization, and computational intelligence. He has developed Deep Spiking Q-Networks (DSQN) for mobile robot path planning, a CNN-LSTM-AM framework for UAV fault detection, and Deep Conditional Generative Models (DCGMDL) for supervised classification. His work integrates reinforcement learning, neural network pruning, and AI-driven automation to enhance machine learning efficiency. He specializes in deep learning model compression, AI-powered automation, and collaborative data analysis methods. His projects include endoscopy fault detection, smart vehicle monitoring, and neuropsychological condition prediction using AI. With extensive experience in R, Python, TensorFlow, and MATLAB, he develops AI models for healthcare, autonomous systems, and intelligent automation. His interdisciplinary research bridges academia and industry, advancing AI for real-world applications in robotics, deep learning optimization, and intelligent control systems. 🚀📡📊

Awards & Recognitions 🏅

Dr. Aakash Kumar has received numerous prestigious awards, including the Chinese Academy of Sciences-The World Academy of Sciences President’s Fellowship (2017–2022) and the Chinese Government Scholarship (2014–2017, 2013–2014). His AI research achievements earned recognition in top conferences, including IEEE Infoteh-Jahorina and Neurocomputing. He has been honored for his contributions to deep learning and AI-powered robotics, including Best Research Paper Awards at multiple international conferences. His work on efficient CNN optimization and deep spiking Q-networks has gained significant academic and industry recognition. As a speaker at AI conferences, he has presented on generative AI, photon-level ghost imaging, and autonomous vehicle advancements. He continues to receive accolades for his groundbreaking research in AI, robotics, and computational intelligence, solidifying his reputation as a leading expert in control systems and AI-driven automation. 🏅🔬📢

Publications 📚

Zhenxing Cheng | Motor drive | Best Researcher Award

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Dr. Zhenxing Cheng | Motor drive | Best Researcher Award

Dr. Zhenxing Cheng is a dedicated researcher in electrical engineering at Harbin Institute of Technology, China. He earned his B.S. and M.S. degrees from Shandong University in 2017 and 2020, respectively. His expertise lies in parameter identification, robust control, and model predictive control of Permanent Magnet Synchronous Motors (PMSM). With a strong research background, he has contributed significantly to high-speed PMSM drive control technology, focusing on harmonic suppression, startup stability, and high-performance voltage regulation. His work has been validated through national and provincial-level research projects. Dr. Cheng has published numerous SCI-indexed journal papers and holds a patent in his research domain. His collaborations include contributions to The National Key R&D Plan and Guangdong Provincial Key Laboratory projects. As an active member of the research community, he continues to push the boundaries of electrical engineering, driving advancements in PMSM control technology.

Profile

Education 🎓

Dr. Zhenxing Cheng obtained his B.S. and M.S. degrees in Electrical Engineering from Shandong University, China, in 2017 and 2020, respectively. His academic journey has been marked by a strong foundation in electrical engineering principles, control systems, and power electronics. Currently, he is pursuing a Ph.D. in Electrical Engineering at Harbin Institute of Technology (HIT), where his research focuses on advanced motor control techniques, parameter identification, and model predictive control for Permanent Magnet Synchronous Motors (PMSM). His education has equipped him with extensive knowledge of LCL filters, active damping, and discrete methods for current control. Dr. Cheng has actively contributed to research projects funded under The National Key R&D Plan and Guangdong Provincial Key Laboratory. His rigorous academic training and research experiences have positioned him as a promising scholar in the field of electrical engineering.

Experience 👨‍🏫

Dr. Zhenxing Cheng has extensive research experience in motor control and power electronics. He has worked on multiple national and provincial-level research projects, including The National Key R&D Plan and Guangdong Provincial Key Laboratory grants. His expertise spans harmonic suppression, robust startup, and steady-state error minimization in high-speed PMSM applications. As a Ph.D. researcher, he has collaborated with leading scientists to propose improved control strategies for Permanent Magnet Synchronous Starter-Generators. His work has resulted in 12 journal publications, including SCI and Scopus-indexed papers. He has also contributed to four industry-sponsored consultancy projects and has one patent in process. Dr. Cheng is actively engaged in developing novel bilinear methods for current control and reducing back electromotive force effects in PMSM systems. His contributions continue to enhance the efficiency and reliability of motor control technologies.

Research Interests 🔬

Dr. Zhenxing Cheng’s research revolves around advanced control strategies for Permanent Magnet Synchronous Motors (PMSM). His work focuses on parameter identification, robust control, and model predictive control techniques to enhance motor performance. He specializes in harmonic suppression, active damping, steady-state error minimization, and bilinear methods for current control. His research contributions have been validated in national and provincial-level projects, particularly in high-speed Permanent Magnet Synchronous Starter-Generator (PMS-SG) drive control. He has also explored LCL filter optimization, discrete control methods, and current harmonic reduction techniques to improve the efficiency of power systems. Dr. Cheng has published 12 journal papers and holds a patent for his innovative motor control methodologies. His research aims to develop high-performance, energy-efficient PMSM control systems, benefiting industries such as renewable energy, automotive, and aerospace. His ongoing projects continue to shape the future of motor control and power electronics.

Awards & Recognitions 🏅

Dr. Zhenxing Cheng has received recognition for his contributions to electrical engineering research. His notable honors include funding under The National Key R&D Plan and Guangdong Provincial Key Laboratory grants for his work on PMSM drive control systems. He has been acknowledged for his outstanding publications in SCI and Scopus-indexed journals, with 12 journal articles demonstrating his expertise in motor control, parameter identification, and robust control techniques. His research on harmonic suppression and high-performance voltage regulation has earned him industry collaborations and consultancy projects. He has been nominated for the Best Researcher Award for his innovative work in LCL filter optimization, active damping techniques, and model predictive control. His patent further solidifies his reputation as an emerging leader in the field. Dr. Cheng continues to push the boundaries of electrical engineering, aiming for excellence in research and technological advancements.

Publications 📚

Chunyu Liu | Cognitive Computing | Best Researcher Award

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Dr. Chunyu Liu | Cognitive Computing | Best Researcher Award

Chunyu Liu is a Lecturer at North China Electric Power University, specializing in machine learning, neural decoding, and visual attention. 📚 She earned her B.S. in Mathematics and Applied Mathematics from Henan Normal University, an M.S. in Applied Mathematics from Northwest A&F University, and a Ph.D. in Computer Application Technology from Beijing Normal University. 🎓 She completed postdoctoral training at Peking University. 🔬 Her research integrates AI methodologies with cognitive neuroscience, focusing on neural encoding, decoding, and attention mechanisms. 🧠 She has published over 10 research papers, including six SCI-indexed publications as the first author. 📝 Her work aims to bridge artificial intelligence with human cognitive function understanding, contributing significantly to computational neuroscience. 🌍 Liu has also been involved in several major research projects, furthering advancements in neural signal analysis and cognitive computing. 🚀

Profile

Education 🎓

Chunyu Liu holds a strong academic background in mathematics and computational sciences. She obtained her B.S. degree in Mathematics and Applied Mathematics from Henan Normal University. ➕ She pursued her M.S. in Applied Mathematics at Northwest A&F University, where she deepened her expertise in mathematical modeling. 🔢 Continuing her academic journey, she earned a Ph.D. in Computer Application Technology from Beijing Normal University. 🖥️ Her doctoral research explored advanced AI techniques applied to neural decoding and cognitive processing. 🧠 To further refine her skills, she completed postdoctoral training at Peking University, focusing on integrating artificial intelligence with neural mechanisms. 🔬 Her academic pathway reflects a multidisciplinary approach, merging mathematics, computer science, and cognitive neuroscience to address complex challenges in brain science and AI. 📊 Liu’s education laid the foundation for her contributions to machine learning, visual attention studies, and neural encoding research.

Experience 👨‍🏫

Dr. Chunyu Liu is currently a Lecturer at North China Electric Power University, where she teaches and conducts research in cognitive computing and machine learning. 🎓 She has led and collaborated on multiple projects related to neural encoding and decoding, investigating how the brain processes object recognition, emotions, and attention. 🧠 Prior to her current role, she completed postdoctoral research at Peking University, where she worked on advanced AI-driven models for neural signal analysis. 🔍 Over the years, Liu has gained extensive experience in analyzing multimodal neural signals, including magnetoencephalography (MEG) and functional MRI (fMRI). 📡 She has also served as a reviewer for esteemed scientific journals and collaborated with interdisciplinary research teams on AI and brain science projects. 🔬 Her expertise extends to both academia and industry, where she has contributed to the development of novel computational models for decoding brain activity. 🚀

Research Interests 🔬

Dr. Chunyu Liu’s research integrates artificial intelligence and brain science to understand cognitive functions through neural decoding. 🧠 She employs multi-modal neural signals such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to analyze brain activity. 📡 Her work explores neural encoding and decoding, focusing on object recognition, emotion processing, and multiple-object attention. 🎯 She develops AI-based models to extract human brain features and gain insights into cognitive mechanisms. 🤖 By integrating psychological experimental paradigms with AI, Liu aims to advance computational neuroscience. 🏆 Her research also inspires the development of new AI theories and algorithms based on principles of brain function. 📊 She has led major projects in cognitive computing, contributing significantly to both theoretical advancements and practical applications in neural signal processing. 🚀 Through her work, she bridges the gap between human cognition and artificial intelligence, driving innovations in brain-computer interface research. 🏅

 

Awards & Recognitions 🏅

Dr. Chunyu Liu has received recognition for her outstanding contributions to cognitive computing and AI-driven neuroscience research. 🏅 She has been nominated for the prestigious International Cognitive Scientist Award for her pioneering work in neural decoding and visual attention mechanisms. 🎖️ Liu’s research publications have been featured in high-impact journals, earning her accolades from the scientific community. 📜 Her first-author papers in IEEE Transactions on Neural Systems and Rehabilitation Engineering, Science China Life Sciences, and IEEE Journal of Biomedical and Health Informatics have been widely cited. 📝 She has also been honored with research grants and funding for AI-driven cognitive studies. 🔬 Her innovative work in decoding brain signals has been recognized in international AI and neuroscience conferences. 🌍 Liu’s academic excellence and contributions continue to shape the field of computational neuroscience and machine learning applications in cognitive science. 🚀

Publications 📚

Neriman Temel Aksu | Physiotherapy and Rehabilitataion | Best Researcher Award

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Dr. Neriman Temel Aksu | Physiotherapy and Rehabilitataion | Best Researcher Award

Neriman Temel Aksu is an Assistant Professor and Doctor Physiotherapist at Akdeniz University Faculty of Health Sciences, Antalya, Turkey. She completed her undergraduate degree in Physiotherapy and Rehabilitation at Istanbul University. With seven years of clinical experience at Antalya Anadolu Hospital, she later pursued a master’s degree in Movement and Exercise Sciences at Akdeniz University. She further specialized in Pulmonary Rehabilitation during her second master’s degree and earned her Ph.D. in Physiotherapy and Rehabilitation from Süleyman Demirel University. Her research focuses on pulmonary rehabilitation, sleep quality in post-lung resection patients, and the effects of kinesiology taping and Qigong training. She has published numerous research articles and books and is an active member of various professional organizations, including TÜSAD, Türk Toraks Derneği, and the European Respiratory Society. Dr. Aksu is recognized for her contributions to physiotherapy and rehabilitation, particularly in respiratory function and post-surgical patient care.

Profile

Education 🎓

Neriman Temel Aksu completed her undergraduate degree in Physiotherapy and Rehabilitation at Istanbul University. She pursued her first master’s degree in Movement and Exercise Sciences at Akdeniz University, where she explored innovative rehabilitation techniques. Recognizing the significance of respiratory physiotherapy, she completed her second master’s degree in Pulmonary Rehabilitation at Akdeniz University, deepening her expertise in respiratory function and post-surgical recovery. She then obtained her Ph.D. in Physiotherapy and Rehabilitation from Süleyman Demirel University, where she conducted advanced research on the effects of Qigong exercise training on patients’ shoulder and respiratory functions. Her academic journey reflects a strong commitment to evidence-based physiotherapy practices and patient-centered rehabilitation. Throughout her education, she integrated both clinical and research perspectives to enhance therapeutic outcomes, specializing in pulmonary rehabilitation, pain management, and exercise interventions for post-thoracic surgery patients. Her academic qualifications have significantly shaped her contributions to physiotherapy education and practice.

Experience 👨‍🏫

Dr. Neriman Temel Aksu has extensive experience in physiotherapy and rehabilitation, combining clinical practice, research, and academia. She worked as a specialist physiotherapist at Antalya Anadolu Hospital for seven years, where she gained hands-on experience in patient rehabilitation and pain management. She later transitioned to academia as a Research Assistant at Akdeniz University Faculty of Health Sciences, contributing to physiotherapy education and clinical research. After completing her doctorate, she was appointed as an Assistant Professor at Akdeniz University, where she continues to teach and mentor students while conducting research in pulmonary rehabilitation. Her expertise includes evaluating the effects of exercise therapy, kinesiology taping, and relaxation techniques on respiratory function and post-operative recovery. She has published extensively in high-impact journals and authored several books on physiotherapy. Her academic and professional journey showcases her dedication to advancing physiotherapy practices and improving patient outcomes through innovative rehabilitation approaches.

Research Interests 🔬

Dr. Neriman Temel Aksu’s research primarily focuses on pulmonary rehabilitation, respiratory function improvement, and post-operative recovery strategies. Her studies have evaluated sleep quality in lung resection patients, highlighting the role of progressive muscle relaxation exercises. She has investigated the effects of kinesiology taping on pain and respiratory function in thoracotomy patients, contributing to non-invasive rehabilitation techniques. Her doctoral research on Qigong exercise training explored its impact on shoulder mobility and lung function, providing new insights into integrative therapy for post-surgical recovery. Additionally, she has analyzed the benefits of connective tissue massage on pain relief, quality of life, and hospital stay duration. With nine peer-reviewed journal publications and multiple research projects, her work significantly influences clinical rehabilitation protocols. She actively collaborates with national and international respiratory societies to enhance physiotherapy interventions. Her research aims to advance evidence-based practices that improve patient outcomes in post-surgical and chronic respiratory conditions.

Dr. Neriman Temel Aksu has received multiple accolades for her contributions to physiotherapy and rehabilitation. Her research in pulmonary rehabilitation and post-surgical recovery has earned her recognition in national and international physiotherapy forums. She has been nominated for the Best Researcher Award, highlighting her impactful work in respiratory physiotherapy. Additionally, her studies on sleep quality, kinesiology taping, and Qigong training have been acknowledged by professional organizations such as TÜSAD and Türk Toraks Derneği. She has published seven books with ISBN, contributing significantly to physiotherapy education. Her publications in SCI and Scopus-indexed journals reflect the high caliber of her research. She is an esteemed member of the European Respiratory Society, where she actively participates in collaborative research. Through her dedication to evidence-based practice and continuous contributions to physiotherapy, she has established herself as a leading researcher in rehabilitation sciences, particularly in pulmonary and post-surgical patient care.

Publications 📚