Mr. Heon-Sung Park | Neural Networks Awards | Best Researcher Award

Posted on by ScienceFather

Mr. Heon-Sung Park | Neural Networks Awards | Best Researcher Award 

Mr. Heon-Sung Park, School of Computer Science and Engineering, Chung-Ang University, South Korea

Heon-Sung Park is a Ph.D. student in the School of Computer Science and Engineering at Chung-Ang University, South Korea, under the guidance of Professor Dae-Won Kim. His research interests focus on artificial intelligence, continual learning, and on-device AI. He previously completed his Master’s degree in the same department and earned his Bachelor’s degree in Information Technology from Silla University. Heon-Sung has contributed to international conferences, including the IEEE International Conference on Consumer Electronics, where he presented his work on a Continual Gesture Recognition System. He has been involved in various projects, such as developing deep learning algorithms for structural adhesive inspection and creating frameworks for on-device AI. He has received several accolades, including the Chung-Ang University Graduate Research Scholarship and the Best Paper Award at the Winter Academic Conference of the Korean Society of Computer and Information. Proficient in Python, LaTeX, and machine learning tools like PyTorch and TensorFlow, Heon-Sung is committed to advancing research in AI and its applications in real-world scenarios.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for the Best Researcher Award: Heon-Sung Park

Heon-Sung Park is a highly qualified candidate for the Best Researcher Award, showcasing an exceptional academic background, significant research contributions, and a commitment to advancing the field of artificial intelligence.

Education 🎓

  • Ph.D. in Computer Science and Engineering
    Chung-Ang University (2022 – Present)
    Academic Adviser: Prof. Dae-Won Kim
  • Master’s in Computer Science and Engineering
    Chung-Ang University (2020 – 2022)
    Academic Adviser: Prof. Dae-Won Kim
  • Bachelor of Science in Information Technology
    Silla University (2014 – 2020)

Work Experience 💼

  • Ph.D. Student
    School of Computer Science and Engineering, Chung-Ang University (2022 – Present)

Achievements 🏆

  • Best Paper Award at the Winter Academic Conference, Korean Society of Computer and Information (2019)
  • Chung-Ang University Graduate Research Scholarship (2022 – 2024)

Awards and Honors 🌟

  • Chung-Ang University Graduate Research Scholarship (2022 – 2024)
  • Best Paper Award (2019) for the research paper presented at the Winter Academic Conference of the Korean Society of Computer and Information

Publication Top Notes:

 

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

Posted on by ScienceFather

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

Dr. Seyed Reza Nabavi | Nueral Network Awards | Best Researcher Award

Posted on by ScienceFather

Dr. Seyed Reza Nabavi | Nueral Network Awards | Best Researcher Award 

Dr. Seyed Reza Nabavi, University of Mazandaran, Iran

Dr. Seyed Reza Nabavi is an Associate Professor of Applied Chemistry in the Department of Applied Chemistry at the University of Mazandaran, Babolsar, Iran. he earned his Ph.D. in Applied Chemistry from the University of Tabriz in 2009, focusing on hybrid modeling and artificial intelligence applications for olefin process optimization. As a visiting scholar at the National University of Singapore in 2008, Dr. Nabavi further honed his expertise in chemical and biomolecular engineering. His teaching repertoire spans diverse topics, including transport phenomena, chemical reactor design, and chemical process modeling at both undergraduate and postgraduate levels. A prolific researcher, his interests lie in polymer nanotechnology, catalytic processes, machine learning in chemical process optimization, and pyrolysis. Notably, he has collaborated on significant projects, such as studying coke formation and inhibitors in naphtha thermal cracking at the bench scale, bridging academia and industry. Married and based in Iran, Dr. Nabavi has received recognition for his academic excellence, including being the top-ranked B.Sc. graduate.

Professional Profile:

ORCID

Suitability for Best Researcher Award: Seyed Reza Nabavi

Based on the provided curriculum vitae, Dr. Seyed Reza Nabavi demonstrates exceptional qualifications that make him a strong candidate for the Best Researcher Award. Below is a summary of his key accomplishments and attributes supporting his suitability for this recognition

🎓 Educational Background

  • Ph.D. in Applied Chemistry (2009), University of Tabriz 🧬
    Thesis: Application of Hybrid Modeling and Artificial Intelligence in Modeling and Optimization of Olefin Processes.

    • Visiting Scholar: National University of Singapore (Apr-Dec 2008).
  • M.Sc. in Applied Chemistry (2003), University of Tabriz 🧵
    Thesis: Preparation and Characterization of Conducting Polyaniline/Nylon-6 Composite Fibers.
  • B.Sc. in Applied Chemistry (2000), University of Sistan and Baluchestan 🏛️
    • 🎖️ First Rank among graduate students.

👨‍🏫 Teaching Experience

  • Expertise in teaching at M.Sc. and B.Sc. levels 📚, including advanced courses:
    • Transport Phenomena, Design of Experiments (DOE), Chemical Reactors, Process Control, and Petrochemical Processes.
    • Proficient in Modeling and Simulation and Unit Operation Laboratories.

🔬 Research Interests

  • Nanotechnology of Polymers: Electrospinning and Nanofiber Membranes 🧵.
  • Catalytic Processes: Ozonation, Photocatalysts, and Reaction Engineering ⚗️.
  • Modeling and Optimization: Applying Machine Learning and Evolutionary Algorithms 🤖.
  • Thermal Cracking & Pyrolysis: Exploring Coke Formation and Mitigation 🔥.

🏅 Academic Positions

  • Associate Professor: 2022 – Present, University of Mazandaran 🏫.
  • Assistant Professor: 2012 – 2022, University of Mazandaran.

🧪 Research Highlights

  • Lead researcher in projects like Coke Formation and Inhibitors in thermal cracking of naphtha (collaboration with Tabriz Petrochemical Company) 🛢️.
  • Published impactful research on polymers, reaction engineering, and optimization using cutting-edge AI techniques.

Publication top Notes:

Multi-Criteria Decision Making in Chemical and Process Engineering: Methods, Progress, and Potential

A liter scale synthesis of hierarchically mesoporous UiO-66 for removal of large antibiotics from wastewater

Data-Based Modeling, Multi-Objective Optimization and Multi-Criteria Decision Making of a Catalytic Ozonation Process for Degradation of a Colored Effluent

A bacterial cellulose-based LiSrVO4:Eu3+ nanosensor platform for smartphone sensing of levodopa and dopamine: point-of-care diagnosis of Parkinson’s disease

Parametric optimization of poly(ether sulfone) electrospun membrane for effective oil/water separation

Deep Learning Aided Multi-Objective Optimization and Multi-Criteria Decision Making in Thermal Cracking Process for Olefines Production