Prof. Donkyu Baek | Sensing Data Award | Best Researcher Award

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Prof. Donkyu Baek | Sensing Data Award | Best Researcher Award 

Prof. Donkyu Baek, Chungbuk National University, South Korea

Dr. Donkyu Baek (백돈규) is an Associate Professor at the School of Semiconductor Engineering, College of Electrical and Computer Engineering, Chungbuk National University in Cheongju, South Korea. He earned his Ph.D. in Electrical Engineering from KAIST (Korea Advanced Institute of Science and Technology) in 2017, where he also completed his Master’s degree. His research spans energy-efficient system optimization for UAVs (Unmanned Aerial Vehicles), low-power electric vehicles, and IoT applications, with a focus on energy harvesting technologies. Prior to his current position, Dr. Baek served as an Assistant Professor at Chungbuk National University’s School of Electronics Engineering and held postdoctoral research fellowships at KAIST and Politecnico di Torino, Italy. His contributions to energy-efficient design have earned him several accolades, including awards from the IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED) and the Design Automation Conference (DAC). Dr. Baek has been an active member of several technical program committees and continues to contribute to leading conferences in his field.

Professional Profile:

 

Suitability of Dr. Donkyu Baek for the Best Researcher Award

Dr. Donkyu Baek’s academic career and research contributions reflect an excellent fit for the Best Researcher Award. His multidisciplinary expertise in energy-efficient UAVs, low-power electric vehicles, and on-chip design for IoT applications showcases innovative and impactful research areas with significant real-world implications. Below is a detailed evaluation of his qualifications:

Education

  1. Doctor of Philosophy (Ph.D.)
    • Field: Electrical Engineering
    • Institution: KAIST, Daejeon, Korea
    • Graduation Date: February 2017
  2. Master of Science (M.S.)
    • Field: Electrical Engineering
    • Institution: KAIST, Daejeon, Korea
    • Graduation Date: February 2011
  3. Bachelor of Science (B.S.)
    • Field: Electrical Engineering
    • Institution: Hanyang University, Seoul, Korea
    • Graduation Date: August 2008

Work Experience

  1. Associate Professor
    • Institution: School of Semiconductor Engineering, Chungbuk National University, Cheongju, Korea
    • Dates: March 2024 – Present
  2. Assistant Professor
    • Institution: School of Electronics Engineering, Chungbuk National University, Cheongju, Korea
    • Dates: March 2020 – February 2024
  3. Postdoctoral Research Fellow
    • Institution: Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy
    • Dates: January 2018 – January 2020
  4. Postdoctoral Research Fellow
    • Institution: School of Electrical Engineering, KAIST, Daejeon, Korea
    • Dates: February 2017 – December 2017

Publication top Notes:

Low-Power Preprocessing System at MCU-Based Application Nodes for Reducing Data Transmission

Navigation Path Following Platform for a Greenhouse Shuttle Robot Using the State-flow Method

Energy-efficient driving scheduling for heterogeneous electric vehicles with consideration of overtaking

On-Chip Energy Harvesting System with Storage-Less MPPT for IoTs

Multi-Criteria Coordinated Electric Vehicle-Drone Hybrid Delivery Service Planning

Preprocessing at Application Nodes for Reduction of Data Transmission in Edge Computing

Efficient Load Balancing Method using Multi-Hop Network in Edge Computing Environment

Flight History-Aware Battery Temperature Estimator for Unmanned Aerial Vehicles Based on Deep Neural Network

Dr. Yue Wang | Sensor development Award | Best Researcher Award

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Dr. Yue Wang | Sensor development Award | Best Researcher Award 

Dr. Yue Wang, University of Science and Technology Liaoning, China

Dr. Yue Wang is an Associate Professor at the School of Chemical Engineering at the University of Science and Technology Liaoning in China. He earned his Bachelor’s degree from the University of Science and Technology Anshan and both his Master’s and Doctorate degrees from the University of Science and Technology Liaoning and Saitama Institute of Technology, Japan, respectively. Since joining the University of Science and Technology Liaoning in 2006, Dr. Wang has focused his research on sensors and biosensors, biofuel cells, supercapacitors, energy harvesting, and artificial muscles. His work has resulted in over 60 published scientific papers, garnering approximately 600 citations, reflecting his significant contributions to the field. Dr. Wang has secured multiple research grants from various institutions, including the Education Department of Liaoning Province and the Natural Science Foundation of Liaoning Province, to advance his projects on conductive sensors, pesticide sensors, electrochemical biosensors, and wearable smart sensing technologies. Additionally, he completed a visiting scholarship at the University of Texas at Dallas in 2019-2020, further enhancing his academic and research expertise.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: Yue Wang

Yue Wang is an exemplary candidate for the Best Researcher Award, primarily due to his substantial academic qualifications, extensive research contributions, and impactful work in the field of Material Science, specifically within sensor and biosensor technologies.

Education

  • Bachelor’s Degree in Material Science
    University of Science and Technology Anshan, China
    September 1998 – July 2002
  • Master’s Degree in Material Science
    University of Science and Technology Liaoning, China
    September 2003 – March 2006
  • Ph.D. in Material Science
    Saitama Institute of Technology, Japan
    April 2008 – March 2011

Work Experience

  • Associate Professor
    University of Science and Technology Liaoning, China
    April 2006 – Present
  • Visiting Scholar
    University of Texas at Dallas
    April 2019 – March 2020

Publication top Notes:

A carbon black–doped chalcopyrite–based electrochemical sensor for determination of hydrogen peroxide

Glucose oxidase, horseradish peroxidase and phenothiazine dyes-co-adsorbed carbon felt-based amperometric flow-biosensor for glucose

Crab gill–derived nanorod-like carbons as bifunctional electrochemical sensors for detection of hydrogen peroxide and glucose

Cellulose-derived hierarchical porous carbon based electrochemical sensor for simultaneous detection of catechol and hydroquinone

A triphenylamine based fluorescent probe for Zn2+ detection and its applicability in live cell imaging

1,8-naphthalimide-triphenylamine-based red-emitting fluorescence probes for the detection of hydrazine in real water samples and applications in bioimaging in vivo

Assoc Prof Dr. Jin Wang | Field Sensing Award | Best Researcher Award

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Assoc Prof Dr. Jin Wang | Field Sensing Award | Best Researcher Award

Assoc Prof Dr. Jin Wang, China University of Geosciences, China

Dr. Jin Wang is an Associate Professor in the Department of Communication Engineering at China University of Geosciences (CUG) in Wuhan, China, where he has been a faculty member since May 2009. He earned his Doctoral Degree in Physical Electronics from Huazhong University of Science and Technology (HUST), and his research focuses on optical electric field sensors, fluorescence and Raman spectroscopy, and free-space optical communications systems. Dr. Wang’s expertise spans several areas including waveguide analysis, optical design, and multispectral fluorescence methods for environmental monitoring. His notable contributions include research on bismuth germanate (BGO) crystal sensors, oil pollution detection using multispectral techniques, and advancements in free-space optical communication technologies. Dr. Wang has held previous positions as a Postdoctoral Researcher at HUST and has worked in both industry and academic roles in the field of optical and electronic engineering.

Professional Profile:

Summary of Suitability for Best Researcher Award: 

Dr. Jin Wang is an accomplished Associate Professor at China University of Geosciences with a strong research portfolio spanning optical electric field sensors, free-space optical communication, and multispectral fluorescence detection methods. His research covers innovative topics such as waveguide fabrication using femtosecond lasers, oil pollution detection using multispectral fluorescence, and the development of robust communication systems for extreme environmental conditions.

Education:

  • Doctoral Degree in Physical Electronics (09/2000 – 09/2006)
    Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology (HUST), Wuhan, China
    Dissertation: “Studies on Adaptive Reception Technology in Optical Wireless Communication”
  • Master’s Degree in Electrical Engineering (09/1997 – 03/2000)
    Ordnance Engineering College, Shijiazhuang, China
    Thesis: “Design of Ultra Wideband Dipole Antenna in the Measurement of Electromagnetic Fields”
  • Bachelor’s Degree in Electrical Engineering (09/1993 – 07/1997)
    Ordnance Engineering College, Shijiazhuang, China

Work Experience:

  • Associate Professor and Associate Director (05/2009 – Present)
    Department of Communication Engineering, China University of Geosciences (CUG), Wuhan, China
    Responsible for teaching, research on optical electric field sensors, and overseeing research projects related to optical communication systems and multispectral fluorescence detection.
  • Postdoctoral Researcher in Communication Engineering (09/2006 – 04/2009)
    Huazhong University of Science and Technology (HUST), Wuhan, China
    Conducted research on free-space optical (FSO) communication systems and developed new techniques for adaptive reception over optical turbulence channels.
  • Photoelectric Design Engineer (11/2005 – 07/2008)
    Wuhan Mengxin Technology CO., LTD, Wuhan, China
    Worked on designing LCOS-based projectors, focusing on optical engine development, cooling systems, and enhancing LED brightness and contrast through optical designs.
  • Digital Circuit Design Engineer (11/1999 – 09/2000)
    Beijing University of Aeronautics and Astronautics, Beijing, China
    Designed digital circuits for fiber optic gyroscopes and worked on output signal simulation systems for fiber optics.

Publication top Notes:

 

Integrated Optical Waveguide Electric Field Sensors Based on Bismuth Germanate

Assoc Prof Dr. Puhong Duan | Remote sensing Award | Young Scientist Award

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Assoc Prof Dr. Puhong Duan | Remote sensing Award | Young Scientist Award

Assoc Prof Dr. Puhong Duan, Hunan University, China

Puhong Duan is an accomplished researcher and academic currently serving as an Associate Professor at the College of Electrical and Information Engineering, Hunan University, in Changsha, China. With a Ph.D. in Pattern Recognition and Intelligent Systems from Hunan University, which he completed in October 2021, Puhong has established himself as a leading expert in the fields of hyperspectral image classification, multi-source data fusion, and object detection. His academic journey began with a Bachelor’s degree in Mathematics and Statistics from Suzhou University, followed by a Master’s degree in Mathematics from Hefei University of Technology. Puhong’s career at Hunan University has seen a steady progression, starting as an Assistant Researcher in 2021, advancing to Associate Researcher in January 2023, and finally being appointed as an Associate Professor in April 2024. His research contributions have significantly advanced the understanding and application of intelligent systems in image processing and data fusion, making him a prominent figure in his field.

Professional Profile:

ORCID

Summary of Suitability for the Research for Young Scientist Award:

Dr. Puhong Duan is an accomplished researcher in the field of pattern recognition, intelligent systems, and remote sensing, with a specific focus on hyperspectral image classification, multi-source data fusion, and object detection. His academic background, including a Ph.D. from Hunan University, and his rapid progression through research and academic positions at Hunan University, showcase his dedication and expertise.

🎓 Education:

  • Ph.D. in Pattern Recognition and Intelligent System
    Hunan University, Changsha, China (Sep. 2017 – Oct. 2021)
  • M.S. in Mathematics
    Hefei University of Technology, Hefei, China (Sep. 2014 – May 2017)
  • B.S. in Mathematics and Statistics
    Suzhou University, Suzhou, China (Sep. 2009 – Jul. 2014)

💼 Working Experience:

  • Associate Professor
    Hunan University, Changsha, China (Apr. 2024 – Present)
  • Associate Researcher
    Hunan University, Changsha, China (Jan. 2023 – Mar. 2024)
  • Assistant Researcher
    Hunan University, Changsha, China (Nov. 2021 – Dec. 2022)

🔬 Research Interests:

  • Hyperspectral Image Classification 🌈
  • Multi-Source Data Fusion 🔗
  • Object Detection 🔍

Puhong Duan is a dedicated scholar and innovator in the field of pattern recognition and intelligent systems, focusing on advanced techniques like hyperspectral image classification and multi-source data fusion. His work significantly contributes to the progress of object detection technologies, pushing the boundaries of what’s possible in modern image analysis.

Publication top Notes:

Channel-Layer-Oriented Lightweight Spectral-Spatial Network for Hyperspectral Image Classification

Click-Pixel Cognition Fusion Network With Balanced Cut for Interactive Image Segmentation

EUAVDet: An Efficient and Lightweight Object Detector for UAV Aerial Images with an Edge-Based Computing Platform

A Robust Infrared and Visible Image Registration Method for Dual-Sensor UAV System

Edge-Guided Hyperspectral Change Detection

Feature Consistency-Based Prototype Network for Open-Set Hyperspectral Image Classification

Feature-Band-Based Unsupervised Hyperspectral Underwater Target Detection Near the Coastline

 

Mr. Mohammad Marjani | Remote sensing | Best Researcher Award

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Mr. Mohammad Marjani | Remote sensing | Best Researcher Award 

Mr. Mohammad Marjani, Memorial University of Newfoundland, Canada

Mohammad Marjani is a dedicated researcher and educator currently pursuing a Doctor of Philosophy in Electrical and Computer Engineering at Memorial University of Newfoundland, specializing in advanced remote sensing and deep learning algorithms for environmental monitoring under the supervision of Dr. Masoud Mahdianpari. He holds a Master of Science in Geospatial Information System (GIS) from K.N.Toosi University of Technology, where he graduated with a stellar GPA of 4.0/4.0, focusing on wildfire spread modeling using deep learning techniques. His academic journey began with a Bachelor of Science in Geodesy and Geomatic Engineering from the same university, where he researched 3D change detection methods in point clouds.Marjani’s research interests span deep learning, machine learning, spatio-temporal modeling, and remote sensing, with particular emphasis on natural hazards like wildfires and methane monitoring. He has accumulated valuable teaching experience as a Teaching Assistant at both the Iran National Geographical Organization and K.N.Toosi University, imparting knowledge in image processing, MATLAB, and Python programming.In addition to his academic endeavors, Marjani is a co-founder of GeoHoosh, an educational group dedicated to promoting artificial intelligence in geomatic and geospatial engineering. His commitment to advancing the field through both research and education underscores his role as a rising expert in geospatial technologies and environmental monitoring.

 

Professional Profile

🎓 EDUCATION

Doctor of Philosophy, Electrical and Computer Engineering
📅 Sep 2023 – Present
📍 Memorial University of Newfoundland, St. John’s, NL, Canada
🌐 Advanced remote sensing and deep learning algorithms for environment monitoring
👨‍🏫 Supervisor: Dr. Masoud Mahdianpari

Master of Science, Geospatial Information System (GIS)
📅 Sep 2020 – Nov 2022
📍 K.N.Toosi University of Technology, Tehran, Iran (KNTU)
📊 GPA: 18.58/20 (4.0/4.0)
🔥 The wildfire spread modeling using deep learning techniques
👨‍🏫 Supervisor: Dr. M.S. Mesgari

Bachelor of Science, Geodesy and Geomatic Engineering
📅 Sep 2016 – Sep 2020
📍 K.N.Toosi University of Technology, Tehran, Iran (KNTU)
📊 GPA: 16.22/20 (3.34/4.0)
📐 Thesis Title: Evaluation of 3D change detection methods in point clouds
👨‍🏫 Supervisor: Dr. H. Ebadi

🔬 RESEARCH INTERESTS

  • Deep Learning 🧠
  • Machine Learning 🤖
  • Spatio-temporal Modeling 🌍
  • Wildfire 🔥
  • Remote Sensing 🛰️
  • Natural Hazards 🌪️
  • Wetland Monitoring 🌿
  • Methane Monitoring 🌱

💼 EXPERIENCE

Teaching Assistantships, Faculty of Iran National Geographical Organization
🖥️ Image Processing
📅 Sep 2019 – Jan 2020

  • Taught MATLAB programming language 💻
  • Prepared lectures 📝
  • Graded course assessments 🧾
  • Defined assignments 📚

Teaching Assistantships, K.N.Toosi University of Technology
🖥️ Computational Intelligence
📅 Sep 2022 – Jan 2023

  • Taught Python programming language 🐍
  • Prepared lectures 📝
  • Graded course assessments 🧾
  • Defined assignments 📚

Co-Founder of GeoHoosh
🌐 Educational Group
📅 Sep 2023 – Present

  • One of the four founders of GeoIntelligence Education Group, named GeoHoosh in Persian 🇮🇷
  • Aims to educate Artificial Intelligence in the Geomatic/Geospatial engineering sub-fields 🧭

Publications Notes:📄

Application of Explainable Artificial Intelligence in Predicting Wildfire Spread: An ASPP-Enabled CNN Approach

CNN-BiLSTM: A Novel Deep Learning Model for Near-Real-Time Daily Wildfire Spread Prediction