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

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

 

Dr. Peng Zhou | Satellite Imaging | Best Researcher Award

Dr. Peng Zhou | Satellite Imaging | Best Researcher Award 

Dr. Peng Zhou, Beijing Normal University, China

Mr. Peng Zhou is a Ph.D. candidate at the Faculty of Geographical Science, Beijing Normal University, specializing in global environmental change. His research interests span across remote sensing, aerosol studies, and Lidar technology, with a focus on leveraging data science, machine learning, and spatiotemporal modeling techniques. Peng Zhou holds a Master’s degree in Surveying and Mapping Engineering from Henan Polytechnic University and earned his Bachelor’s degree from Nanyang Normal University. His academic pursuits and research aim to contribute to understanding and mitigating environmental challenges through advanced spatial analysis and remote sensing applications.

Professional Profile:

ORCID

 

Education:

  • Ph.D. in Faculty of Geographical Science, Beijing Normal University, expected completion September 2024.
  • M.S. in Surveying and Mapping Engineering, Henan Polytechnic University, September 2021 – July 2024.
  • B.S. in Surveying and Mapping Engineering, Nanyang Normal University, September 2017 – July 2021.

Work Experience:

Mr. Peng Zhou’s professional experience includes research and academic roles focusing on remote sensing, aerosol studies, lidar, data science, machine learning, and spatiotemporal modeling. He has actively contributed to the field of geographical science through his research and affiliations with academic institutions.

 

Publication top Notes:

Quantifying the effects of the microphysical properties of black carbon on the determination of brown carbon using measurements at multiple wavelengths

Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean

Quantifying the effects of the microphysical properties of black carbon on the determination of brown carbon using measurements at multiple wavelengths

Supplementary material to “Quantifying the effects of the microphysical properties of black carbon on the determination of brown carbon using measurements at multiple wavelengths”

R-MFNet: Analysis of Urban Carbon Stock Change against the Background of Land-Use Change Based on a Residual Multi-Module Fusion Network

The Simulated Source Apportionment of Light Absorbing Aerosols: Effects of Microphysical Properties of Partially‐Coated Black Carbon

Dr. Akito Higatani | Intelligent Sensors | Best Researcher Award

Dr. Akito Higatani | Intelligent Sensors | Best Researcher Award

Dr. Akito Higatani, Hanshin Expressway Co., Ltd., Japan

Akito Higatani is an accomplished professional in traffic engineering, currently serving as Assistant Manager in the Planning Department at Hanshin Expressway Co., Ltd. With a career spanning 18 years, he has made significant contributions to the field through his research and practical insights into traffic management and efficiency. Dr. Higatani’s academic journey began at Kyoto University, Japan, where he earned his Bachelor’s degree in Engineering from the Undergraduate School of Global Engineering, specializing in Transportation Engineering and Management. He continued his studies at Kyoto University, obtaining a Master’s degree in Urban Management, focusing on traffic efficiency in urban expressways. His doctoral studies also at Kyoto University culminated in a Doctor of Engineering degree, where his research focused on planning patrolling schedules in urban expressway networks considering traffic incidents and network performance fluctuations. Dr. Higatani has contributed extensively to the field through peer-reviewed papers and presentations at international conferences. His research, such as studying traffic volume fluctuations and travel time reliability measures in the Hanshin Expressway Network, has been instrumental in advancing understanding and strategies in traffic engineering.

 

Professional Profile:

SCOPUS

 

Education:

Akito Higatani pursued his academic journey at Kyoto University, Japan, specializing in Transportation Engineering and Management.

  • Bachelor of Engineering (Undergraduate School of Global Engineering, April 2000 – March 2004): Akito completed his undergraduate studies with a focus on Transportation Engineering and Management. His graduation thesis investigated traffic flow observation using image data.
  • Master of Engineering (Department of Urban Management, April 2004 – March 2006): Continuing his studies at Kyoto University, Akito delved deeper into urban traffic management, particularly focusing on traffic efficiency at merging sections of urban expressways using image data.
  • Doctor of Engineering (Department of Urban Management, April 2012 – March 2015): Akito pursued his doctoral studies, specializing in planning patrolling schedules within urban expressway networks. His dissertation focused on optimizing schedules considering traffic incidents and network performance fluctuations.

Work Experience:

Akito Higatani has accumulated extensive experience in traffic engineering and management, primarily at Hanshin Expressway Co., Ltd.

  • Assistant Manager, Planning Department: Akito has been serving as an Assistant Manager since joining Hanshin Expressway in April 2006. His role involves strategic planning within the Planning Department, focusing on optimizing traffic flow and efficiency across the expressway network.

Academic Achievements:

Akito Higatani has contributed significantly to the field of traffic engineering through peer-reviewed publications and conference presentations:

 

Publication top Notes:

Assessing the Impacts of Autonomous Vehicles on Road Congestion Using Microsimulation

An investigation into the appropriateness of car-following models in assessing autonomous vehicles

Driving simulator experiment on speed reduction during earthquake on an urban expressway

A study of traffic volume fluctuation considering traffic incidents in hanshin expressway network

Slippage test of frictional high strength bolted joints with adhesives for corroded damaged steel members

 

Mr. Mohammad Marjani | Remote sensing | Best Researcher Award

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

 

 

 

 

 

 

 

 

Assoc Prof Dr. Dericks Shukla | Remote Sensing | Excellence in Research

Assoc Prof Dr. Dericks Shukla | Remote Sensing | Excellence in Research 

Assoc Prof Dr. Dericks Shukla, IIT Mandi, India

Dr. Dericks Praise Shukla, born on January 2, 1982, is an esteemed Associate Professor with a robust academic and research background in Remote Sensing and GIS. He began his academic journey with a Bachelor of Science degree in Physics, Electronics, and Mathematics from Ewing Christian College, Allahabad University, completed between 1999 and 2002. He then pursued a Master of Science degree in Remote Sensing and GIS from Jiwaji University, which he obtained from 2002 to 2004. Dr. Shukla further advanced his expertise by earning a Ph.D. in Remote Sensing and Environmental Hydro-Geology from the University of Delhi, where he studied from 2006 to 2012.Dr. Shukla’s professional career has been marked by significant contributions to both teaching and research. Since December 2019, he has been associated with the Indian Institute of Technology (IIT) Mandi, where he is involved in teaching, research, and administrative duties. Prior to this, from January 2015 to November 2019, he also held similar responsibilities at IIT Mandi. From August 2011 to January 2015, Dr. Shukla worked at Ram Lal Anand College and the Department of Geology, where he continued his dedication to teaching and research. His professional journey began at J.M EnviroNet Pvt. Ltd., Gurgaon, where he served as a Functional Area Expert for EIA as a consultant in Remote Sensing and GIS from November 2009 to August 2013.

Professional Profile

Degrees Conferred

  • B.Sc.: Ewing Christian College, Allahabad University 🏛️
    • Fields: Physics, Electronics, and Mathematics (1999-2002) 🧮
  • M.Sc.: Jiwaji University 🌍
    • Fields: Remote Sensing and GIS (2002-2004) 🌐
  • Ph.D.: University of Delhi 🏫
    • Fields: Remote Sensing, Environmental Hydro-Geology (2006-2012) 🌎

Research/Training Experience

  • December 2019 – Present: Indian Institute of Technology Mandi 🏔️
    • Roles: Teaching, Research, Administrative Work 📖
  • January 2015 – November 2019: Indian Institute of Technology Mandi 🏔️
    • Roles: Teaching, Research, Administrative Work 📚
  • August 2011 – January 2015: Ram Lal Anand College and Department of Geology 🏫
    • Roles: Teaching, Research, Administrative Work 📝
  • November 2009 – August 2013: J.M EnviroNet Pvt. Ltd., Gurgaon 🏢
    • Role: Functional Area Expert for EIA as Consultant in Remote Sensing and GIS 🌐

Major Scientific Fields of Interest

  • Remote Sensing & GIS (RS&GIS) 🌐
  • Natural Hazards 🌪️
  • Multispectral and SAR Remote Sensing 🌈
  • Himalayan Geology 🏔️

 

Publications Notes:📄

Discriminative Spectral–Spatial Feature Extraction-Based Band Selection for Hyperspectral Image Classification

Effect of scale and mapping unit on landslide susceptibility mapping of Mandakini River Basin, Uttarakhand, India

Identifying Geotechnical Characteristics for Landslide Hazard Indication: A Case Study in Mandi, Himachal Pradesh, India

Deciphering the role of meteorological parameters controlling the sediment load and water discharge in the Sutlej basin, Western Himalaya

Band Selection Using Combined Divergence–Correlation Index and Sparse Loadings Representation for Hyperspectral Image Classification

Spatial distribution of uranium and chemo-radiological assessment in Hamirpur district, Himachal Pradesh, India