Prof. Keon Baek | Data analysis | Best Researcher Award

Keon Baek | Data analysis | Best Researcher Award

Keon Baek | Chosun University | South Korea

Keon Baek is a dedicated Data Scientist and Electrical Engineer based in Gwangju, South Korea 1 ๐Ÿ‡ฐ๐Ÿ‡ท. With a strong academic background and practical experience, he focuses on power market analysis, policy design, and technology development through insightful data analysis ๐Ÿ“Š. His research interests include consumer behavior ๐Ÿ’ก, demand flexibility ๐Ÿ”„, market and policy implications ๐Ÿ›๏ธ, and the growing field of vehicle electrification ๐Ÿš—โšก. Keon’s passion lies in leveraging data to shape the future of sustainable energy.

Professional profile :ย 

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Summary of Suitability :ย 

Keon Baek, a dedicated Data Scientist and Electrical Engineer from Gwangju, South Korea, is an excellent candidate for the Best Researcher Award. With a robust academic foundation and a wealth of hands-on experience, Keon has demonstrated significant contributions to the fields of power market analysis, policy design, and technology development. His expertise lies in using data to inform decisions around sustainable energy, which aligns perfectly with the award’s criteria for groundbreaking research that drives innovation and societal impact.

Education :

  • Ph.D. (Power System & Economics) – Gwangju Institute of Science and Technology (2020.03 โ€“ 2023.02) โšก๐Ÿ’ฐ
  • M.S. (Power System & Economics) – Gwangju Institute of Science and Technology (2018.03 โ€“ 2020.02) ๐Ÿ’ก๐Ÿ“ˆ
  • B.S. (Electrical Engineering) – Korea Advanced Institute of Science and Technology (2004.03 โ€“ 2011.02) โš™๏ธ๐Ÿ”Œ

Experience :

  • Assistant Professor, Dept. of Electrical Engineering – Chosun University (2023. 09 โ€“ 2023. 08) ๐Ÿ‘จโ€๐Ÿซ๐Ÿ’ก
  • Post-doc., Research Institute for Solar and Sustainable Energies (RISE) – Gwangju Institute of Science and Technology (2023. 02 โ€“ 2023.08) โ˜€๏ธ๐ŸŒฑ
  • Electric Engineer, Distribution Transformer Division – Hyundai (2017. 04 โ€“ 2018. 07) ๐Ÿญโšก
  • Engineer, Offshore Plant Engineering Center – Korea Shipbuilding & Offshore Engineering (2015. 02 โ€“ 2017. 03) ๐Ÿšข๐ŸŒŠ
  • Associate Researcher, Wind Power System Research Center – Korea Shipbuilding & Offshore Engineering (2011. 02 โ€“ 2015. 01)
  • Publication Top NOTES :
    Resident Behavior Detection Model for Environment Responsive Demand Response :
    • Authors: K. Baek, E. Lee, J. Kim

    • Published in: IEEE Transactions on Smart Grid, 2021, Vol. 12, Issue 5, Pages 3980-3989

    • Citations: 35

    • Summary: This paper proposes a model for detecting resident behavior in smart grid environments, aiming to optimize demand response (DR) mechanisms. The approach focuses on adjusting electricity usage patterns by predicting and responding to residents’ behavior, enhancing both energy efficiency and grid reliability. This model is crucial for increasing the responsiveness and flexibility of demand response programs in residential areas.

    Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach :
    • Authors: E. Lee, K. Baek, J. Kim

    • Published in: Energies, 2020, Vol. 13, Issue 23, Article 6355

    • Citations: 28

    • Summary: This study assesses the potential flexibility of demand response programs in industrial settings using a data-driven approach. It evaluates how various industrial processes can be adjusted to provide flexibility in energy consumption without negatively impacting production efficiency. The research also explores the use of real-time data to enhance decision-making in demand response strategies, enabling more effective integration of renewable energy sources.

    Multi-Objective Optimization of Home Appliances and Electric Vehicles Considering Customerโ€™s Benefits and Offsite Shared Photovoltaic Curtailment :
    • Authors: Y. Kwon, T. Kim, K. Baek, J. Kim

    • Published in: Energies, 2020, Vol. 13, Issue 11, Article 2852

    • Citations: 22

    • Summary: This paper discusses a multi-objective optimization approach for managing home appliances and electric vehicles (EVs) while considering customer benefits and photovoltaic (PV) energy curtailment. It focuses on maximizing the benefits to consumers by coordinating the use of home appliances and EVs with the availability of solar energy while reducing the waste of excess PV power. The study is significant for improving the efficiency of residential energy management systems.

    Stochastic Optimization-Based Hosting Capacity Estimation with Volatile Net Load Deviation in Distribution Grids :ย 
    • Authors: Y. Cho, E. Lee, K. Baek, J. Kim

    • Published in: Applied Energy, 2023, Vol. 341, Article 121075

    • Citations: 13

    • Summary: The research proposes a stochastic optimization method to estimate hosting capacity in distribution grids, accounting for the volatile nature of net load deviation. The study addresses challenges related to integrating renewable energy sources, such as solar and wind, into existing power grids. It develops a model that quantifies the gridโ€™s capacity to absorb additional renewable energy without compromising stability, providing valuable insights for grid operators managing increasing renewable penetration.

    Datasets on South Korean Manufacturing Factoriesโ€™ Electricity Consumption and Demand Response Participation :
    • Authors: E. Lee, K. Baek, J. Kim

    • Summary: This dataset publication presents detailed information on electricity consumption patterns and the participation of South Korean manufacturing factories in demand response programs. It provides real-world data that can be used to evaluate the effectiveness of demand response strategies and analyze consumption behaviors in industrial sectors. Researchers and energy managers can leverage this dataset to optimize industrial demand response programs and improve grid reliability.

Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | University of Southern California | United States

Mehdi Badami is a dedicated Ph.D. candidate in Environmental Engineering at the University of Southern California (USC) under Prof. Constantinos Sioutas. His expertise lies in air quality improvement, with hands-on experience in air pollution monitoring using advanced instrumentation such as SMPS-CPC, OPS, and Aethalometer 51. He specializes in data-driven environmental assessments, employing Python for pollution source apportionment and emission trend analysis. His research contributes to community-centric environmental policies and sustainable air quality solutions. Passionate about environmental justice, he aims to bridge scientific research with real-world policy implementation. ๐ŸŒฑ๐Ÿ”ฌ

Professional Profile:

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Suitability for the Young Scientist Award

Mehdi Badami is a strong candidate for the Young Scientist Award due to his significant contributions to environmental engineering, particularly in air quality improvement. As a Ph.D. candidate at the University of Southern California (USC), his research focuses on air pollution monitoring and data-driven environmental assessments. His expertise in advanced instrumentation (e.g., SMPS-CPC, OPS, Aethalometer 51) and Python-based pollution source apportionment makes him a valuable asset to the field.

Education & Experience ๐Ÿข๐ŸŽ“

  • Ph.D. Candidate in Environmental Engineering (2022-Present) โ€“ USC, Los Angeles, USA ๐Ÿ‡บ๐Ÿ‡ธ

    • GPA: 3.95/4
    • Advisor: Prof. Constantinos Sioutas
  • M.Sc. in Mechanical Engineering (Fluid Mechanics) (2017-2020) โ€“ University of Tehran, Iran ๐Ÿ‡ฎ๐Ÿ‡ท

    • GPA: 3.77/4
    • Supervisors: Dr. Alireza Riasi, Prof. Kayvan Sadeghy
  • B.Sc. in Mechanical Engineering (2012-2016) โ€“ K. N. Toosi University of Technology, Iran ๐Ÿ‡ฎ๐Ÿ‡ท

  • Research Assistant โ€“ USC Aerosol Lab (2023โ€“Present) ๐Ÿญ๐ŸŒซ๏ธ

    • Conducted air pollution measurements using state-of-the-art monitoring systems
    • Developed Python programs for data automation and pollution trend analysis
    • Led collaborations with institutions like Harvard, UCLA, and Dresden University
    • Mentored Ph.D. students on environmental research projects
  • Research Assistant โ€“ Hydro-kinetic Energy Lab, University of Tehran (2017โ€“2022) ๐Ÿ”ฌ๐Ÿ’ง

    • Investigated fluid mechanics phenomena related to blood hammer effects in arteries
  • Teaching Assistant โ€“ USC & University of Tehran (2018โ€“2024) ๐Ÿ“š๐Ÿ‘จโ€๐Ÿซ

    • Assisted in courses on climate change, air quality, fluid mechanics, and thermodynamics

Professional Development ๐Ÿš€

Mehdi Badami has actively contributed to the field of environmental engineering through cutting-edge research on air pollution, sustainability, and emission control. His extensive knowledge of aerosol science, atmospheric chemistry, and data analysis allows him to assess air quality trends with precision. He has developed innovative models for pollution source apportionment, worked on real-time monitoring systems, and collaborated with leading institutions to improve urban air quality. His passion for environmental justice drives his work towards creating actionable solutions that ensure healthier air for communities. His dedication extends beyond academia, as he actively engages in outreach and policy-driven initiatives. ๐ŸŒฟ๐Ÿ“Š

Research Focus ๐Ÿ”

Mehdiโ€™s research centers on air pollution control, environmental monitoring, and sustainable urban development. His work involves identifying and mitigating pollution sources through field measurements and computational models. He specializes in:

  • Air Quality Assessment ๐ŸŒซ๏ธ๐Ÿ“Š โ€“ Studying PM2.5 and ultrafine particle pollution in urban environments
  • Pollution Source Apportionment ๐Ÿญโš–๏ธ โ€“ Analyzing emissions from vehicles, industries, and natural sources
  • Aerosol Science ๐ŸŒช๏ธ๐Ÿ’จ โ€“ Investigating the toxicity and health impacts of airborne particles
  • Machine Learning in Environmental Studies ๐Ÿค–๐Ÿ“‰ โ€“ Utilizing data science to model pollution trends
  • Climate and Environmental Justice ๐ŸŒŽโš–๏ธ โ€“ Advocating for equitable air quality policies in urban communities

Awards & Honors ๐Ÿ†

  • Outstanding Research Assistant Award โ€“ USC, Sonny Astani Department of Civil and Environmental Engineering (2024) ๐Ÿ…
  • Fellowship Award โ€“ USC (2022-2023) ๐ŸŽ“๐Ÿ’ฐ (Recognized for academic excellence in Environmental Engineering)
  • National Fellowship for Masterโ€™s Studies โ€“ University of Tehran (2017) ๐Ÿ“–๐Ÿ†
  • Top 0.15% Rank in National Entrance Exam โ€“ Iran (Competitive ranking in Mechanical Engineering)

Publication Top Notes:

๐Ÿ“„ Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collection โ€“ Atmospheric Environment (2023) โ€“ ๐Ÿ“‘ Cited by: 11
๐Ÿ“„ Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles โ€“ Atmospheric Environment (2023) โ€“ ๐Ÿ“‘ Cited by: 7
๐Ÿ“„ Numerical study of blood hammer phenomenon considering blood viscoelastic effects โ€“ European Journal of Mechanics-B/Fluids (2022) โ€“ ๐Ÿ“‘ Cited by: 7
๐Ÿ“„ Development and performance evaluation of online monitors for near real-time measurement of total and water-soluble organic carbon in fine and coarse ambient PM โ€“ Atmospheric Environment (2024) โ€“ ๐Ÿ“‘ Cited by: 4
๐Ÿ“„ Numerical analysis of laminar viscoelastic fluid hammer phenomenon in an axisymmetric pipe โ€“ Journal of the Brazilian Society of Mechanical Sciences and Engineering (2021) โ€“ ๐Ÿ“‘ Cited by: 3
๐Ÿ“„ Urban emissions of fine and ultrafine particulate matter in Los Angeles: Sources and variations in lung-deposited surface area โ€“ Environmental Pollution (2025) โ€“ ๐Ÿ“‘ Cited by: 1

 

 

 

Mr. Bocheng Zhao | Network post-processing | Best Researcher Award

Mr. Bocheng Zhao | Network post-processing | Best Researcher Award

Mr. Bocheng Zhao, Xidian University, China

Mr. Zhao is an Associate Professor at the School of Computer Science and Technology, Xidian University, where he leads research in interactive learning, deep reinforcement learning, and multi-objective game confrontation. With over 10 publications in prestigious international journals and conferences, his work showcases significant innovation and expertise in artificial intelligence and machine learning. Mr. Zhao actively contributes to the field through his roles in specialized committees, including the Human-Computer Interaction Specialized Committee of the CSIG and the Intelligent Command and Control Specialized Committee of the CCIC. His research interests and professional activities highlight his dedication to advancing AI technology and his influence within the scientific community.

Professional Profile:

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Suitability for the Award

Mr. Bocheng Zhao is a strong contender for the Research for Best Researcher Award due to his significant contributions to the fields of AI and machine learning, particularly in areas that are at the forefront of current technological advancements. His active involvement in professional committees, coupled with his role as an associate professor at a leading institution, further solidifies his position as a leading researcher in his field.

Professional Role and Expertise:

Mr. Zhao is an Associate Professor at the School of Computer Science and Technology, Xidian University, indicating a leadership position in a prominent academic institution. His primary research areas include interactive learning, deep reinforcement learning, and multi-objective game confrontation. This expertise aligns well with cutting-edge research topics in artificial intelligence and machine learning.

Research Contributions:

Mr. Zhao has made substantial contributions to his field with over 10 publications in prestigious international journals and conferences. His work in interactive learning and reinforcement learning addresses complex problems and demonstrates a high level of research innovation and technical expertise.

Professional Memberships:

His involvement in specialized committees, such as the Human-Computer Interaction Specialized Committee of the CSIG and the Intelligent Command and Control Specialized Committee of the CCIC, highlights his active role in shaping the future of these research areas and his influence in the broader scientific community.

Research Interests:

His research interests in interactive learning, intelligent growth, and related fields reflect a focus on advancing knowledge and technology in significant areas of artificial intelligence. This aligns with the goals of the Research for Best Researcher Award, which seeks to recognize individuals making notable contributions to their fields.

Publication Top Notes:

  • Title: Parame: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion
    • Year: 2020
    • Cited by: 60
  • Title: Deep Imitator: Handwriting Calligraphy Imitation via Deep Attention Networks
    • Year: 2020
    • Cited by: 23
  • Title: Pen Tip Motion Prediction for Handwriting Drawing Order Recovery Using Deep Neural Network
    • Year: 2018
    • Cited by: 14
  • Title: Nonrigid Point Matching of Chinese Characters for Robot Writing
    • Year: 2017
    • Cited by: 12
  • Title: Image Hazing and Dehazing: From the Viewpoint of Two-Way Image Translation with a Weakly Supervised Framework
    • Year: 2022
    • Cited by: 5