Changhyoun Park | Machine Learning | Best Researcher Award

Dr. Changhyoun Park | Machine Learning | Best Researcher Award

Research Scientist | Pusan National University | South Korea

Changhyoun Park is a South Korean atmospheric scientist and research scholar currently serving as a Research Scientist at the Institute of Environmental Studies and a Lecturer in the Department of Atmospheric Environmental Sciences at Pusan National University (PNU), South Korea. With extensive international academic and research experience, including postdoctoral positions in the USA, Dr. Park has focused on the intersection of atmospheric modeling, greenhouse gas fluxes, and artificial intelligence. His work bridges theoretical research and practical applications, contributing to the advancement of climate and environmental science through teaching, mentorship, and high-impact scholarly publications.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Dr. Changhyoun Park holds a Ph.D. in Atmospheric Sciences from Texas A&M University in the United States, where he conducted advanced research in greenhouse gas fluxes and atmospheric modeling. Prior to this, he earned both his Master’s and Bachelor’s degrees in Atmospheric Sciences from Pusan National University (PNU), South Korea. His academic path reflects a strong commitment to environmental and climate research, enhanced by international collaborations and exposure to multidisciplinary approaches in atmospheric science, machine learning, and mesoscale modeling.

Professional Experience

Dr. Park currently holds dual positions as a Research Scientist at the Institute of Environmental Studies and a Lecturer in the Department of Atmospheric Environmental Sciences at PNU. His prior appointments include postdoctoral research roles at Texas A&M University, the University of California, Los Angeles (JIFRESSE), and PNU. He also has industry experience as a Project Manager at YhKim Co. Ltd. His work includes developing AI-based prediction models, conducting mesoscale simulations, managing national-level carbon modeling projects, and mentoring gifted science students through national science education programs in Korea.

Awards and Honors

Throughout his academic and professional journey, Dr. Changhyoun Park has received multiple awards recognizing his contributions to research and science education. These include the Best Researcher of the Year Award from the Institute of Environmental Studies at PNU, an Outstanding Presentation Award by the Korean Society for Atmospheric Environment, and a Regent’s Graduate Fellowship at Texas A&M University. He was also a session winner at Texas A&M’s Student Research Week and received an Encouragement Award from Korea’s Director’s Council of Gifted Science Education.

Research Focus

Dr. Park’s research centers on micrometeorology, atmospheric carbon modeling, greenhouse gas (GHG) dynamics, and the application of artificial intelligence to environmental prediction systems. His expertise includes mesoscale numerical modeling of GHGs, machine learning-based fog and flux prediction, and eddy covariance data analysis. He has led significant projects on CO₂ radiative forcing, VOC fluxes, and vegetation uptake across East Asia and Korea. His interdisciplinary approach integrates atmospheric science with cutting-edge computational techniques to address pressing climate and environmental challenges.

Publications

Significance of Time-Series Consistency in Evaluating Machine Learning Models for Gap-Filling Multi-Level Very Tall Tower Data
Published Year: 2025
Cited by: 5

Environmental factors contributing to variations in CO2 flux over a barley–rice double‑cropping paddy field in the Korean Peninsula
Published Year: 2022
Cited by: 12

Numerical simulation of atmospheric CO2 concentration and flux over the Korean Peninsula using WRF-VPRM model during Korus-AQ 2016 campaign
Published Year: 2020
Cited by: 20

CO2 transport, variability, and budget over the southern California air basin using the high-resolution WRF-VPRM model during the CalNex 2010 campaign
Published Year: 2018
Cited by: 30

Anthropogenic and biogenic features of long-term measured CO2 flux in north downtown Houston, Texas
Published Year: 2016
Cited by: 24

Conclusion

Dr. Changhyoun Park’s academic and research journey reflects a robust commitment to advancing atmospheric and environmental sciences. His diverse roles across academia, research, and education have positioned him as a leader in micrometeorological modeling and AI applications in climate science. With numerous peer-reviewed publications and funded research projects, he continues to contribute significantly to understanding biosphere-atmosphere interactions, offering scientific insights that support sustainable environmental policy and technological innovation in atmospheric monitoring.

Shinoy Vengaramkode Bhaskaran | Big Data Analytics | Best Researcher Award

Mr. Shinoy Vengaramkode Bhaskaran | Big Data Analytics | Best Researcher Award

Senior Big Data Engineering Manager, Zoom Communications Inc, United States

Shinoy Bhaskaran is a seasoned leader with a strong background in data engineering, platform development, and team leadership. With extensive experience in building large-scale data platforms and driving data strategy, Shinoy specializes in real-time and batch processing using cutting-edge technologies like PySpark, Snowflake, and AWS. He has demonstrated expertise in managing diverse teams globally, fostering high-performance environments, and delivering impactful data-driven solutions across industries. As a Senior Engineering Manager at Zoom Video Communications, he oversees a team of 20+ engineers and has successfully managed data pipelines that process billions of transactions daily. His leadership approach emphasizes mentorship, team growth, and creating inclusive, innovative work cultures. 🌟👨‍💻

Publication Profile

ORCID

Education:

Shinoy Bhaskaran holds a degree in Engineering, but specific details about his educational qualifications are not provided in the available information. His career journey reflects continuous learning and applying new technologies, with an emphasis on real-world problem solving in the data engineering field. 🎓

Experience:

Shinoy’s career spans over a decade, with significant experience in managing data engineering teams and developing robust data platforms. He has worked at prominent organizations such as Zoom Video Communications, GoTo Inc., LogMeIn, Citrix Systems, and Wipro Technologies. In his current role, he manages high-volume data pipelines, focusing on data quality, storage, cost, security, and compliance. He also excels in driving cross-functional collaborations and mentoring teams to achieve high levels of success in data engineering, governance, and analytics. 💼

Awards and Honors:

Shinoy Bhaskaran has been recognized for his excellence in leadership, innovation, and data-driven impact. His work in building and managing large-scale data platforms has earned him respect in the tech community, though specific award details are not provided in the available information. 🎖️

Research Focus:

Shinoy’s research and technical expertise are centered around big data platforms, real-time analytics, cloud computing, data engineering, and data governance. He is particularly interested in developing scalable data solutions for enterprises, ensuring compliance with regulations like GDPR and SOX, and enhancing the decision-making process through data-driven insights. His research spans various domains, including AI-enhanced predictive maintenance, big data analytics for secure banking, and cost optimization strategies for businesses using generative AI. 🔍📊

Conclusion:

Shinoy Bhaskaran’s career is marked by his passion for leadership, technical expertise in data platforms, and commitment to creating high-performing teams. His ability to navigate complex data challenges and deliver impactful solutions has made him a recognized leader in the field of data engineering. 🌟

Publications:

  1. Gen-Optimizer: A Generative AI Framework for Strategic Business Cost Optimization
    Published Year: 2025
    Journal: Computers
    DOI: 10.3390/computers14020059
    Cited by: 0

  2. BankNet: Real-Time Big Data Analytics for Secure Internet Banking
    Published Year: 2025
    Journal: Big Data and Cognitive Computing
    DOI: 10.3390/bdcc9020024
    Cited by: 0

  3. Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework
    Published Year: 2024
    Journal: Sensors
    DOI: 10.3390/s24247918
    Cited by: 0