Assist. Prof. Dr. Lechen Li | Signal Processing | Best Researcher Award

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Assist. Prof. Dr. Lechen Li | Signal Processing | Best Researcher Award 

Assist. Prof. Dr. Lechen Li, Hohai University, China

Lechen Li is an Assistant Professor at the College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, China. He received his Ph.D. in Engineering Mechanics from Columbia University in 2023, where his research focused on smart grid development, data-driven system control, and computational structural dynamics. Prior to that, he earned an M.S. in Data Science from Columbia University, supported by the Robert A.W. and Christine S. Carleton Scholarship, and a B.S. in Engineering Mechanics from Sichuan University, where he won the First Prize in the Zhou Peiyuan National Mechanics Modeling Contest. His current research spans infrastructure intelligent monitoring, data-driven seepage analysis, computational dynamics, and renewable energy optimization. Dr. Li has presented award-winning work at major international conferences such as the 8th World Conference on Structural Control and Monitoring and has collaborated on interdisciplinary projects involving smart electricity networks and structural health monitoring.

Professional Profile:

SCOPUS

🏅 Summary of Suitability for Best Researcher Award

Dr. Lechen Li is a highly promising and accomplished early-career researcher whose interdisciplinary work spans Engineering Mechanics, Data Science, and Infrastructure Monitoring. His exceptional academic background, innovative research in intelligent structural control, and impactful contributions to renewable energy systems make him an excellent candidate for the Best Researcher Award.

🎓 Education

  • Ph.D. in Engineering Mechanics
    Columbia University, USA (09/2019 – 06/2023)
    🔍 Research: Smart Grid, Structural Dynamics, Signal Processing
    📊 GPA: 3.889/4.0

  • M.S. in Data Science
    Columbia University, USA (09/2018 – 08/2019)
    💡 Focus: Neural Networks, Dynamical Systems
    📚 Robert A.W. and Christine S. Carleton Scholarship
    📊 GPA: 3.917/4.0

  • B.S. in Engineering Mechanics
    Sichuan University, China (09/2014 – 06/2018)
    🧠 Strong foundation in Mechanics & Modelling
    📊 GPA: 3.6/4.0
    🥇 First Prize in Zhou Peiyuan National Mechanics Modeling Contest (2017)
    🏅 First Prize Scholarship (Twice between 2014–2016)

🧑‍🏫 Current Position

  • Assistant Professor
    College of Water Conservancy and Hydropower Engineering, Hohai University, China (06/2023 – Present)
    🌊 Research: Infrastructure Intelligent Monitoring, Seepage Control, Computational Dynamics, Renewable Energy.

🧪 Research & Projects

  • Structural Control & Health Monitoring
    Columbia University (2021 – 2023)
    🤖 Developed a Generalized Auto-Encoder (GAE) for damage detection
    🎙️ Presented at 8WCSCM, awarded Best Conference Paper (2022) 🏆

  • Smart Grid for Residential Buildings
    Columbia University (2019 – 2020)
    ⚡ Built ConvLSTM neural network for intelligent load control
    📈 Improved forecasting accuracy by 16%

💼 Industry Experience

  • Data Research Analyst
    CICT, Colombo, Sri Lanka (12/2017 – 03/2018)
    🚢 Applied ML for port logistics & road paving optimization
    🔁 Designed reinforcement learning system for transportation planning

  • CAE Analyst
    National Institute of Water, Energy & Transportation, China (06/2016 – 08/2016)
    🏗️ Simulated pile-soil stress using XFEM
    🔍 Assessed 70% lateral pressure effects on platform-supported pile groups

🏅 Achievements, Awards & Honors

  • 🥇 Best Conference Paper Award, 8WCSCM (2022)

  • 📚 Robert A.W. and Christine S. Carleton Scholarship (2018)

  • 🧠 First Prize, Zhou Peiyuan National Mechanics Modeling Contest (2017)

  • 🎖️ Sichuan University First Prize Scholarship (2014–2016, twice)

Publication Top Notes:

Experimental Study on Dynamic Characteristics of Coarse-Grained Materials and Its Application on Numerical Analysis for Permanent Deformation of Rockfll Dams

Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award

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Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award 

Dr. Longbin Jin, Konkuk University, South Korea

Longbin Jin, is a Ph.D. candidate in Computer Science at Konkuk University, Korea, with an expected graduation in February 2025. His research focuses on adaptive visual prompting for video action recognition in vision-language models under the guidance of Professor Eun Yi Kim. He holds a Master’s degree in Smart ICT Convergence and a Bachelor’s degree in Mechanical Engineering & Automation from Shanghai University, China. Throughout his academic career, Longbin has received numerous accolades, including winning the ICASSP 2023 SPGC Challenge and multiple Excellence and Encouragement Prizes at the Korea Software Congress. Currently, he serves as an AI Researcher at Voinosis in Seoul, where he develops AI models for early detection of hearing loss and cognitive impairment in the elderly. He is also an instructor at Konkuk University, teaching courses on Artificial Intelligence, Computer Vision, and Machine Learning. His project experience includes collaborations on medical imaging and virtual reality, demonstrating his expertise in applying AI technologies across diverse fields. Longbin is proficient in English, Chinese, and Korean, reflecting his international background and commitment to advancing technology in healthcare and education.

Professional Profile:

GOOGLE SCHOLAR

Research for Community Impact Award: Longbin Jin’s Suitability

Longbin Jin is a highly qualified candidate for the Research for Community Impact Award due to his significant contributions in the fields of artificial intelligence and healthcare, particularly in projects that directly benefit the community.

📚 Education

  • Ph.D. in Computer Science
    Konkuk University, Korea
    Expected: February 2025
    Thesis: Adaptive Visual Prompting for Video Action Recognition in Vision-Language Models
    Advisor: Prof. Eun Yi Kim
  • M.S. in Smart ICT Convergence
    Konkuk University, Korea
    Graduated: August 2020
    Thesis: E-EmoticonNet: EEG-based Emotion Recognition with Context Information
    Advisor: Prof. Eun Yi Kim
  • B.S. in Mechanical Engineering & Automation
    Shanghai University, China
    Graduated: August 2018

💼 Work Experience

  • AI Researcher
    Voinosis, Seoul, Korea
    December 2022 – Present

    • Researcher on AI models for early detection of hearing loss and cognitive impairment based on voice analysis for the elderly (VoiceCheck & BrainGuardDoctor Apps).
  • Instructor
    Konkuk University, Seoul, Korea
    March 2022 – Present

    • Teaching courses on Computer Vision, Artificial Intelligence, and Machine Learning.
  • AI Engineer
    Lulla, Seoul, Korea
    October 2022 – November 2022

    • Main researcher for an AI model for a child face-matching system to assist kindergarten teachers (Lulla App).

🏆 Achievements, Awards, and Honors

  • Winner of ICASSP 2023 SPGC Challenge: Multilingual Alzheimer’s Dementia Recognition through Spontaneous Speech (First Author) 🥇
  • Excellence Prize, Korea Software Congress 2023 🥇
  • Encouragement Prize, ACM Student Research Competition, Computer Human Interaction 2020 (First Author) 🎖️
  • Excellence Prize, Korea Software Congress 2019 (First Author) 🏅
  • Encouragement Prize, Korea Software Congress 2019 (First Author) 🎖️
  • Excellent Presentation, International Conference on Culture Technology 2018 🌟

Publication Top Notes:

Interpretable Cross-Subject EEG-Based Emotion Recognition Using Channel-Wise Features†

CITED:29

Consen: Complementary and simultaneous ensemble for alzheimer’s disease detection and mmse score prediction

CITED:15

Eeg-based user identification using channel-wise features

CITED:7

E-EmotiConNet: EEG-based emotion recognition with context information

CITED:2

Emotion Recognition based BCI using Channel-wise Features

CITED:1

 

Mr. Qiang Yu | Signal Theory Award | Best Researcher Award

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Mr. Qiang Yu | Signal Theory Award | Best Researcher Award

Mr. Qiang Yu, Shanxi Normal University, China

Dr. Qiang Yu is a distinguished professor in the Department of Mathematical Sciences at Shanxi Normal University, China. With a solid academic foundation, Dr. Yu obtained his B.S. in Mathematics Education from Shi He Zi University in 2003, followed by an M.S. in Applied Mathematics and a Ph.D. in Basic Mathematics from Shaanxi Normal University in 2009 and 2014, respectively. His doctoral research, under the guidance of Professor Baowei Wu, focused on nonlinear systems, stability, stabilization, and control. Dr. Yu’s professional career began as a mathematics teacher at Fukang No.1 Senior School in Xinjiang. He then advanced to academic positions at Heng Shui University and Shaanxi Normal University, where he steadily rose through the ranks from Lecturer to Associate Professor, and ultimately to Professor in December 2023. He also served as a visiting professor at the Shibaura Institute of Technology in Japan from 2019 to 2020, collaborating with Prof. Guisheng Zhai.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award

Dr. Qiang Yu demonstrates an exceptional academic and professional background that makes him highly suitable for the Best Researcher Award. His educational foundation in mathematics (B.S., M.S., and Ph.D. from Shi He Zi University and Shaanxi Normal University) underpins his rigorous work in complex areas like control theory, dynamical systems, and nonlinear systems. He has further specialized in switched systems, robust control, and time-delay systems—highly relevant research areas with widespread applications in engineering and mathematics.

📚 Academic Background

  • 🎓 B.S. in Mathematics Education (1999-2003) – Shi He Zi University
  • 🎓 M.S. in Applied Mathematics (2006-2009) – Shaanxi Normal University
  • 🎓 Ph.D. in Basic Mathematics (2011-2014) – Shaanxi Normal University
    • 📑 Advisor: Professor Baowei Wu
    • 🔍 Research Theme: Nonlinear Systems, Stability, Stabilization, and Control

🏫 Professional Experience

  • 🧑‍🏫 Math Teacher – Fukang No.1 Senior School, Xinjiang (2003-2006)
  • 📈 Lecturer – Heng Shui University, Hebei (2009-2011)
  • 🎓 Lecturer, Associate Professor, and Professor – Shaanxi Normal University, Shanxi (2014-present)
  • 🌏 Visiting Professor – Shibaura Institute of Technology, Saitama, Japan (2019-2020)

🔬 Research Interests

  • 🛠️ Switched Systems
  • 📏 Robust Control
  • ⏳ Time-Delay Systems
  • 📊 Control Theory and Engineering
  • 🧮 Applied Mathematics
  • 🔄 Dynamical Systems
  • 🤖 Neural Networks

🌐 Professional Memberships and Activities

  • 🔍 Reviewer for Mathematical Reviews
  • 🏅 Member, IEEE Control Systems Society
  • 🧩 Member, Chinese Mathematical Society
  • 🤖 Member, Chinese Association of Automation
  • 🇨🇳 Member, Society of Industry and Applied Mathematics of China
  • ✒️ Editorial Board Member, American Journal of Applied Mathematics (Since 2020)

🏆 Honors and Awards

  • 🥇 First Prize Gardener’s Scholarship, Shaanxi Normal University (2013)
  • 🥈 Second Prize in National College Student Academic Competitions (2013)
  • 🎖️ National Scholarship for Doctoral Students, Ministry of Education of China (2013)
  • 🏅 Excellent Postgraduate Student Award, Shaanxi Normal University (2014)
  • 🥉 Third Prize in Teachers’ Skills Competition, Shanxi Normal University (2015)
  • 🥈 Second Prize in National Mathematics Micro Course Design Competition (2016)
  • 🌟 Advanced Individual for Educational Excellence, Shanxi Normal University (2017)
  • 🥉 Third Prize for Excellent Academic Paper, Shanxi Science and Technology Department (2018)
  • 🥇 First Prize Science and Technology Award, Shaanxi Higher Education Institutions (2019)
  • 🏆 Second Prize of the Natural Science Award, Shaanxi Science and Technology (2022)

Publication top Notes:

Sampled-data synchronization of delayed multi-agent networks and its application to coupled circuit

CITED:62

Analysis of mixed convection flow in an inclined lid-driven enclosure with Buongiorno’s nanofluid model

CITED:56

Stability analysis for discrete-time switched systems with stable and unstable modes based on a weighted average dwell time approach

CITED:45

Coiflets solutions for Föppl-von Kármán equations governing large deflection of a thin flat plate by a novel wavelet-homotopy approach

CITED:39

Robust stability analysis of uncertain switched linear systems with unstable subsystems

CITED:38

Stability analysis of discrete-time switched linear systems with unstable subsystems

CITED:36

Dr. B. Omkar Lakshmi Jagan | Signal Estimation Award | Best Researcher Award

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Dr. B. Omkar Lakshmi Jagan | Signal Estimation Award | Best Researcher Award 

Dr. B. Omkar Lakshmi Jagan, Vignan’s Institute of Information Technology, India

Dr. Banana Omkar Lakshmi Jagan is an accomplished academic and researcher in the field of Statistical Signal Processing, with a Ph.D. from Koneru Lakshmaiah Education Foundation. Currently serving as an Assistant Professor in the Department of Computer Science Engineering at Vignan’s Institute of Information Technology, Dr. Jagan has a diverse teaching and research background. His previous roles include Assistant Professor in Artificial Intelligence and Machine Learning at Malla Reddy University and research positions with the NRB-DRDO projects focused on submarine target motion analysis and performance evaluation of algorithms. With over five years of research experience and nearly two years in teaching, Dr. Jagan has specialized in Deep Learning, Machine Learning, Linux Programming, and IoT. He has also earned additional certifications in Deep Learning and IoT from NPTEL. His commitment to both academic excellence and innovative research drives his career in exploring advanced technologies and methodologies in his field.

Professional Profile:

Suitability for the Best Researcher Award:

Dr. Banana Omkar Lakshmi Jagan has demonstrated significant achievements in research, teaching, and contributions to multiple domains, particularly in Statistical Signal Processing, Machine Learning, Deep Learning, and Target Tracking. Based on his extensive academic background, research projects, and publications, he is a strong candidate for the Best Researcher Award.

Education 

  • Ph.D. in Statistical Signal Processing
    2023
    Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh
  • M.Tech. in Power Systems
    2016
    Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh
  • B.Tech. in Electrical and Electronics Engineering
    2014
    Sri Sivani College of Engineering, JNTU Kakinada, Andhra Pradesh
  • Intermediate (M.P.C)
    2008
    Board of Intermediate Education, Andhra Pradesh
  • Xth Grade
    2006
    Council for the Indian School Examinations, Delhi

Work Experience

  1. Assistant Professor
    Department of Computer Science Engineering
    Vignan’s Institute of Information Technology (A), Duvvada, Visakhapatnam, Andhra Pradesh, India
    May 22, 2024 – Present
  2. Assistant Professor
    Department of Artificial Intelligence and Machine Learning, Department of Computer Science Engineering
    School of Engineering, Malla Reddy University, Hyderabad, Telangana, India
    December 28, 2022 – May 22, 2024
  3. Research Associate (RA)
    NSTL-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 17, 2022 – December 27, 2022
    Project Title: Performance Evaluation of all TMA Algorithms for Bot & Calculation of MLA & SOA for Identified Zigging Targets
  4. Senior Research Fellow (SRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 9, 2021 – January 8, 2022
    Project Title: State of Art Submarine Target Motion Analysis
  5. Junior Research Fellow (JRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 9, 2019 – July 8, 2021
    Project Title: State of Art Submarine Target Motion Analysis
  6. Junior Research Fellow (JRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 12, 2016 – July 11, 2018
    Project Title: Advance Submarine Target Motion Analysis

Publication top Notes:

CITED:56
CITED:26
CITED:21
CITED:18
CITED:13
CITED:11

Dr. Zhengjia Xu | Signal Analysis Award | Best Researcher Award

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Dr. Zhengjia Xu | Signal Analysis Award | Best Researcher Award

Dr. Zhengjia Xu, Cranfield University, United Kingdom

Dr. Zhengjia Xu is an accomplished Electronic and Embedded Software Engineer with a rich blend of academic and industrial experience. He holds a Ph.D. in Aerospace from Cranfield University, where his research focused on cognitive communication and intelligent DSP for drone applications. Dr. Xu has a strong track record of over 25 peer-reviewed publications, including influential journal articles and conference papers in fields such as intelligent signal processing and aerospace engineering. Currently, he serves as a Research Fellow at Cranfield University, specializing in position, navigation, and timing systems, and has led several high-profile projects funded by ESA and EPSRC. His prior roles include Senior RF Engineer at Drone Defense Services Ltd, where he made significant advancements in passive RF radar and SDR-based receivers, and Electronic and Embedded Software Engineer at ASH Wireless (Captec LTD), where he developed advanced NB-IoT products and embedded firmware.

Professional Profile:

Summary of Suitability for the Best Researcher Award

Zhengjia Xu has a comprehensive technical and research background, demonstrating expertise in both industrial and academic settings. His experience spans a range of areas including embedded software development, digital system design, RF analysis, and intelligent signal processing.

Education

Ph.D. in Aerospace Engineering
Cranfield University, Cranfield, UK
September 2017 – March 2021

  • Research Area: Cognitive communication, intelligent DSP, drone communication
  • Thesis: “Cognitive Communication for UAV Applications”
  • Proposed a DSP algorithm enabled by deep learning for RF fingerprint identification, simulated air-to-ground communication performance, and proposed system architectures for UAV communications.

M.Sc. in Vehicle Operation Design
Nanjing University of Aeronautics and Astronautics, Nanjing, China
September 2014 – June 2017

  • Research Area: Aircraft modeling and control, fault-tolerant control
  • Simulated aircraft aerodynamic models, developed aircraft control algorithms, and analyzed real flight data. Involved in PCB layout design and the development of flight simulators.

Bachelor in Electrical and Electronics Engineering
Nanjing University of Aeronautics and Astronautics, Nanjing, China
September 2010 – June 2014

  • Thesis: “Research on Stability and Control of Quadratic Aircraft Based on STM32F407”
  • Designed PID-based flight control software on a self-designed PCB board with STM32 MCU.

Work Experience

Research Fellow in Position, Navigation, and Timing
Cranfield University, Bedford, UK
March 2023 – Present

  • Managed projects with stakeholders including Telespazio – Thales UK, European Space Agency, and others.
  • Co-supervised over 10 MSc and PhD student projects.
  • Main researcher for two ESA-funded projects and one EPSRC-funded 6G project.
  • Delivered lectures and developed course materials for 13 hours across four modules.

Senior RF Engineer
Drone Defense Services Ltd, Retford, UK
March 2022 – March 2023

  • Developed passive RF radar products, including software refactoring and hardware integration.
  • Improved radar detection range significantly and led the design of an SDR-based OFDM receiver.
  • Proficient in SDR developments and GPU platform optimization.

Electronic and Embedded Software Engineer
ASH Wireless (Captec LTD), Southampton, UK
March 2021 – March 2022

  • Developed an NB-IoT product for air-to-ground communication.
  • Customized IoT protocol suite and performed schematic design and RF validation.
  • Experienced in STM ARM Cortex-based embedded application developments.

Volunteer, IET Aerospace TN Committee
Institution of Engineering and Technology (IET)
September 2022 – Present

  • Participated in strategic planning and board meetings for the aerospace technical network.

Publication top Notes:

CITED:15
CITED:13
CITED:12
CITED:8
CITED:8

Mr. Lin Li | Compressive Sensing Award | Best Innovation Award

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Mr. Lin Li | Compressive Sensing Award | Best Innovation Award

Mr. Lin Li, Chengdu University of Technology, China

Li Lin received his M.S. degree in Educational Technology from Sichuan Normal University in Chengdu, China, in 2011. He is currently pursuing a Ph.D. in Earth Exploration and Information Technology at the same institution. His research interests focus on machine learning theory and 3D point cloud processes. From July 2011 to July 2019, Li Lin worked as a Senior Engineer specializing in production design at ThinkGeo (US) Science and Technology Co., Ltd. in Chengdu, Sichuan. With a strong background in computer science, Li Lin continues to contribute to the fields of technology and research.

Professional Profile:

 

Summary of Suitability for Best Innovation Award:

Li Lin’s background and research accomplishments demonstrate significant expertise and innovation in the field of 3D point cloud processes, particularly in machine learning and LiDAR technology. His academic journey, with an M.S. degree in educational technology and current Ph.D. studies in Earth exploration and information technology, shows his commitment to advancing technological solutions in a complex and emerging area. His research focuses on applying machine learning theory to 3D point cloud processing, which is crucial for various applications like geospatial analysis and environmental monitoring.

Education:

  • Master’s Degree in Educational Technology
    • Institution: Sichuan Normal University, Chengdu, China
    • Duration: September 1, 2008, to July 1, 2011
  • Ph.D. in Earth Exploration and Information Technology (Pursuing)
    • Institution: Sichuan Normal University, Chengdu, China
    • Current Status: Ongoing

Work Experience:

  • Senior Engineer (Production Design)
    • Company: ThinkGeo (US) Science and Technology Co., Ltd., Chengdu, Sichuan, China
    • Duration: July 1, 2011, to July 3, 2019

Research Interests:

  • Machine Learning Theory
  • 3D Point Cloud Processes

This outlines Li Lin’s career trajectory and expertise in both education and industry

Publication top Notes:

Compressing and Recovering Short-Range MEMS-Based LiDAR Point Clouds Based on Adaptive Clustered Compressive Sensing and Application to 3D Rock Fragment Surface Point Clouds

 

Assist Prof Dr. Hwa-Dong Liu | Signal Processing | Best Researcher Award

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Assist Prof Dr. Hwa-Dong Liu | Signal Processing | Best Researcher Award

Assist Prof Dr. Hwa-Dong Liu, Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taiwan

Hwa-Dong Liu is an Assistant Professor at National Taiwan Normal University (NTNU) in Taipei, Taiwan, specializing in power electronics, microcontrollers, rail vehicle power systems, and solar power systems. He holds a Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST). His research interests include the development of advanced power converters, control strategies for renewable energy systems, and innovative solutions for electric vehicle charging. Dr. Liu has authored numerous papers in reputable journals, with a focus on improving the efficiency and performance of power electronic systems and renewable energy technologies. His recent work includes contributions to energy management systems, high-gain boost converters, and novel MPPT algorithms for solar power generation.

Professional Profile:

Summary of Suitability for Best Researcher Award 

Hwa-Dong Liu has expertise in several cutting-edge fields including power electronics, microcontrollers, rail vehicle power systems, and solar power systems. This diversity indicates a broad impact on multiple important areas of research.

Education

  • Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST).

Work Experience

  • Assistant Professor at National Taiwan Normal University (NTNU).

Expertise

  1. Power Electronics
  2. Microcontroller
  3. Rail Vehicle Power Systems
  4. Solar Power Systems

Publication top Notes:

An improved solar step-up power converter for next-generation electric vehicle charging

Hybrid Management Strategy for Outsourcing Electromechanical Maintenance and Selecting Contractors in Taipei MRT

An Improved High Gain Continuous Input Current Quadratic Boost Converter for Next-Generation Sustainable Energy Application

Novel MPPT algorithm based on honey bees foraging characteristics for solar power generation systems

High-Voltage Autonomous Current-Fed Push-Pull Converter with Wireless Communication Applied to X-Ray Generation

 

 

 

Mr. Yeonjae Park | Signal Cleaning Award | Best Scholar Award

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Mr. Yeonjae Park | Signal Cleaning Award | Best Scholar Award

Mr. Yeonjae Park, The Graduate School of Yonsei University, South Korea

Yeonjae Park is a Master’s student at Yonsei University in the Department of Medical Informatics and Biostatistics, under the guidance of Professor Dae Ryong Kang. With a strong foundation in Computer and Telecommunication Engineering as well as Information and Statistics, Park obtained dual B.S. degrees from Yonsei University, where they were mentored by Professors Cho Young-rae and Na Seongyong. Their research interests span machine learning, deep learning, generative models, multi-modal data analysis, and time series forecasting. Park has gained valuable research experience through various positions, including as a researcher intern at the Artificial Intelligence-Information Retrieval Lab, a researcher at the Applied Data Science Lab, and their current role at the National Health BigData Clinical Research Institute. Their projects encompass a range of topics, from text extraction and OCR recognition to complex analyses in genomics, disease correlations, and the effectiveness of medical treatments.

Professional Profile:

Summary of Suitability for Best Scholar Award:

Yeonjae Park has a strong academic foundation, holding dual Bachelor’s degrees in Computer and Telecommunication Engineering and Information and Statistics from Yonsei University, one of South Korea’s most prestigious institutions. Currently, Yeonjae is pursuing a Master’s degree in Medical Informatics and Biostatistics at the same university, under the guidance of a notable advisor, Dae Ryong Kang.

Education 📚

  • Samseon Middle School, Seoul, Korea (Mar. 2010 ~ Jul. 2010)
  • SungSan Middle School, Seoul, Korea (Jul. 2010 ~ Feb. 2013)
  • Kwangsung High School, Seoul, Korea (Mar. 2013 ~ Feb. 2016)
  • Yonsei University, Department of Computer and Telecommunication Engineering 🖥️ (Mar. 2016 ~ Aug. 2021)
    • B.S. in Computer and Telecommunication Engineering
    • Advisor: Prof. Cho Young-rae
  • Yonsei University, Department of Information and Statistics 📊 (Feb. 2016 ~ Aug. 2021)
    • B.S. in Information and Statistics
    • Advisor: Prof. Na Seongyong
  • Yonsei University, Department of Medical Informatics and Biostatistics 🧬 (Aug. 2021 ~ Present)
    • Master Student
    • Advisor: Prof. Dae Ryong Kang

Research Interests 🔍

  • Machine Learning / Deep Learning 🤖
  • Generative Models 🌀
  • Multi Modal 🧠
  • Time Series Forecasting ⏳

Research Experiences 💼

  • Researcher Intern at Artificial Intelligence-Information Retrieval Lab, Yonsei University, Korea (May. 2019 ~ Apr. 2020)
  • Researcher at Applied Data Science Lab, Yonsei University, Korea (May. 2020 ~ Jan. 2021)
  • Researcher at National Health BigData Clinical Research Institute, Korea (Jan. 2021 ~ Present)

 

Publication top Notes:

Development and Validation of a Real-Time Service Model for Noise Removal and Arrhythmia Classification Using Electrocardiogram Signals

Intracardiac Echocardiogram: Feasibility, Efficacy, and Safety for Guidance of Transcatheter Multiple Atrial Septal Defects Closure