Dr. Yongho Jeong | Computer vision | Best Researcher Award

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Dr. Yongho Jeong | Computer vision | Best Researcher AwardΒ 

Dr. Yongho Jeong, Konkuk University, South Korea

Dr. Yongho Jeong is a physicist specializing in experimental particle physics, high-energy physics, and AI-driven data analysis. He earned his Ph.D. in Physics from Sungkyunkwan University, Korea, in 2022 under the supervision of Prof. YongIl Choi, focusing on the search for R-parity violating supersymmetry in proton-proton collisions at √s = 13 TeV using the CMS detector. He completed his B.S. in Physics from Soonchunhyang University in 2013. Dr. Jeong has held multiple postdoctoral positions, including at the University of Seoul, where he worked on Gas Electron Multiplier (GEM) detector aging tests, and at the Korea Astronomy and Space Science Institute (KASI), where he contributed to quantum noise reduction for future gravitational wave detectors. He has also been involved in AI software development at Mustree Company and is set to join Konkuk University as a postdoctoral researcher in 2024, focusing on 3D point cloud data analysis. His extensive research experience includes collaborations with CERN on the GEM Detector Upgrade Project for the CMS experiment, where he worked on quality control, chamber assembly, and detector performance studies. His expertise spans detector development, high-energy physics simulations, data analysis for supersymmetry searches, and advanced AI applications in physics.

Professional Profile:

ORCID

Summary of Suitability for Community Impact AwardΒ 

Dr. Yongho Jeong is a highly deserving candidate for the Community Impact Award, given his significant contributions to experimental particle physics, AI-driven technological advancements, and quantum noise reduction for future scientific applications. His extensive research collaborations, contributions to international projects, and involvement in technology-driven community advancements make him a strong nominee for this award.

πŸ“š Education

  • Ph.D. in Physics (2014.09 – 2022.02) – Sungkyunkwan University, Suwon, Korea
    • Supervisor: YongIl Choi
    • Thesis: Search for R-parity violating supersymmetry in pp collisions at √s = 13 TeV in the CMS detector
  • B.S. in Physics (2007.03 – 2013.02) – Soonchunhyang University, Asan, Korea
    • Thesis: The Age of the Universe

πŸ’Ό Work Experience

  • Postdoctoral Researcher – KonKuk University (KU), Seoul, Korea (2024.09 – Present)

    • Integrated Analytical Models and Advanced Strategies for 3D Point Cloud Data Analysis

  • Postdoctoral Researcher – University of Seoul (UOS), Seoul, Korea (2023.11 – 2024.08)

    • Gas Electron Multiplier (GEM) Detector Aging Test
    • Production of GEM Detector Foil for the Rare Isotope Accelerator Complex (RAON) Laboratory

  • Technology Team – AI Software Development – Mustree Company, Seoul, Korea (2023.07 – 2023.10)

    • Developed AI Software for Size Measurement

  • Postdoctoral Researcher – Korea Astronomy and Space Science Institute (KASI), Daejeon, Korea (2022.05 – 2023.07)

    • Quantum Noise Reduction Technology for Future Gravitational Wave Detectors
    • Development of a 2 Β΅m Laser Squeeze System

  • Ph.D. Researcher – High Energy Physics – Korea University, Seoul, Korea (2020.01 – 2022.04)

    • Data Analysis for Supersymmetric Particles
    • Search for R-parity Violating Supersymmetry in Proton-Proton Collisions at √s = 13 TeV

  • Ph.D. Researcher – GEM Detector Upgrade Project (Phase II) – CERN, Geneva, Switzerland (2018.01 – 2019.12)

    • Quality Control (QC) of GEM Chambers in the CMS Experiment
    • QC2: Leakage Current Test
    • QC3: Gas Leak Test
    • QC4: High Voltage Test
    • GEM Chamber Assembly, Aging Tests & Discharge Probability Studies

  • Ph.D. Researcher – Experimental Particle Physics – Sungkyunkwan University, Suwon, Korea (2017.06 – 2018.02)

    • Data Analysis for ttΜ„ Inclusive Decay
    • Measurement of the Inclusive Top Quark Cross Section in Di-lepton Channels at √s = 13 TeV

  • Ph.D. Researcher – Experimental Particle Physics – University of Seoul, Seoul, Korea (2016.01 – 2017.06)

    • CMS Detector Simulation for Phase II Upgrade
    • Muon Isolation Optimization Simulation

πŸ† Achievements & Contributions

βœ… Authored numerous research papers in High-Energy Physics & Detector Technology
βœ… Significant contributions to CMS Detector R&D at CERN
βœ… Advanced AI-based measurement software for industry applications
βœ… Developed quantum noise reduction techniques for future gravitational wave detectors

πŸŽ–οΈ Awards & Honors

πŸ… Recognized Researcher in Particle Physics for contributions to Supersymmetry & CMS Experiments
πŸ… Recipient of CERN Research Fellowships for GEM Detector Upgrade & Testing
πŸ… Awarded Postdoctoral Research Positions in Multiple Leading Korean Institutions
πŸ… Contributor to the CMS Collaboration at the European Organization for Nuclear Research (CERN)

PublicationΒ Top Notes:

A Mobile LiDAR-Based Deep Learning Approach for Real-Time 3D Body Measurement

A Multi-View Integrated Ensemble for the Background Discrimination of Semi-Supervised Semantic Segmentation

Prof. Raziyeh Pourdarbani | Computer Vision Awards | Best Researcher Award

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Prof. Raziyeh Pourdarbani | Computer Vision Awards | Best Researcher AwardΒ 

Prof. Raziyeh Pourdarbani, University of Mohaghegh Ardabili, Iran

Dr. Razieh Pourdarbani is a professor in the Department of Biosystems Engineering at the Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabili, Iran. She holds a Ph.D. in Agricultural Mechanization Engineering from the University of Tabriz (2012), where her dissertation focused on sorting date fruits based on maturity stages using image processing. She also earned her M.Sc. (2009) and B.Sc. (2005) degrees in Agricultural Mechanization and Machinery Engineering, respectively, from the same university. Dr. Pourdarbani’s research specializes in precision agriculture, image processing, artificial intelligence, and machine vision. Her contributions to these fields aim to advance agricultural technologies and systems for improved efficiency and sustainability.

Professional Profile:

GOOGLE SCHOLAR

Suitability for the Research for Best Researcher Award

Razieh Pourdarbani, born on December 9, 1982, is a professor at the Department of Biosystems Engineering, University of Mohaghegh Ardabili, Iran. With a Ph.D. in Agricultural Mechanization Engineering from the University of Tabriz (2012), her dissertation on date fruit sorting using image processing laid the foundation for her expertise in precision agriculture and automation.

πŸŽ“ Education

  • Ph.D. in Agricultural Mechanization Engineering
    • Institution: University of Tabriz
    • Year: 2012
    • Dissertation: Sorting of Date Fruit Based on Maturity Stages Using Image Processing
  • M.Sc. in Agricultural Mechanization Engineering
    • Institution: University of Tabriz
    • Year: 2009
    • Thesis: Investigation on Apple Sorting Using Image Processing
  • B.Sc. in Agricultural Machinery Engineering
    • Institution: University of Tabriz
    • Year: 2005

🏒 Work Experience

  • Professor, Department of Biosystems Engineering
    • Institution: Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili
    • Role: Specializing in Precision Agriculture, Machine Vision, Image Processing, and Artificial Intelligence.

πŸ† Achievements and Honors

  • πŸŽ– Recognized Expert in Precision Agriculture and Image Processing.
  • πŸ… Pioneer in integrating Artificial Intelligence and Machine Vision in agricultural mechanization.
  • πŸ“š Published numerous influential papers in the field of agricultural engineering and biosystems.
  • 🌟 Mentored students and researchers in advanced biosystems engineering applications.

PublicationΒ Top Notes:

CITED:83
CITED:66
CITED:54
CITED:39
CITED:38
CITED:37

Ms. Maryam Moshrefizadeh | Computer Vision Awards | Best Researcher Award

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Ms. Maryam Moshrefizadeh | Computer Vision Awards | Best Researcher AwardΒ 

Ms. Maryam Moshrefizadeh, Siant Louis University, United States

Maryam Moshrefizadeh is a Ph.D. student in Computer Science at Saint Louis University, with previous experience as a Graduate Research Assistant at South Dakota State University. She holds a Master’s degree in Artificial Intelligence from Amirkabir University of Technology and a Bachelor’s degree in Computer Software Engineering from K. N. Toosi University of Technology, both in Tehran, Iran. Maryam’s research interests lie in computer vision, deep learning, and machine learning. Professionally, she has worked as an AI researcher and developer, including roles at DRNEXT.IR, Payesh24, and Cobenefit, where she contributed to the development of AI-driven platforms, machine learning models, and website functionality. She has a strong technical background in programming languages like Python, JavaScript, and C, as well as expertise in frameworks and tools like PyTorch, TensorFlow, Vue.js, and Docker. Maryam is fluent in English and Persian and is passionate about mountaineering, cycling, photography, and outdoor activities.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Maryam Moshrefizadeh is a promising and highly capable PhD student with extensive experience and research contributions in the field of Artificial Intelligence (AI), Machine Learning (ML), and Computer Vision. Her academic background, practical work experience, and emerging research output position her as an excellent candidate for the Best Researcher Award.

Education

πŸŽ“ Saint Louis University
Ph.D. | Graduate Research Assistant | Computer Science
πŸ“… Jan 2024 ‑ Dec 2028 | St. Louis, MO, USA

πŸŽ“ South Dakota State University
Ph.D. | Graduate Research Assistant | Computer Science
πŸ“… Aug 2022 ‑ Dec 2023 | Brookings, SD, USA

πŸŽ“ Amirkabir University of Technology (Polytechnic)
M.S. in Artificial Intelligence
πŸ“… Jan 2014 ‑ Sept 2017 | Tehran, Iran

πŸŽ“ K. N. Toosi University of Technology
B.S. in Computer Software Engineering
πŸ“… Sept 2009 ‑ Aug 2013 | Tehran, Iran

Work Experience

πŸ’Ό DrNext.ir | Developer and AI Researcher
πŸ“… Nov 2020 – Present
β€’ Developed prescription writing notepad allowing doctors to type or use a pen πŸ–ŠοΈ
β€’ Implemented features for appointment scheduling and clinic reception handling πŸ—“οΈ
β€’ Worked in an agile team with Kanban, Scrum, Jira, and Git πŸ”§

πŸ’Ό Payesh24 | AI Engineer
πŸ“… Nov 2017 – Jul 2020
β€’ Researched and implemented various AI algorithms and machine learning models πŸ€–
β€’ Worked with supervised and unsupervised learning algorithms such as SVM and KNN πŸ“Š

πŸ’Ό BeFine | Developer
πŸ“… Apr 2006 – Feb 2009
β€’ Developed and maintained website for diabetic products and information πŸ’»
β€’ Shared health tips and updates on diabetes 🩺

πŸ’Ό Cobenefit Developer | Remote
πŸ“… Oct 2021 – Present
β€’ Develop and maintain websites using Vue.js, ES6, HTML5, CSS3, and SASS 🌐

Research Interests

πŸ” Computer Vision | πŸ€– Deep Learning | πŸ“š Machine Learning

PublicationΒ Top Notes

EC-WAMI: Event Camera-Based Pose Optimization in Remote Sensing and Wide-Area Motion Imagery

Multimodal Fusion of Heterogeneous Representations for Anomaly Classification in Satellite Imagery