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

Mr. Adrian Barglazan | Computer Vision | Best Researcher Award

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Mr. Adrian Barglazan | Computer Vision | Best Researcher Award

Mr. Adrian Barglazan, University “Lucian Blaga” Sibiu, Romania

Adrian Barglazan is a Senior Software Engineer at Cognizant Softvision, based in Sibiu, Romania, with a strong focus on continuous learning and growth in software development. He holds a Bachelor’s and Master’s degree in Computer Science from Lucian Blaga University of Sibiu, where he is also pursuing a Ph.D. with a research focus on media forensics. With over 15 years of professional experience, Adrian has worked in various roles, including software development, team leadership, and teaching. His expertise spans Microsoft-related technologies, agile development, clean code principles, and design patterns. Throughout his career, he has contributed to projects in cloud ERP systems, pharmaceutical software, and ERP applications, working with technologies such as C#, ASP.NET, JavaScript, React, and Azure. In addition to his industry work, Adrian has been a teaching assistant at Lucian Blaga University of Sibiu since 2011, specializing in data compression and DirectX. His interests extend to computer vision and machine learning, reflecting his passion for innovative and high-quality software solutions

Professional Profile:

ORCID

Suitability for Best Researcher Award – Adrian Barglazan

Adrian Barglazan demonstrates strong expertise in software development, computer vision, and media forensics, with a balance of industry experience and academic involvement. His Ph.D. research in media forensics, combined with over a decade of teaching experience in data compression and image processing, positions him as a knowledgeable professional in his field. However, for a Best Researcher Award, factors such as high-impact publications, patents, funded research projects, and citations play a crucial role. While Adrian has valuable technical contributions, his eligibility for this award would be strengthened by more peer-reviewed research publications and recognized contributions to the scientific community. Therefore, he is a strong candidate for an innovation or industry-academic impact award but may need further academic credentials to be fully competitive for a Best Researcher Award.

πŸŽ“ Education:

  • PhD in Computer Science (2019 – Present) πŸ“–πŸ”
    Lucian Blaga University of Sibiu – Focus on Media Forensics
  • Master’s Degree in Computer Science (2009 – 2011) πŸŽ“
    Lucian Blaga University of Sibiu
  • Bachelor’s Degree in Computer Science (2005 – 2009) πŸŽ“
    University “Lucian Blaga”, Faculty of Engineering “Hermann Oberth”, Sibiu

πŸ’Ό Work Experience:

πŸ”Ή Senior Software Engineer – Cognizant Softvision (Sept 2020 – Present)
πŸ“ Sibiu, Romania

  • Focus on Microsoft-related technologies, agile development, and clean code
  • Expertise in software architecture, development, testing, and mentoring

πŸ”Ή PhD Student & Teaching Assistant – Lucian Blaga University of Sibiu (Sept 2011 – Present)
πŸ“ Sibiu County, Romania

  • Research in Media Forensics πŸ”
  • Teaching Data Compression & DirectX to 4th-year students πŸŽ“
  • Covers key algorithms like Shannon, Huffman, LZ77, JPEG, MPEG

πŸ”Ή Software Developer – Visma (Apr 2017 – Sept 2020)
πŸ“ Sibiu County, Romania

  • Senior developer in cloud ERP Single Page Application (SPA) development β˜οΈπŸ’»
  • Technologies: C#, ASP.NET MVC, Azure SQL, React, TypeScript
  • Worked with Kanban methodology, CI/CD, and cross-country teams

πŸ”Ή Developer – iQuest Technologies (Sept 2011 – Apr 2017)
πŸ“ Sibiu County, Romania

  • Lead developer in Pharma sector projects πŸ’Š
  • Software architecture, risk management, and recruitment πŸ“‹

πŸ† Achievements, Awards & Honors:

🌟 PhD Researcher in Media Forensics πŸ“ΈπŸ”¬
🌟 Senior Software Engineer with over 17 years of experience in the software industry πŸ’»
🌟 Specializes in Microsoft technologies, Agile development, and Clean Code principles ⚑
🌟 Mentor & Teacher – educating future developers on Data Compression & DirectX πŸŽ“
🌟 Experienced in cloud-based ERP systems, software architecture, and machine learning β˜οΈπŸ€–
🌟 Contributor to recruitment & technical interviews in multiple companies πŸ…

PublicationΒ Top Notes:

Wavelet Based Inpainting Detection

Enhanced Wavelet Scattering Network for Image Inpainting Detection

Lung Sounds Anomaly Detection with Respiratory Cycle Segmentation

Image Inpainting Forgery Detection: A Review

Image Inpainting Forgery Detection: A Review

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