Saravit Soeng

About

Research Focus

• Multimodal Action Detection: Spatio-temporal modeling and vision-language reasoning for real-time abnormal human action detection (fall detection, fight identification, safety compliance)
• Computer Vision: Object detection, pose estimation, image classification, and intelligent video surveillance systems
• Vision-Language Models (VLM): Multimodal AI combining visual and language understanding for scene reasoning and document intelligence
• Large Language Models (LLM): Applied LLM systems including OCR-based document extraction, NLP pipelines, and prompt-driven solutions
• IoT & Big Data Infrastructure: End-to-end IoT data pipelines for industrial sensor data collection, processing, storage, and monitoring using Spark and Kafka
• Applied AI Systems: Address verification with geocoding and deep learning, blockchain-based voting systems, and real-world AI deployment

Education

• Ph.D. in Big Data (Mar 2022 – Feb 2026)
  Chungbuk National University, South Korea
  Dissertation: "A Multimodal Framework for Real-Time Abnormal Human Action Detection Using Spatio-Temporal Modeling and Vision-Language Reasoning"
• M.S. in Big Data (Mar 2020 – Feb 2022)
  Chungbuk National University, South Korea
  Dissertation: "An Implementation of IoT End-to-end Data Pipeline for Industrial Big Data Platform"
• B.S. in Computer Science (Nov 2013 – May 2017)
  Royal University of Phnom Penh, Cambodia

Professional Experience

• 2026 – Present: Researcher, AI Convergence Lab, Chungbuk National University
• 2022 – 2026: Research Assistant (PhD), Big Data Lab, Chungbuk National University
• 2020 – 2022: Research Assistant (MSc), Big Data Lab, Chungbuk National University
• 2017 – 2020: Instructor & Developer, Korea Software HRD Center, Cambodia

Research Publications

Contact

• AI Convergence Lab, Chungbuk National University, Cheongju, South Korea
• Google Scholar
• ORCID: 0000-0001-5704-8820
• LinkedIn