About Me
I am an AI researcher and machine learning engineer with over 4 years of experience in developing machine/deep learning algorithms for real-world applications. My expertise lies in adversarial machine learning, real-world automation, worker safety, and health monitoring, with a specific focus on fatigue and muscle fatigue. I strive to leverage AI to solve complex problems and enhance safety in various domains.
Projects
Here are some notable projects:
- AI Researcher at IvWorks Company (Seoul, South Korea): Worked on identifying anomalies during the production stage of semiconductor materials using time series and vision data.
- Research Assistant at CONTIL (Chung-Ang University): Developed machine learning and deep learning algorithms for worker safety in construction, focusing on computer vision and embedded systems.
- Instructor at Kainat School System: Taught computer science and lab technician courses for grades 6-10.
Research Interests
My research interests include:
- Adversarial Machine Learning
- Automation in Real-World Scenarios
- Worker Safety and Health Monitoring
- Central Fatigue and Muscle Fatigue Monitoring
- AI-Driven Solutions for Complex Problems
For more detailed information, you can visit my Google Scholar profile.
Publications
Here are some selected publications:
- Rotation Error Detection of Gallium Nitride (GaN) Substrate in MBE utilizing Ensemble Learning - Published in ACS Publisher (Impact Factor: 4.1)
- Fall Prevention From Ladders Utilizing a Deep Learning-Based Height Assessment Method - Published in IEEE Access (Impact Factor: 4.34)
- A Novel Deep Learning-based Mitosis Recognition Approach for Uterine Leiomyosarcoma Histopathology - Published in Cancer Journal (Impact Factor: 7.6)
- Tag and IoT-based Safety Hook Monitoring for Prevention of Falls from Height - Published in Automation in Construction (Impact Factor: 11.45)
- Fall Prevention from Scaffolding Using Computer Vision and IoT-Based Monitoring - Published in Journal of Construction Engineering Management (Impact Factor: 3.9)
Conference Papers
Here are some selected conference papers:
- Framework for Immersive Embodied Interaction Development in Construction Education and Training - CSCE Niagara Falls, Canada, 2024
- Artificial Intelligence-based Safety Helmet Recognition on Embedded Devices to Enhance Safety Monitoring Process - Authors: Sharjeel Anjum, Syed Farhan Alam, Rabia Khalid, Chansik Park. IEEE International Conference On Artificial Intelligence In Engineering And Technology, 2022 (Published).
- A Pull-Reporting Approach for Floor Opening Detection using Deep-Learning on Embedded Devices - Authors: Sharjeel Anjum, Rabia Khalid, M.Khan, N.Khan, Chansik Park. 38th International Symposium on Automation and Robotics in Construction, 2022 (Published).
- A Worker-Driven Approach for Opening Detection by Integrating Computer Vision and Built-in Inertia Sensors on Embedded Devices - Authors: Sharjeel Anjum, Muhammad Sibtain, Rabia Khalid, M.Khan, and Chansik Park*. 12th International Conference on Construction and Project Management, 2022 (Published)
- Fall and Normal Activity Classification via Multiple Wearable Sensors - Authors: Rabia Khalid, Sharjeel Anjum, Chansik Park. IEEE International Conference On Artificial Intelligence In Engineering And Technology, 2022 (Published).
- IMU-based Smart Safety Hook for Fall Prevention at Construction Sites - Authors: M.Khan, Rabia Khalid, Sharjeel Anjum, N.Khan, Chansik Park. TENSYMP Conference: 10th IEEE Region Symposium, 2022 (Published).
- A Deep Learning based Detection of Fall Potent for Lone Construction Worker - Authors: N.Khan, Sharjeel Anjum, Rabia Khalid, Junsung Park, Chansik Park. 38th International Symposium on Automation and Robotics in Construction, 2022 (Published).
- Image Recognition and Blockchain Network Integrated Construction Site Safety Management System Framework - Authors: Dohyeong Kim, Jaehun Yang, Sharjeel Anjum, and Doyeop Lee. 12th International Conference on Construction and Project Management, 2022 (Published)
- AprilTag and Stereo Visual Inertial Odometry (A-SVIO) based Mobile Assests Localization at Indoor Construction Site - Authors: Rabia Khalid, M.Khan, Sharjeel Anjum, Junsung Park, Doyep Lee, and Chansik Park*. ICCPM Conference: 12th International Conference on Construction and Project Management, 2022 (Published)