publications / Presentations

Peer-reviewed Journal Publications
(†: Corresponding Author, #: Equal Contribution)

Park, Soyeon#, Sang Min Yang#, Gyeongho Kim#, Dong Min Kim, Dong Chan Kim, Hoon-Hee Lee, Jae Gyeong Choi, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Towards holistic machinability estimation of titanium alloy: An integrated approach with enhanced feature extraction and physics-guided deep multi-task learning." Advanced Engineering Informatics 76 (2026): 104964.

Lim, Chansung, Gyeongho Kim†, and Sunghoon Lim†. "A deep active learning framework for defect classification of wafer bin maps under noisy labels." Advanced Engineering Informatics 74 (2026): 104621.
Choi, Jae Gyeong#, Dong Chan Kim#, Dong Min Kim, Gyeongho Kim, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Supervised contrastive learning for multi-source domain generalization: Tool failure prediction in data-deficient cryogenic milling processes." Applied Soft Computing 187 (2026): 114217.
Hwang, Gahyun#, Juhyun Kim#, Jihyeok Choi#, Geonhee Han, Gyeongho Kim, and Sunghoon Lim†. “Class-imbalanced gas thermal image detection in manufacturing using thermal region masking and density-based reweighting.” Applied Soft Computing 186 (2026): 114186.
Kim, Gyeongho, Sang Min Yang, Sujin Jeon, Soyeon Park, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. “Robust tool wear prediction under novel operating conditions via physics-guided unsupervised domain adaptation.” Advanced Engineering Informatics 69 (2026): 103883.
Kim, Gyeongho, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Towards efficient data-driven fault diagnosis under low-budget scenarios via hybrid deep active learning.” Reliability Engineering & System Safety 266 (2026): 111637.
Choo, Youngjun, Sunghoon Lim, Yonghyun Kim, YeoJoon Park, Yonghoon Oh, Changyob Lee, Wonjun Yun, and Namhun Kim†."AIoT image analysis for real-time dispatching of shipyard transport devices: A focus on trailers." Expert Systems with Applications 296 (2026): 128947.
Kang, Yun Seok, Jae Gyeong Choi, Sang Min Yang, Sunghoon Lim, Dong Chan Kim†, and Hyung Wook Park†. "Artificial Intelligence Augmented Digital Twin for Improving the Machinability in a Robotic Carbon Fiber-reinforced Plastics Machining Process." Journal of Intelligent Manufacturing 37 (2026): 2259–2274.
Kim, Gyeongho, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Hyung Wook Park, and Sunghoon Lim†. “Fisher-informed continual learning for remaining useful life prediction of machining tools under varying operating conditions.” Reliability Engineering & System Safety 253 (2025): 110549.
Jeon, Sujin, Soyeon Park, Joonbum Bae, and Sunghoon Lim†. “Applying multistep classification techniques to recognize static and dynamic hand gestures in a soft sensor-embedded glove.” IEEE Sensors Journal 24, no. 19 (2024): 30668-30679.
Kim, Gyeongho#, Sang Min Yang#, Dong Min Kim, Jae Gyeong Choi, Sunghoon Lim†, and Hyung Wook Park†. "Developing a deep learning-based uncertainty-aware tool wear prediction method using smartphone sensors for the turning process of Ti-6Al-4V." Journal of Manufacturing Systems 76 (2024): 133-157.
Choi, Jae Gyeong, Dong Chan Kim, Miyoung Chung, Gyeongho Kim, Hyung Wook Park, and Sunghoon Lim†. “Accurate synthesis of sensor-to-machined-surface image generation in carbon fiber-reinforced plastic drilling.” Expert Systems with Applications 255 (2024): 124656.
Kim, Gyeongho, Jae Gyeong Choi, and Sunghoon Lim†. "Using Transformer and a Reweighting Technique to Develop a Remaining Useful Life Estimation Method for Turbofan Engines." Engineering Applications of Artificial Intelligence 133 (2024): 108475.
Kim, Gyeongho, Soyeon Park, Jae Gyeong Choi, Sang Min Yang, Hyung Wook Park, and Sunghoon Lim†. “Developing a Data-driven System for Grinding Process Parameter Optimization Using Machine Learning and Metaheuristic Algorithms.” CIRP Journal of Manufacturing Science and Technology 51 (2024): 20-35.
Choi, Jae Gyeong#, Dong Chan Kim#, Miyoung Chung#, Sunghoon Lim†, and Hyung Wook Park†. “Multimodal 1D CNN for delamination prediction in CFRP drilling process with industrial robots.” Computers & Industrial Engineering 190 (2024): 110074.
Kim, Gyeongho, Sang Min Yang, Sinwon Kim, Do Young Kim, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. "A multi-domain mixture density network for tool wear prediction under multiple machining conditions." International Journal of Production Research (2023):https://doi.org/10.1080/00207543.2023.2289076
Kim, Gyeongho#, Sang Min Yang#, Dong Min Kim, Sinwon Kim, Jae Gyeong Choi, Minjoo Ku, Sunghoon Lim†, and Hyung Wook Park†. "Bayesian-Based Uncertainty-Aware Tool-Wear Prediction Model in End-Milling Process of Titanium Alloy." Applied Soft Computing 148 (2023): 110922.
Vania, Malinda#, Bayu Adhi Tama#, Hasan Maulahela, and Sunghoon Lim†. “Recent Advances in Applying Machine Learning and Deep Learning to Detect Upper Gastrointestinal Tract Lesions.” IEEE Access 11 (2023): 66544-66567.
Kim, Gyeongho, Jae Gyeong Choi, Minjoo Ku, and Sunghoon Lim†. "Developing a semi-supervised learning and ordinal classification framework for quality level prediction in manufacturing." Computers & Industrial Engineering 181 (2023): 109286.
Tama, Bayu Adhi, Malinda Vania, Seungchul Lee†, and Sunghoon Lim†. "Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals." Artificial Intelligence Review 56 (2023): 4667-4709.
Kim, Gyeongho#, Dong-hyun Shin#, Jae Gyeong Choi, and Sunghoon Lim†. "A Deep Learning-Based Cryptocurrency Price Prediction Model That Uses On-chain Data." IEEE Access 10 (2022): 56232-56248.
Kim, Kyudong, Heena No, Kijung Park†, Hyun Woo Jeon†, and Sunghoon Lim. "Characterization of Power Demand and Energy Consumption for Fused Filament Fabrication Using CFR-PEEK." Rapid Prototyping Journal 28, no. 7 (2022): 1394-1406.
Kim, Gyeongho, and Sunghoon Lim†. "Development of an Interpretable Maritime Accident Prediction System Using Machine Learning Techniques." IEEE Access 10 (2022): 41313-41329.
Tama, Bayu Adhi#, Malinda Vania#, Iljung Kim, and Sunghoon Lim†. "An EfficientNet-based Weighted Ensemble Model for Industrial Machine Malfunction Detection Using Acoustic Signals." IEEE Access 10 (2022): 34625-34636.
Hwang, Seong Wook, and Sunghoon Lim†. “The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM.” European Journal of Industrial Engineering 16, no. 6 (2022): 1.
Chatterjee, Sujoy, and Sunghoon Lim†. "A TOPSIS-inspired ranking method using constrained crowd opinions for urban planning." Entropy 24, no. 3 (2022): 371.
Kim, Gyeongho#, Jae Gyeong Choi#, Minjoo Ku, Hyewon Cho, and Sunghoon Lim†. "A Multimodal Deep Learning-Based Fault Detection Model for a Plastic Injection Molding Process." IEEE Access 9 (2021): 132455-132467.
Tuarob, Suppawong, Poom Wettayakorn, Ponpat Phetchai, Siripong Traivijitkhun, Sunghoon Lim, Thanapon Noraset, and Tipajin Thaipisutikul†. "DAViS: A Unified Solution for Data Collection, Analyzation, and Visualization in Real-time Stock Market Prediction." Financial Innovation 7 (2021): 56.
Lim, Sunghoon†, Sun Jun Kim, YoungJae Park, and Nahyun Kwon. "A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo traffic." Expert Systems with Applications 184 (2021): 115532.
Choi, Jae Gyeong, Chan Woo Kong, Gyeongho Kim, and Sunghoon Lim†. "Car crash detection using ensemble deep learning and multimodal data from dashboard cameras." Expert Systems with Applications 183 (2021): 115400.
Tama, Bayu Adhi, and Sunghoon Lim†. "Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation." Computer Science Review 39 (2021): 100357.
Nkenyereye, Lewis, Bayu Adhi Tama, and Sunghoon Lim†. "A Stacking-based Deep Neural Network Approach for Effective Network Anomaly Detection." Computers, Materials & Continua 66, no. 2 (2021): 2217-2227.
Tama, Bayu Adhi, and Sunghoon Lim†. "A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support Systems." Mathematics 8, no. 10 (2020): 1814.
Chatterjee, Sujoy, and Sunghoon Lim†. "A Multi-objective Differential Evolutionary Method for Constrained Crowd Judgment Analysis." IEEE Access 8 (2020): 87647-87664.
Lim, Sunghoon, and Conrad S. Tucker†. "Mining Twitter data for causal links between tweets and real-world outcomes." Expert Systems with Applications: X 3 (2019): 100007.
Lim, Sunghoon, Conrad S. Tucker†, Kathryn Jablokow, and Bart Pursel. "A semantic network model for measuring engagement and performance in online learning platforms." Computer Applications in Engineering Education 26, no. 5 (2018): 1481-1492.
Tuarob, Suppawong, Sunghoon Lim, and Conrad S. Tucker†. "Automated Discovery of Product Feature Inferences within Large Scale Implicit Social Media Data." Journal of Computing and Information Science in Engineering 18, no. 2 (2018): 021017.
Lim, Sunghoon, and Conrad S. Tucker†. "Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers." Journal of Mechanical Design 139, no. 11 (2017): 111409.
Lim, Sunghoon, Conrad S. Tucker†, and Soundar Kumara. "An unsupervised machine learning model for discovering latent infectious diseases using social media data." Journal of Biomedical Informatics 66 (2017): 82-94. Lim, Sunghoon, and Conrad S. Tucker†. "A Bayesian Sampling Method for Product Feature Extraction From Large-Scale Textual Data." Journal of Mechanical Design 138, no. 6 (2016): 061403.

Peer-reviewed Journal Publications: under review
(†: Corresponding Author, #: Equal Contribution)

Jeon, Sujin#, Soyeon Park#, Gyeongho Kim, Jiyeon Cheon, and Sunghoon Lim†. "Prototype-guided tuning and reliability-aware test-time adaptation for robust optical character recognition on manufacturing equipment displays." Advanced Engineering Informatics (Under Review)
Cheon, Jiyeon, Dajeong Kam, Gyeongho Kim, and Sunghoon Lim†. "Session-Wise Feature Offset Learning for Few-Shot Class-Incremental Hand Gesture Recognition." IEEE Internet of Things Journal (Under Review)
Lim, Chansung, Gyeongho Kim†, and Sunghoon Lim†. "Open-set defect classification of wafer bin maps via multi-label evidential deep learning." Advanced Engineering Informatics (Under Review)

Peer-reviewed Conference Proceedings
(†: Corresponding Author, #: Equal Contribution)

Park, Soyeon#, Sang Min Yang#, Gyeongho Kim#, Dong Min Kim, Hoon Hee Lee, Jae Gyeong Choi, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Accurate monitoring of machining process of Ti-6Al-4V using deep multi-task learning." In 2024 International Conference on Advanced Mechatronic Systems, Institute of Electrical and Electronics Engineers (IEEE), 2024.
Choi, Jae Gyeong, and Sunghoon Lim†. "Multimodal sensor-guided diffusion model for machined surface image synthesis." In 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Ph.D. Consortium, 2024.
Kim, Gyeongho, Sang Min Yang, Sinwon Kim, Dong Min Kim, Sunghoon Lim†, and Hyung Wook Park†. “Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning.” In 2022 International Conference on Advanced Mechatronic Systems, Institute of Electrical and Electronics Engineers (IEEE), 2022.
Chatterjee, Sujoy, and Sunghoon Lim†. “A TOPSIS-based Multi-objective Model for Constrained Crowd Judgment Analysis.”, In Eighth AAAI Human Computation and Crowdsourcing (HCOMP-2020), 2020.
Lim, Sunghoon, Conrad S. Tucker†, Kathryn Jablokow, and Bart Pursel. "Quantifying the Mismatch between Course Content and Students’ Dialogue in Online Learning Environments." In ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, American Society of Mechanical Engineers (ASME), 2017. [Design Education (DEC) Technical Committee Best Paper]

International Conference Presentations
(*: Presenter, †: Corresponding Author)

Kim, Gyeongho*, Sang Min Yang, Sujin Jeon, Soyeon Park, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. “Development of a robust tool wear prediction method under novel operating conditions using deep unsupervised domain adaptation and physics-guided adjustment.” INFORMS Annual Meeting, Atlanta, Georgia, 2025.

Park, Soyeon, Sang Min Yang*, Gyeongho Kim, Dong Min Kim, Hoon Hee Lee, Jae Gyeong Choi, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Accurate monitoring of machining process of Ti-6Al-4V using deep multi-task learning." 2024 International Conference on Advanced Mechatronic Systems, Shiga, Japan, 2024.

Kim, Gyeongho*, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Hyung Wook Park, and Sunghoon Lim†. “Continual learning-based remaining useful life prediction of machining tools under varying operating conditions." INFORMS Annual Meeting, Seattle, Washington, 2024.
Choi, Jae Gyeong*, Dong Chan Kim, Miyoung Chung, Hyung Wook Park, and Sunghoon Lim†.“Sensor to Machined Surface Image Generation in CFRP Drilling." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Jeon, Sujin*, Soyeon Park, Hyewon Cho, and Sunghoon Lim†. “Hand gesture recognition without-of-distribution gesture detection using a soft sensor embedded glove." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Kim, Gyeongho*, and Sunghoon Lim†. “Development of a Deep Learning-based Uncertainty-aware Predictive Maintenance Method." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Cho, Hyewon*, Nurbolat Aimakov, Inwoo Park, Myeonghoon Choi, Yerim Kim, Geosong Na, Sunghoon Lim, and Woonggyu Jung†. "Glomerulus quantification with deep learning based on novel multi-modal label-free quantitative phase imaging from a near-infrared (Conference Presentation)." In Quantitative Phase Imaging IX, p. PC123890A. SPIE, 2023.
Kim, Gyeongho*, Sang Min Yang, Sinwon Kim, Dong Min Kim, Sunghoon Lim†, Hyung Wook Park†. “Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning.” 2022 International Conference on Advanced Mechatronic Systems, Toyama, Japan, 2022.
Ku, Minjoo*, Gyeongho Kim, and Sunghoon Lim†. “Developing a quality level prediction framework with semi-supervised learning and ordinal classification for UV lamps.” IISE Annual Conference & Expo 2022, Seattle, Washington, 2022.
Hwang, Seong Wook*, and Sunghoon Lim†. “The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM.” INFORMS Annual Meeting, Seattle, Washington, 2019.

Domestic Conference Presentations
(*: Presenter, †: Corresponding Author)

Jeon, Sujin*, and Sunghoon Lim†. “도메인 지식을 반영한 설명 가능한 인공지능 (XAI) 기반의 베어링 잔여 수명 예측." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Park, Soyeon*, and Sunghoon Lim†. “공정 조건의 의미론적 표현 학습을 기반으로 한 강건한 공구 마모 예측 모델 개발." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Lim, Chansung*, Gyeongho Kim, and Sunghoon Lim†. "A deep active learning framework for defect classification of wafer bin maps under noisy labels." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Cheon, Jiyeon*, Dajeong Kam, and Sunghoon Lim†. "Parameter-efficient few-shot class-incremental learning for wearable sensor-based hand gesture recognition." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Kam, Dajeong*, Jiyeon Cheon, and Sunghoon Lim†. "Cross-subject open-set hand gesture recognition using multi-representation fusion CNN with multi-score inference." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Choi, Jihyeok*, Juhyun Kim, Gyeongho Kim, and Sunghoon Lim†. “A cycle-consistent generative model for bidirectional cross-modal translation between industrial tabular and time-series data in an ultraviolet lamp pinch-sealing process." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Han, Geonhee, Juhyun Kim*, and Sunghoon Lim†. “An iTransformer-based approach for BTX yield forecasting in the coke oven gas purification process." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Kim, Gyeongho*, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Hybrid data-driven approach for manufacturability prediction of 3D microbial fuel cell anode.” KIIE Fall Conference, Daejeon, Republic of Korea, 2025.

Kim, Gyeongho*, Soyeon Park, Sang Min Yang, Dong Min Kim, Dong Chan Kim, Hoon-Hee Lee, Jae Gyeong Choi, Sujin Jeon, Hyung Wook Park, and Sunghoon Lim†. “Machinability estimation of titanium alloy: An integrated approach with enhanced feature extraction and physics-guided deep multi-task learning.” KORAS Fall Conference, Yeosu, Republic of Korea, 2025.

Kim, Gyeongho*, Sang Min Yang, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Hyung Wook Park, and Sunghoon Lim†. “새로운 가공 조건에서의 공구 마모 예측을 위한 비지도 도메인 적응 기반 인공지능 방법론 개발.” KSMTE Spring Conference, Gangneung, Republic of Korea, 2025.

Kim, Gyeongho*, Sang Min Yang, Sujin Jeon, Soyeon Park, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. “Development of a robust tool wear prediction method under novel operating conditions using deep unsupervised domain adaptation and physics-guided adjustment.” Korean Reliability Society Spring Conference, Jeju, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Hyung Wook Park, and Sunghoon Lim†. “Development of a physics-guided deep domain adaptive regression method for robust tool wear prediction under novel operating conditions.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Jeon, Sujin*, Yun Seok Kang, Hyung Wook Park, and Sunghoon Lim†. “설명 가능한 인공지능(XAI)을 활용한 로봇팔 트리밍 공정의 공구 마모 예측.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Park, Soyeon*, Gyeongho Kim, Sang Min Yang, Hyung Wook Park, and Sunghoon Lim†. “Predicting Machinability Using Cross-task Attention-based Multi-task Learning.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Kim, Gyeongho*, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Juhyun Kim, Chansung Lim, Hyung Wook Park, and Sunghoon Lim†. “Continual learning-based remaining useful life prediction of machining tools under varying operating conditions.” Korean Reliability Society Fall Conference, Gyeongju, Republic of Korea, 2024.
Kim, Gyeongho*, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Juhyun Kim, Ji Yeon Cheon, Chansung Lim, and Sunghoon Lim†. “Hybrid Deep Active Learning Under Low-Budget Scenarios for Efficient Fault Detection.” KIIE Fall Conference, Seoul, Republic of Korea, 2024.
Park, Soyeon*, Sang Min Yang, Gyeongho Kim, Ji Yeon Cheon, and Sunghoon Lim†. “Uncertainty-aware machining process monitoring using multi-task learning.” KIIE Fall Conference, Seoul, Republic of Korea, 2024.
Kim, Gyeongho*, Yunseok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Juhyun Kim, Ji Yeon Cheon, Chansung Lim, Hyung Wook Park, and Sunghoon Lim†.“Fisher-informed continual learning for remaining useful life prediction of machining tools under varying operating conditions.” KSMTE Annual Spring Conference 2024, Gangneung, Republic of Korea, 2024.
Park, Soyeon*, and Sunghoon Lim†. “Lightweight anomalous object detection in a fixed-camera environment.” KIIE Fall Conference, Ulsan, Republic of Korea, 2023.
Kim, Gyeongho*, Sang Min Yang, Sin Won Kim, Do Young Kim, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. "Deep Learning-based Tool Wear Prediction under Multiple Machining Conditions." PHM Korea 2023, Seoul, Republic of Korea, 2023.
Kim, Gyeongho*, Soyeon Park, Jae Gyeong Choi, Hyeokjoon Choi, and Sunghoon Lim†.“Grinding Process Parameter Optimization Using Machine Learning Techniques.” Korea Data Mining Society Summer Conference, Gangneung, Republic of Korea, 2023.
Kim, Gyeongho*, Sangmin Yang, and Sunghoon Lim†. “Development of a Bayesian-based Uncertainty-aware Tool Wear Prediction Model in the End Milling Process.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Ku, Minjoo*, and Sunghoon Lim†. “Development of a deep learning-based anomaly detection model using multivariate time series manufacturing data.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Jeon, Sujin*, Soyeon Park, Hyewon Cho, and Sunghoon Lim†. “Multistep classification of static and dynamic finger gestures using a soft sensor embedded glove.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Kim, Gyeongho*, and Sunghoon Lim†. “Development of a Remaining Useful Life Estimation Method Using Transformer and a Reweighting Technique.” Korea Data Mining Society Summer Conference, Busan, Republic of Korea, 2022.
Cho, Hyewon*, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Development of a deep learning-based real-time gesture detection and classification model using a wearable sensing glove.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2022.
Choi, Jae Gyeong*, Dong Chan Kim, Miyoung Chung, Sunghoon Lim†, and Hyung Wook Park†. “A multimodal 1D convolutional neural network for delamination prediction in carbon fiber reinforced plastic (CFRP) drilling processes.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2022.
Choi, Jae Gyeong*, Chan Woo Kong, Gyeongho Kim, and Sunghoon Lim†. “Car crash detection using ensemble deep learning and multimodal data from dashboard cameras.” Korea Safety Management & Science Fall Conference, Ulsan, Republic of Korea, 2021.
Kim, Gyeongho, Jae Gyeong Choi, Minjoo Ku, Hyewon Cho, and Sunghoon Lim*,†. “Developing a deep learning-based fault detection model for plastic injection molding for car parts companies.” KSQM Spring Conference, Seoul, Republic of Korea, 2021.
Kim, Sun Jun*, and Sunghoon Lim†. “A deep learning-based hybrid recommender system with fake review filtering for e-commerce customers.” KIIE Fall Conference, Seoul, Republic of Korea, 2020.
Choi, Jae Gyeong*, Chan Woo Kong, and Sunghoon Lim†. “Developing machine-learning-based car crash detection systems using video and audio data.” KIIE Fall Conference, Seoul, Republic of Korea, 2019.
Baek, DaeSeon, and Sunghoon Lim*,†. “Smart farming: Developing growth programs and reforming environmental conditions for hog raising using machine vision and deep learning.” KIIE/KORMS/KSS Joint Spring Conference, Gwangju, Republic of Korea, 2019.

patents

Kweon, Sang Jin, Sunghoon Lim, Dagyo Kweon, Taeyeop Kang, Soyeon Park, Jiyeong Min, and Yujin Song. “터널 내 감시 카메라를 활용하여 실시간으로 차량의 번호판을 인식하고 차선 변경하는 차량을 감지하기 위한 방법 및 장치.” Pending, 2024.
Kweon, Sang Jin, Sunghoon Lim, Dagyo Kweon, Taeyeop Kang, Soyeon Park, Jiyeong Min, and Yujin Song. “터널 내에서 CCTV를 활용한 실시간 차량의 후면 번호판 인식 및 차선 변경 차량 감지.” Pending, 2023.
Park, Hyung Wook, Gyeongho Kim, Sunghoon Lim, and Sang Min Yang. “ELECTRONIC DEVICE AND METHOD OF OPERATION FOR PREDICTING THE DEGREE OF TOOL WEAR BASED ON AN ARTIFICIAL INTELLIGENCE MODEL THAT REFLECTS UNCERTAINTY (불확실성을 반영하는 인공지능 모델 기반 공구의 마모 정도를 예측하는 전자 장치 및 그 동작 방법).” 10-2993812.
Lim, Sunghoon, Sujin Jeon, Soyeon Park, and Joonbum Bae. “Static and dynamic gesture recognition device using a soft sensor embedded glove and method thereof (소프트 센서가 부착된 장갑을 이용한 정적 및 동적 제스처 인식 장치 및 방법).” 10-2895661.
Kweon, Sang Jin, Yong Ung Kwon, and Sunghoon Lim. “DEVICE AND METHOD TO PREDICT MUSCLE INJURY DURING REPEATITIVE WORKING ACTIVITY OF WORKER (근로자의 반복적인 근무 활동 동안 근육 부상을 예측하는 방법 및 장치).” 10-2485242.
Kweon, Sang Jin, Yong Ung Kwon, and Sunghoon Lim. “METHOD AND DEVICE FOR REHABILITATION TO PREVENT INJURIES DUE TO REPEATED ROTATION MOTION (반복 회전동작으로 인한 부상 방지 재활 방법 및 부상 방지 재활 장치).” 10-2413185.

Books

서울대학교 국가미래전략원. "그랜드 퀘스트 시즌3." 지식노마드, 2026.

Chatterjee, Sujoy, Thipendra P Singh, Sunghoon Lim, Anirban Mukhopadhyay. “Social Media and Crowdsourcing: Application and Analytics.” CRC Press, 2023.

columns

Lim, Sunghoon. “A New Paradigm for AI Autonomous Manufacturing Reading UNIST’s “The Future of Manufacturing” (AI 자율제조의 새로운 패러다임 UNIST의 ‘제조업의 미래’ 읽기).” UNIST Magazine 2024 Winter, 2024.
Lim, Sunghoon. "[오퍼레이션 트렌드] AI 시대의 제조업, 글로벌 등대공장 네트워크." CHIEF EXECUTIVE, 2024. [Full Text]
Lim, Sunghoon. “AI and reformation of manufacturing cities, Pittsburgh and Ulsan (인공지능과 제조도시의 재도약, 피츠버그와 울산).” UNIST Magazine 2021 Autumn, 2021.

Broadcast Appearance

피지컬AI 프론티어 강국 신기술 조찬 포럼 열려…”데이터 표준화·생태계 구축이 핵심” (2026.04.08./인더스트리뉴스) [Link]

[신년기획]한국형 AI 필승카드⑤-중소기업 AI 확산 없이는 AI 강국도 없다 (2026.01.05./전자신문) [Link]

"생산인구 줄고 中위협 이중고… AI 제조혁신 中企만 살아남아" (2025.12.14./매일경제) [Link]
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