Yonghan Jung
Mathematics · Purdue University West Lafayette
Publications
31
Citations
203
Est. group size
—
Recurring co-author estimate
Active years
21
Publishing since 2006
This researcher works primarily on causal inference, the branch of statistics and machine learning concerned with estimating cause-and-effect relationships from data, including methods that use machine learning to estimate treatment effects and bounds on causal effects when some variables are unmeasured. Their publication record also includes a notable side interest in applied sensing and robotics topics, such as LiDAR (laser-based distance sensing) and vision-based mapping for disaster investigation and drone surveying, suggesting collaborative work spanning statistical theory and applied engineering. Publications span top machine learning venues as well as remote sensing and applied engineering journals.
Publication output has been variable over the past decade with gaps in some years (e.g., 2019, 2022) followed by a marked increase in 2024 and continued output projected into 2025-2026.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Information-Theoretic Causal Bounds under Unmeasured Confounding
arXiv (Cornell University) · 2026
- Data-Driven Information-Theoretic Causal Bounds under Unmeasured Confounding
arXiv (Cornell University) · 2026
- Benchmarking Visual Feature Representations for LiDAR-Inertial-Visual Odometry Under Challenging Conditions
IEEE Access · 2026
- Benchmarking Visual Feature Representations for LiDAR-Inertial-Visual Odometry Under Challenging Conditions
arXiv (Cornell University) · 2026
- Sufficient Invariant Learning for Distribution Shift
2025
- The Short-Term Intervals Stock Volatility Prediction System for Supporting Investment Decision-Making based on News
Journal of the Korea Academia-Industrial cooperation Society · 2025
- Performance Evaluation of Drone LiDAR Sensors for Field Operations in Mountainous Areas
Korean Journal of Remote Sensing · 2024
- Accuracy Assessment of Terrestrial and Drone LiDAR-Based Model for Disaster Site Investigation
Korean Journal of Remote Sensing · 2024
- Analysis of Landslide Damage from Rainfall Using Drone Mapping
Korean Journal of Remote Sensing · 2024
- Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference
2024
- Association between clinical ischemic risk and thrombogenicity phenotype and their prognostic prediction in patients undergoing percutaneous coronary intervention
European Heart Journal · 2024
- Development of A Vision-LiDAR SLAM Robot Platform for Disaster and Accident Scene Investigation
Journal of the Korea Academia-Industrial cooperation Society · 2024
- System Calibration of Vision-LiDAR Sensor Module Mounted on A Ground Disaster Investigation Robot
Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography · 2024
- Unified Covariate Adjustment for Causal Inference
2024
- Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
2023
- Korean Journal of Remote Sensing×3
- arXiv (Cornell University)×3
- Neural Information Processing Systems×2
- Proceedings of the AAAI Conference on Artificial Intelligence×2
- Journal of the Korea Academia-Industrial cooperation Society×2
- Arvid Sjölander
Mathematics · Indiana University
- Vidhura Tennekoon
Mathematics · Indiana University
- Eloise Kaizar
Mathematics · The Ohio State University
- Weibin Mo
Mathematics · Purdue University West Lafayette
- Giorgos Bakoyannis
Mathematics · Indiana University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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