Researcher Database

（Last updated : 2026-04-09 16:01:15）　

LIU JIAQING

Department / Course College of Information Science and Engineering Department of Information Science and Engineering

Title / Position Lecturer

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Other Affiliations
1.	College of Information Science and Engineering Department of Information Science and Engineering

Academic background
1.	2018/10/01～2021/09/25	Doctoral Program (2nd Semester) │ Graduate School, Division of Information Science │ Ritsumeikan University │ Completed

Business career
1.	2026/04/01 ～	Lecturer │ │
2.	2022/04/01 ～ 2026/03/31	Assistant Professor │ │
3.	2021/10/01 ～ 2022/03/31	Project Assistant Professor │ │

Present specialized field

Books
1.	2021/09/18	Computer-aided Detection of Depressive Severity Using Multimodal Behavioral Data │ ,pp.353-371

Papers
1.	2026/05/15	Multimodal Brownian Bridge Diffusion Model for Controllable Synthetic Medical Image Generation │ Biomedical Signal Processing and Control │ 117
2.	2026/04/15	Integrating text and medical images for segmentation using interpretable graph neural network, │ Biomedical Signal Processing and Control │ 115
3.	2026/04	DepressionLLM: Emotion- and causality-aware depression detection with foundation models │ Displays │ 92
4.	2026/03/26	RA3-FDA: Resource-Adaptive Federated Domain Adaptation with Dual Heterogeneity Awareness for EEG-based Depression Detection │ Expert Systems with Applications │ 1
5.	2026/03	One framework to rule them all: Unifying multimodal tasks with LLM neural-tuning │ Pattern Recognition │ 171 (B)
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Academic conference presentation
1.	2025/09	Clinical Data-Driven Retrieval-Augmented Model for Lung Nodule Malignancy Prediction,
2.	2025/07	CoordConv-ControlDDPM: A Text-Guided Approach to Medical Imåage Augmentation for Improved Segmentation
3.	2025/07	Dual-Stream Fusion for Advanced Spatio-Temporal Analysis in Remote Photoplethysmography,
4.	2025/07	Enhancing Depression Detection with Chain-of-Thought Prompting: From Emotion to Reasoning Using Large Language Models
5.	2025/07	Retrieval-Augmented Multimodal Depression Detection
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Works
1.	2025/07	Multimodal AI for Depression Detection: Advances in Emotion Understanding and Model Interpretability
2.	2025/03	Advancing Depression Detection with AI
3.	2023/03/17	Multimodal Deep Learning in Depression Estimation
4.	2022/08	Multimodal Deep Learning in Healthcare