About Me

I am a Ph.D. student in Computer Science at Georgetown University, advised by Professor Sarah A. Bargal. My research focuses on multimodal generative AI, controllable and character-consistent visual generation, diffusion models, multimodal reasoning, LLM/MLLM post-training, and agentic AI systems.

Education

2021–2027

Georgetown University, Washington, DC
Ph.D. in Computer Science
Computer Vision Group
Advisor: Sarah A. Bargal

2019–2021

Georgetown University, Washington, DC
M.S. in Computer Science

2015–2019

Beihang University, Beijing, China
B.E. in Computer Science and Technology

Publications

ViSTA: Visual Storytelling using Multi-modal Adapters for Text-to-Image Diffusion Models

2026

Sibo Dong, Ismail Shaheen, Maggie Shen, Rupayan Mallick, and Sarah Adel Bargal

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · Oral

[Proceedings] [arXiv]

Sidecar: Training-Free Semantic Reuse for Character-Consistent Free-form Visual Storytelling

2026

Sibo Dong and Sarah Adel Bargal

Under review

[arXiv]

FreeStory: Training-Free Character Consistency for Free-Form Visual Storytelling

2026

Sibo Dong, Ismail Shaheen, and Sarah Adel Bargal

Under review

[arXiv] [Code] [Project Page]

D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition

2025

Rupayan Mallick, Sibo Dong, Nataniel Ruiz, and Sarah Adel Bargal

CVPR Workshop on Uncertainty Quantification for Computer Vision

[Proceedings] [arXiv]

Predicting Missing Response with BERT Model in Process Data

2024

Qiwei He and Sibo Dong

International Meeting of the Psychometric Society (IMPS)

SEINE: SEgment-based Indexing for NEural Information Retrieval

2022

Sibo Dong, Justin Goldstein, and Grace Hui Yang

SIGIR Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR)

[Proceedings] [arXiv]

Do We Really Need Everything Everywhere All at Once? Query-Specific Fine-Tuning for Transformer-Based Neural Retrievers

2022

Sibo Dong and Grace Hui Yang

Text REtrieval Conference (TREC)

GazBy: Gaze-Based BERT Model to Incorporate Human Attention in Neural Information Retrieval

2022

Sibo Dong, Justin Goldstein, and Grace Hui Yang

ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR)

[Proceedings] [arXiv]

Industry Research Experience

May–Aug. 2026

Siemens
Data and AI Team
Cloud & Industrial GenAI Intern

May–Aug. 2025

Siemens Digital Industries Software
GenX Team
Cloud & Industrial GenAI Intern

May–Aug. 2023

ByteDance
Applied Machine Learning Team
Research Scientist Intern

Additional Research Experience

Sep. 2018–Jun. 2019

Beihang University
Engineering Research Center
Undergraduate Thesis: Automatic Scoring Method for Essay Review

Jul.–Sep. 2018

University of California, Berkeley
Visual Computing Lab
Eyeglasses-free Vision Correcting Display

Jan.–Apr. 2017

Beihang University
Institute of Advanced Computing Technology
Real-Time Video Dehazing Based on Spatio-Temporal Markov Random Fields

Technical Skills

Research: Multimodal generative AI, diffusion models, visual storytelling, vision-language and multimodal LLMs, agentic LLMs, reinforcement learning and post-training, text-to-SQL.
Programming & frameworks: Python, C++; PyTorch, TensorFlow, Hugging Face Transformers, Diffusers; Apache Calcite.
Languages: Mandarin Chinese (native), English (fluent).

Professional Service & Honors

Reviewer: NeurIPS, ICLR, WACV, BMVC, SIGIR, CIKM, ICTIR, TOIS (2020–present).
Teaching assistant: Science of AI (2026); Deep Learning (2025–2026); Deep Reinforcement Learning (2021–2023), Georgetown University.
Honors: 2026 Conference Travel Grant; 2024 Outstanding Teaching Assistant.