Zihao Wang

Zihao Wang

Second-year student in Master of Science of Computer Science in UC San Diego

Posts by Collection

portfolio

publications

Double-Flow GAN Model for the Reconstruction of Perceived Faces from Brain Activities

Zihao Wang, Jing Zhao, Hui Zhang

Published in arXiv (preprint), 2024

This paper proposes Double-Flow GAN, a dual-stream generative adversarial framework that reconstructs perceived human faces from fMRI brain activity. The model leverages a feature-aligned latent space to enhance perceptual realism and structural accuracy, achieving state-of-the-art performance in neural decoding.

Recommended citation: Wang, Z., Zhao, J., & Zhang, H. (2024). Double-Flow GAN Model for the Reconstruction of Perceived Faces from Brain Activities. arXiv preprint arXiv:2312.07478. https://arxiv.org/abs/2312.07478v2

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs

Ye Tian, Xiaoyuan Ren, Zihao Wang, Onat Gungor, Xiaofan Yu, Tajana Rosing

Published in 22nd IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS) (published), 2025

DailyLLM is a lightweight LLM-based framework for context-aware activity log generation and summarization using multimodal smartphone and smartwatch sensors. It achieves 17% higher BERTScore precision and 10× faster inference compared to state-of-the-art methods while using only a 1.5B-parameter model.

Recommended citation: Tian, Y., Ren, X., Wang, Z., Gungor, O., Yu, X., & Rosing, T. (2025). DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs. In 22nd IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS). https://arxiv.org/abs/2507.13737

MultiLifeQA: A Multi-Domain Health Reasoning Benchmark

Ye Tian$^*$, Zihao Wang$^*$, Onat Gungor, Xiaoran Fan, Tajana Rosing

Published in International Conference on Learning Representations (ICLR) (under review), 2026

We propose MultiLifeQA, a large-scale question answering benchmark for multidimensional lifestyle health reasoning. It spans four lifestyle dimensions (diet, activity, sleep, and emotion) and evaluates cross-dimensional and long-horizon reasoning capabilities of LLMs through context-based and database-augmented prompting.

Recommended citation: Tian, Y.$^*$, Wang, Z.$^*$, Gungor, O., Fan, X., & Rosing, T. (2026). MultiLifeQA: A Multi-Domain Health Reasoning Benchmark. Submitted to the International Conference on Learning Representations (ICLR). https://openreview.net/forum?id=5882BZyFdS

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.