Institute of Information Science

Automatic Music Concert Animation

Incorporating artificial intelligence into the multimedia is a complex project. Itinvolves integration of cross-modal data, such as images, musical sounds, and evenbody movement. In this project, we focus on such integration technology inanimation. We endeavor to teach machines to understand music content, match thebody movement of virtual characters to that content, and even allow virtual musiciansto perform with human. Such technology will not only make the animation taskefficient but also explore new possibilities of interactive multimedia.

Cryptography in the Quantum Era: Challenge and Opportunity

With the rapid advance of quantum technology, it becomes increasingly imperative to understand the role of quantum in cryptography. We have worked on this exciting interdisciplinary field for a decade from both practical and theoretical aspects. In particular, we have actively participated in the post-quantum cryptography standardization process by the U.S. National Institute of Standards and Technology (NIST) with one submission surviving in round 2. On the theoretical side, we have broad interests and contributed to several research topics such as device-independent randomness amplification, classical delegation of quantum computation, and security in the quantum random oracle model.

Assemble and Annotate Economically Important Genome in Chromosome

Rapid progress in sequencing technologies has moved biomedical research into the era of big data. However, consider the limitation on budget and computational burdens for releasing the full power of raw sequences. We develop a new hybrid and spiral strategy to sketch the draft genome by integrating gap-closing and scaffolding algorithms using local de novo assembly of link reads. This approach has improved the genome assemblies of human and vital aquaculture species, both in terms of continuity and completeness for precision medicine and genome breeding.

AirBox: a participatory PM2.5 sensing system

The AirBox project is the largest l participatory PM2.5 sensing system in the world. The project enables low-cost PM2.5 sensing and enriches environmental data analysis at a finer spatio-temporal granularity. It provides innovative services for anomaly detection, emission source finding, and data forecast; and it has created a positive ecosystem involving academia, industry, governments, and citizens. It has the potential to facilitate smart city design, intelligent environmental governance, and public-private partnerships for the common good into the future.

A data-independent acquisition-based global phosphoproteomics system enables deep profiling

Nature Communications, May 2021

Reta Birhanu Kitata, Wai-Kok Choong, Chia-Feng Tsai, Pei-Yi Lin, Bo-Shiun Chen, Yun-Chien Chang, Alexey I. Nesvizhskii, Ting-Yi Sung and Yu-Ju Chen

Null Space Component Analysis of One-Shot Single-Channel Source Separation Problem

IEEE Transactions on Signal Processing, To Appear

Wen-Liang Hwang and Jinn Ho

End-to-end Recurrent Cross-Modality Attention for Video Dialogue

IEEE/ACM Transactions on Audio, Speech and Language Processing, To Appear

Yun-Wei Chu, Kuan-Yen Lin, Chao-Chun Hsu, Lun-Wei Ku

Knowledge Based Hyperbolic Propagation

Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 2021

Chang-You Tai, Chienkun Huang, Liangying Huang, Lun-Wei Ku

User-Centric Path Reasoning towards Explainable Recommendation

Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 2021

Chang-You Tai, Liangying Huang, Chienkun Huang, Lun-Wei Ku

Beyond Fair Pay: Ethical Implications of Crowdsourcing NLP Task

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2021), June 2021

Boaz Shmueli, Jan Fell, Soumya Ray, Lun-Wei Ku