Auton Lab postdoc candidate job talk: Wednesday March 28, 11am, NSH 4119

[Artur Dubrawski]

Team,

We will have a skype presentation on Wednesday next week given by Bo Wu of Chinese Academy of Science, who is seeking a post-doctoral position with the Auton Lab.

Please see below the title/abstract and bio of the speaker and please join us to see the talk!

Cheers
Artur

---

Title: Temporal Learning and Prediction

Abstract:
While time-aware scenarios are ubiquitous, Temporal Learning and Prediction motivated by a wide range of applications depending on the dynamic platforms or systems (e.g. diffusion in marketing, pricing in ads etc). In domains as diverse as consumption, finance, entertainment and transportation, we observe a fundamental shift away from discrete, infrequent data to nearly continuous monitoring and recording. Therefore, temporal modeling dynamic signals, behaviors or information is a novel and prevalent topic in research area.

Meanwhile, as an important platform for users to share and spread information at anytime, “social media” offers an good opportunity to study temporal social signals, such as post popularity, user interests over time etc. We treated future popularity prediction as our research problem, and our research work tends to investigate the temporal learning and prediction techniques for sequential or time-series data. Different with previous prediction algorithms, our work study multiple temporal-view prediction problems for social media popularity, which contains dynamic factorization prediction, specific time prediction and time-series prediction. From the inner to sequential and from implicit to explicit, these prediction approaches progressively the influence previous user sharing behaviors to future popularity. Moreover, we explorer temporal learning and prediction have effective effects, which evaluated by the experiments of social media popularity prediction on large dataset. And we are also tring to applied proposed temporal modeling approaches into other problems.

Short Bio:
Bo Wu received Ph.D. degree from Chinese Academy of Sciences (Institute 
of Computing Technology), Beijing, China. His current research interests 
are temporal machine learning, deep learning, computer vision and social 
multimedia. He has over 2-years research experience in Microsoft 
Research Asia, and one year research experience in Academia Sinica. He 
has authored several papers published at top conferences and journals 
(ACM MM, AAAI, IJCAI, TKDE etc.), and also invited as reviewers or TPC 
member of IEEE TKDE, IEEE TMM, ACM Multimedia, SIGIR and ICIP etc. He is 
co-organizer of ACM Multimedia Challenge 2017. He has received several 
awards, including Turing 50th Student Scholarship, Innovation Research 
Award, Ph.D. Student Research Award, Top 1% in Global Recommendation 
Challenge etc.