knowledge and learning
- We present a modern review on forecast combinations over the past five decades
- New paper “Feature-based intermittent demand forecast combinations: accuracy and inventory implications” appeared in International Journal of Production Research
- New Paper: “Optimal reconciliation with immutable forecasts” appeared in European Journal of Operational Research
- The febama paper is published in the International Journal of Forecasting
- New paper “Escalator accident mechanism analysis and injury prediction approaches in heavy capacity metro rail transit stations” published in Safety Science
- The darima paper is published in the International Journal of Forecasting
- Paper accepted in IJF: Hierarchical forecasting with a top-down alignment of independent level forecasts
- Paper “Improving forecasting with sub-seasonal time series” accepted in IJPR
- Keynote talk for ICDM 2021 workshop by Yanfei Kang
- Feng Li is interviewed by the Forecasting Impact Podcast
Welcome to Dr. Yanfei Kang and Feng Li’s Lab — KLLAB (pronounced as [col·lab], meaning collaborating). A lab for knowledge and learning.
The initiative of KLLAB is to bring collaborations between Dr. Yanfei Kang‘s institution Beihang University and Dr. Feng Li‘s institution Central University of Finance and Economics. KLLAB is not only a lab named after Dr. Kang and Li’s initials but also stands for knowledge and learning for the people in our lab.
Our KLLAB started as a joint meetup between Beihang University and Central University of Finance and Economics in earlier 2016. In 2020, the KLLAB has reached 20 members.
We focus on finding and solving interesting problems in forecasting, statistical computing, and distributed learning.
Our KLLAB has invited collaborators to visit the lab every year, and we also organize focused workshops with a specific theme. Our research network reaches Australia, UK, Sweden, the US, and other countries. Please checkout our collaboration network on this page.
We welcome university students to join us from all levels, from undergraduates to Ph.D. The KLLAB also sends the best students to the world’s leading universities.
Dr. Yanfei Kang and Dr. Feng Li are also offering undergraduate and graduate-level courses in statistical computing [K][L], Bayesian analysis[K][L], distributed statistical computing [L], and data science [L] every year.