Shiwei Liu

Hi, I am a Ph.D. candidate of machine learning in the data mining group at the Eindhoven University of Technology (TU/e), the Netherlands, under the supervision of Mykola Pechenizkiy and Decebal Constantin Mocanu. Before I moved to the Netherlands, I obtained my master degree at Harbin Institute of Technology (Shenzhen).

Research Interests

Machine Learning, Deep Learning, Sparse Neural Network Training, Sparsity, Computer Vision, Efficient Neural Network.

News

5/2022, one paper got accepted by UAI 2022 (link - here).

4/2022, our tutorial “Sparse Neural Networks Training” has been accepted at ECMLPKDD 2022 (link - here).

6/4/2022, I got my PhD with cum laude (distinguished thesis).

3/2022, I got my PhD thesis abstract accpeted by IDA 2022, which was also the first conference (symposium) that I have attended in the first year of my PhD. PhD life is a cycle :).

2/2022, I am honored to receive the postdoctoral fellowship at IFML of The University of Texas at Austin.

1/2022, (2/3) two of my first-author papers are accepted by ICLR 2022: the unreasonable effectiveness of random pruning and FreeTickets Ensemble.

12/2021, I receive the “outstanding intern” honour in JD Acedemy Explore.

9/2021, (1/1) one of my first-author paper gets accepted by NeurIPs 2021: Sparse Training via Boosting Pruning Plasticity with Neuroregeneration.

6/2021, I moved to Beijing, China for my internship at JD Acedemy Explore, under supervision of Li Shen and Dacheng Tao.

5/2021, (2/2) two of my first-author papers are accepted by ICML 2021: In-Time Over-Parameterization and Selfish Sparse RNN Training.

Experience

PeriodDegreeVenue
March. 2018 - presentPh.D.Eindhoven University of Technology
June. 2021 - Nov. 2021Research InternJD Acedemy Explore
July. 2015 - Sep. 2017M.Sc.Harbin Institute of Technology
July. 2011 - Sep. 2015B.Sc.North University of China