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Tianlin Liu Updated: April 17, 2021 Tianlin Liu Updated: April 17, 2021 PhD student E-mail: [email protected] Department of Mathematics and Computer Science Web: http://tianlinliu.com University of Basel, Basel, Switzerland. RESEARCH Machine Learning, Inverse problems. INTEREST EDUCATION University of Basel, Switzerland 2020 – present PhD of Mathematics and Computer Science Advisor: Professor Ivan Dokmanic´ Jacobs University Bremen, Germany 2017 – 2019 Master of Science in Data Engineering Advisor: Professor Herbert Jaeger Jacobs University Bremen, Germany 2013 – 2016 Bachelor of Science in Mathematics Advisor: Professor Gotz¨ Pfander AWARDS AND Oberwolfach Leibniz Graduate Student Grant 2021 FELLOWSHIPS Jacobs University Bremen Dean’s Prize for Outstanding Master’s Thesis 2019 IEEE NER 2019 Best Paper Finalist Award 2019 Bernstein Network SmartStart-1 Fellowship 2018 – 2019 ACM-BCB 2018 Travel Award 2018 Jacobs University Bremen President’s List Distinction 2017 – 2019 PUBLICATIONS [1] Tianlin Liu and Friedemann Zenke. Finding trainable sparse networks through Neural Tangent Transfer. In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020. [2] Zekun Yang∗ and Tianlin Liu∗. Causally Denoise Word Embeddings Using Half- Sibling Regression. In Proceedings of AAAI Conference on Artificial Intelli- gence, 2020. (∗Equal contribution). [3] Tianlin Liu. Harnesing Slow Dynamics in Neuromorphic Computation. Master thesis, Department of EE and CS, Jacobs University, 2019. (Dean’s Prize for Outstanding Master’s Thesis). [4] Tianlin Liu, Lyle Ungar, and Joao˜ Sedoc. Continual Learning for Sentence Rep- resentations Using Conceptors. In Proceedings of NAACL Conference on Hu- man Language Technologies, 2019. [5] Xu He, Tianlin Liu, Fatemeh Hadaeghi, and Herbert Jaeger. Reservoir transfer on analog neuromorphic hardware. In Proceedings of International IEEE EMBS Conference on Neural Engineering (NER), 2019. (Best Paper Finalist Award, 3rd place out of 467 accepted papers). [6] Tianlin Liu, Lyle Ungar, and Joao˜ Sedoc. Unsupervised post-processing of word vectors via conceptor negation. In Proceedings of AAAI Conference on Artificial Intelligence, 2019. Tianlin Liu – Page 1 of 2 – Curriculum Vitae [7] Tianlin Liu, Joao˜ Sedoc, and Lyle Ungar. Correcting the common discourse bias in linear representation of sentences using conceptors. In Proceedings of ACM- BCB Workshop on BioCreative/OHNLP Challenge, 2018. (Travel Award). [8] Tianlin Liu and Arvid Kappas. Predicting engagement breakdown in HRI using thin-slices of facial expressions. In Proceedings of AAAI-2018 Workshop on Affective Content Analysis, 2018. [9] Tianlin Liu and Dae Gwan Lee. Fast binary compressive sensing via smoothed `0 gradient descent. In Proceedings of 5th International Workshop on Com- pressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), 2018. SERVICES Reviewer for ICML 2021 and NeurIPS 2021. RESEARCH Jacobs University Bremen, Bremen, Germany 02/2018 – 06/2019 EXPERIENCE Research assistant • Advisor: Professor Herbert Jaeger • Design and deploy reservoir computing algorithms on the Dynap-se board, which is a neuromorphic architecture tiling a number of analog microchips for Spiking Neural Networks. This project is funded by the NeuRAM3 EU Horizon 2020 Program. Jacobs University Bremen, Bremen, Germany 09/2017 – 12/2018 Research assistant • Advisor: Professor Herbert Jaeger • Develop provable learning methods for Observable Operator Models (OOMs), an epistemic model for stochastic systems emulating information gain pro- cesses. University of Pennsylvania, Philadelphia, USA 05/2018 – 09/2018 Visiting researcher • Advisor: Professor Lyle Ungar • Examine linguistic properties of distributional word representations (word vec- tors) with spectral decomposition methods. Chinese University of Hong Kong, Hong Kong 09/2016 – 03/2017 Research assistant • Supervisor: Professor Defeng Wang and Professor Lin Shi. • Applied compressive sensing methods on Magnetic Resonance Imaging (MRI); developed an infrastructure for automatically reconstructing 3D Spine Model from Bipolar X-ray Images. Jacobs University Bremen, Bremen, Germany 09/2015 – 06/2016 Research assistant • Supervisors: Professor Gotz¨ Pfander and Dr. Dae Gwan Lee. • Designed efficient Compressive Sensing algorithms for binary (f0; 1g-valued) signal reconstruction. COMPUTER Python, MATLAB, C, LATEX. SKILLS LANGUAGES Mandarin – mother tongue English – fluent German – basic Tianlin Liu – Page 2 of 2 – Curriculum Vitae.
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