I am an assistant professor in Halıcıoğlu Data Science Institute with affiliation to Computer Science and Engineering Department at UC San Diego. My research vision is to make the next generation AI systems and deep learning algorithms more robust, reliable, trustworthy and safer.
I’m open to collaborations with highly motivated students and post-doc researchers with strong machine learning and mathematical backgrounds! Please contact me with your CV and research experience once you have completed the form:
Ph.D in Massachusetts Institute of Technology, Cambridge, MA, 2020
Electrical Engineering and Computer Science
Advisor: Prof. Luca Daniel
Thesis: Evaluating robustness of neural networks
M.S. in National Taiwan University, Taiwan, 2013
Graduate Institue of Communication Engineering
Advisor: Prof. Tzong-Lin Wu
Thesis: Design of Broadband Common-Mode Filters
B.S. in National Taiwan University, Taiwan, 2011
Major: Electrical Engineering
Graduated at class rank in the top 5%
MIT-IBM Watson AI Lab, Cambridge, MA
Research Staff Member, 2020-2021
Google DeepMind, London, UK
Research Scientist Intern, Summer 2019
Project: Evaluating robustness of deep reinforcement learning agents with continuous control tasks
Results published in ICLR 2020
IBM Research, Yorktown Heights, NY
Research Intern, Summer 2018
Project: Evaluating robustness of neural networks
IBM Research, Yorktown Heights, NY
Research Intern, Summer 2017
Project: Trajectory data mining and anomaly detection
Mitsubishi Electric Research Lab, Cambridge, MA
Research Intern, Summer 2015
Project: Irregular bin-packing on 2D objects
Institute of Mathematics, Academia Sinica, Taipei, Taiwan
Research Intern, Summer 2009
Project: Combinatorics
Robust Deep Reinforcement Learning through Adversarial Loss
T. Oikarinen, W. Zhang, A. Megretski, L. Daniel and T.-W. Weng
NeurIPS 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta Learning
R. Wang, K. Xu, S. Liu, P.-Y. Chen, T.-W. Weng, G. Chuang and M. Wang
ICLR 2021
Fast Training of Provably Robust Neural Networks by SingleProp
A. Boopathy, T.-W. Weng, S. Liu, P.-Y. Chen, G. Zhang and L. Daniel
AAAI 2021
Neural Network Control Policy Verification with Persistent Adversarial Perturbations
Y.-S. Wang, T.-W. Weng, and L. Daniel,
ICML 2020
Robust Deep Reinforcement Learning through Adversarial Loss
T. Oikarinen, T.-W. Weng and L. Daniel
ICML 2020, Uncertainty and Robustness in Deep Learning workshop
Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control
T.-W. Weng, K. Dvijotham2, J. Uesato2, K. Xiao2, S. Gowal2, R. Stanforth2, Pushmeet Kohli
ICLR 2020
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework
C.-Y. Ko, J. Mohapatra, S. Liu, P.-Y. Chen, L. Daniel and T.-W. Weng
Preprint
On the Equivalence between Neural Network and Support Vector Machine
Y. Chen, W. Huang, L. M. Nguyen and T.-W. Weng
NeurIPS 2021
Hidden Cost of randomized smoothing
J. Mohapatra, C.-Y. Ko, T.-W. Weng, P.-Y. Chen, S. Liu and L. Daniel
AIstats 2021
Higher order certification for randomized smoothing
J. Mohapatra, C.-Y. Ko, T.-W. Weng, P.-Y. Chen, S. Liu and L. Daniel
NeurIPS 2020
Certified Interpretability Robustness for Class Activation Mapping
A. Gu, T.-W. Weng, P.-Y. Chen, S. Liu and L. Daniel
NeurIPS 2020, ML4AD workshop [Video]
Towards Verifying Robustness of Neural Networks Against a Family of Semantic Perturbations
J. Mohapatra, T.-W. Weng, P.-Y. Chen, S. Liu and L. Daniel
CVPR 2020 [Video]
Towards Certificated Model Robustness Against Weight Perturbations
T.-W. Weng1, P. Zhao1, S. Liu, P.-Y. Chen and X. Lin, L. Daniel
AAAI 2020
Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation
Y.-S. Wang, T.-W. Weng and L. Daniel
NeurIPS 2019, Safety and Robustness in Decision Making Workshop
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
T.-W. Weng, P.-Y. Chen2, L. M. Nguyen2, M. S. Squillante2, A. Boopathy, I. Oseledets, and L. Daniel
ICML 2019
POPQORN: Quantifying Robustness of Recurrent Neural Networks
C.-Y. Ko1, Z. Lyu1, T.-W. Weng, L. Daniel, N. Wong, and D. Lin
ICML 2019
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
A. Boopathy, T.-W. Weng, P.-Y. Chen, S. Liu and L. Daniel
AAAI 2019
Efficient Neural Network Robustness Certification with General Activation Functions
H. Zhang1, T.-W. Weng1, P.-Y. Chen, C.-J. Hsieh and L. Daniel
NeurIPS 2018
Toward Fast Computation of Certified Robustness for ReLU Networks
T.-W. Weng1, H. Zhang1, H. Chen, Z. Song, C.-J. Hsieh, D. Boning, I. S. Dhillon and L. Daniel
ICML 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
T.-W. Weng1, H. Zhang1, P.-Y Chen, J. Yi, D. Su, Y. Gao, C.-J. Hsieh and L. Daniel
ICLR 2018
On extensions of clever: A neural network robustness evaluation algorithm
T.-W. Weng1, H. Zhang1, P.-Y Chen, A. Lozano, C.-J. Hsieh and L. Daniel
IEEE GlobalSIP 2018
Robust PCA through Robust Optimization
Tsui-Wei Weng and Luca Daniel
NeurIPS 2017, Women in Machine Learning Workshop (WiML)
Computing Least Trimmed Squares Regression to Certifiable Optimality
Tsui-Wei Weng, Rahul Mazumder and Luca Daniel
NeurIPS 2017, Women in Machine Learning Workshop (WiML)
Uncertainty Quantification of Silicon Photonic Devices with Correlated and Non-Gaussian Random Parameters
Tsui-Wei Weng1, Zheng Zhang1, Zhan Su, Youssef Marzouk, Andrea Melloni and Luca Daniel
Optics Express, vol. 23, Issue 4, pp.4242-4254, 2015
Stochastic Simulation and Robust Design Optimization of Integrated Photonic Filters
Tsui-Wei Weng, Daniele Melati, Andrea Melloni and Luca Daniel
Nanophotonics, vol. 6, Issue 1, pp. 299-308, July 2016
A Big-Data Approach to Handle Process Variations: Uncertainty Quantification by Tensor Recovery
Zheng Zhang, Tsui-Wei Weng, and Luca Daniel
IEEE Components, Packaging and Manufacturing Technology, Dec. 2016 (Best paper award)
A Novel Miniaturized Bandstop Filter Using Defected Ground on System in Package(SiP)
Tsui-Wei Weng and Tzong-Lin Wu
IEEE EPEPS, Tempe, Arizona, USA, Oct. 2012
Synthesis Model and Design of a Common-Mode Bandstop Filter (CM-BSF) with An All-Pass Characteristic for High-Speed Differential Signals
Tsui-Wei Weng, Chung-Hao Tsai, Chung-Hao Chen, Don-Ho Han and Tzong-Lin Wu
IEEE Trans. Microw. Theory Tech., vol. 62, no.8, pp.1647-1656, Aug. 2014
Hyperbolic Expressions of Polynomial Sequences and Parametric Number Sequences Defined by Linear Recurrence Relations of Order 2
Tian-Xiao He, Peter J.-S. Shiue, Tsui-Wei Weng
Journal of Concrete and Applicable Mathematics, vol. 12, 63-85, 2014
Sequences of Numbers Meet the Generalized Gegenbauer-Humbert Polynomials
Tian-Xiao He, Peter J.-S. Shiue, Tsui-Wei Weng
ISRN Discrete Mathematics, vol. 2011, Article ID 674167, 16 pages, 2011
On relations of Chebyshev polynomial, Morgan-Voyce polynomial, Fibonacci number, Pell number and Lucas number (in Chinese)
Tsui-Wei Weng
Mathmedia, v.34, no. 4, p.31-42, 2010