• "Trusted aggregation: Model filtering backdoor defense in federated learning'', the 6th International Conferences on Econometrics and Statistics, Tokyo, Japan, Aug 2023

• "Defending against Backdoor Attack'', the 15th International Conference of the ERCIM WG on Computational and Methodological Statistics, London, United Kingdom, Dec 2022

• "Trusted aggregation: Model filtering backdoor defense in federated learning", the International Conference on Advances in Interdisciplinary Statistics and Combinatorics, Greensboro, Oct 2022

• "Detecting adversarial examples with Bayesian neural network'', the 5th International Conferences on Econometrics and Statistics, Kyoto, Japan, June 2022

• "Detecting Adversarial Examples with Bayesian Neural Network", the 7th Bayesian, Fiducial & Frequentist, Toronto, Candada, May 2022

• "On the Robustness of Machine Learning Systems”, San Francisco Bay Area Chapter of American Statistical Association (SFASA), Virtual, Apr 2022

• "On the Robustness of Deep Neural Networks”, Cisco Systems, Inc., Virtual, Apr 2022

• "On the Robustness of Deep Neural Networks”, Rensselaer Polytechnic Institute, Virtual, Feb 2022

• "ER-Classifier and BATer”, Presentation, Auburn University, Virtual, Oct 2021

• "Towards robustness of deep neural networks via regularization”, ICCV poster presentation, Virtual, Oct 2021

• "Defending against adversarial attacks by regularized deep embedding”, Symposium on Data Science & Statistics, Bellevue, May 2019

• "Improved adversarial defense through robust bayesian neural network”, ICLR poster presentation, New Orleans,May 2019

• "Learning from group comparisons: Exploiting higher order interactions”, NeurIPS Poster Presentation, Montreal, Dec 2018