Our paper
has been awarded a best paper award for 2020 in the IEEE Transactions on Power Systems.
Check our paper Differential Privacy of Hierarchical Census Data: An Optimization Approach, by Ferdinando Fioretto, Pascal Van Hentenryck, and Keyu Zhu, to be publsihed in Artificial Intelligence. It presents a state-of-the-art algorithm for releasing census data under the framework of differential privacy. Beautiful dynamic program exploiting the structure of the cost function.
I am delighted to receive the Student Recognition of Excellence in Teaching: Class of 1934 Award at Georgia Tech. Back in 2010 when I was at Brown in Computer Science, I received the Philip J. Bray Award for Teaching Excellence. Those awards are incredibly special to me and always remind me how much I personally benefited from some amazing math and CS teachers in high school and college (Gaby and Baudouin, that is for you).
Check these civic engagement projects at Georgia Tech.
This is the video of my talk entitled On-Demand Multimodal Transit Systems: Capturing Travel Mode Adoption and Assessing Resilience for the 2021 Inaugural INFORMS TSL Virtual Seminar Series.
Check the video of our work to be presented at AAAI 2021.
Yesterday, I got a nice surprise in the mail from students in my undergraduate class on constraint programming.
This came with plenty of coffee and chocolate. In a challenging year, we manage to learn and have some fun at the same time.
I was fortunate to be a 2020 INFORMS Diversity, Equity, and Inclusion (DEI) Ambassador. You can check what we do on the Seth Bonder Camp. I also had the immense pleasure of meeting Professor Charles Pierre at Clark Atlanta University in that context (he is also DEI ambassador) and we are getting organized for new DEI initiatives. Thanks INFORMS!
Check our video on integrating optimization, machine learning, and model-predictive control for large-scale ride-sharing systems.
It presents the paper Real-Time Dispatching of Large-Scale Ride-Sharing Systems: Integrating Optimization, Machine Learning, and Model Predictive Control. Connor Riley, Pascal Van Hentenryck, and Enpeng Yuan. In the Proceedings of 29th International Joint Conference on Artificial Intelligence (IJCAI-20), Tokyo, Japan 2020.
Check our AAAI 2021 paper on Bias and Variance of Post-processing in Differential Privacy. It studies the effects of post-processing differentially private outputs (e.g., to restore feasibility of some constraints) on the noise distribution. The paper takes a first step towards understanding the properties of post-processing and quantifies the bias and variance introduced by a wide class of post-processing algorithms based on projection. It includes an analysis of the release of important quantities based on census data. The most interesting result is Theorem 5.
