From Goleta to La Jolla, there is always a SoCal beach!

Call for reviewers of 2nd Workshop on AI for Drug Discovery and Development NeurIPS AI4D3 Workshop at NeurIPS Conference '24! Feel free to sign up and share! forms.gle/B9SKCeJsbCNp3L…

Can we use active learning to better train AI systems like those found in autonomous vehicles? Chong Liu, DSI Postdoctoral Fellow, is applying active learning for automatic video semantic segmentation Learn more with insights written by Chong Liu: datascience.uchicago.edu/insights/behin…

Open educational materials can often go a long way. I benefitted from countless such materials myself (e.g., those from Gilbert Strang, Steve Boyd & Andrew Ng). Now it's time to contribute back. Here we go -- 52 videos from three grad-level courses I taught at UCSB. Enjoy.

Our #ComputerScience department at @UAlbany is #hiring a Visiting Assistant Professor! Feel free to apply if you are interested! Link: albany.interviewexchange.com/jobofferdetail…

I'm happy to share that I'm starting a new position as Assistant Professor of Computer Science at University at Albany SUNY - The State University of New York!

Happy to release a review manuscript on #BindingAffinity Prediction! We reviewed a lot of approaches from conventional to machine learning-based ones. Feel free to check it out here! arxiv.org/abs/2410.00709

Flying to Seattle to attend #INFORMS2024 conference! I'll co-chair the #GenerativeAI for #DecisionMaking session (SA72, 8am Sun Oct 20) and give a talk at #BayesianOptimization session (WB72, 9:30am Wed Oct 23). Happy to meet new and old friends!

Welcome to my talk at #INFORMS2024 conference today! At 9:30am I'll present "Parametric Function Approximation for Black-Box Optimization: A New Perspective" at WB72 (Regency 703).

I'm looking for two #ComputerScience #PhD students starting Fall 2025 @UAlbany SUNY - The State University of New York! The focused areas are #MachineLearning, #Optimization, and #AI4Science! Full ad is here: chong-l.github.io/hiring.html. Come and join us!

Our paper "Black-Box Optimization with Implicit Constraints for Public Policy" is accepted by AAAI -2025 AI for Social Impact Track! We apply #Bayesianoptimization help police districting. Paper: arxiv.org/abs/2310.18449. Coauthors: Wenqian Xing JungHo Lee Shixiang (Woody) Zhu .

Happy to be invited as an Area Chair of @ICMLconf-2025! The abstract submission deadline is Jan 23, 2025 AOE and the full paper submission deadline is Jan 30, 2025 AOE.

Wrote a blog sharing my #ComputerScience #Faculty #JobMarket experience in 2022-2023. Feel free to share it if you found it interesting or helpful! Link: chong-l.github.io/Liu_Faculty_Hu…

Jan 15 is the #ComputerScience #PhDapplication deadline University at Albany, only one week left! Look forward to reading your application!

Happy to share that our paper has been selected for #Oral presentation at AAAI-2025 #AI for #SocialImpact Track! See you in Philadelphia next month!

Many #DrugDiscovery problems focus on hitting multiple target performance criteria when screening over drug candidates. Our new @AISTATS_conf-2025 paper models it as constrained Multi-Objective Bayesian Optimization problem and solve it efficiently! Link: arxiv.org/abs/2411.03641

Attending the 2025 Information Theory and Applications Workshop #ITA2025 in San Diego! Tomorrow I'll give a talk on our recent #AISTATS2025 paper "Constrained Multi-Objective Bayesian Optimization through Optimistic Constraints Estimation". arxiv.org/abs/2411.03641

Congrats!

Come and join us at 2025 Midwest AI for Drug and Development workshop in Chicago!

New @UncertaintyinAI-2025 paper! Exact acquisition function maximizer can be hardly obtained in #BayesianOptimization, and our paper systematically studies it in theory. We find a condition where BO can still be no-regret even without exact maximization. arxiv.org/abs/2506.11831