The focus of our research is to address (1) how neuronal development contributes to the assembly and function of the nervous system, and (2) how defects in this process lead to brain disorders. We take a multidisciplinary approach that include genetics, cell biology, developmental biology, biochemistry, advanced imaging (for neuronal structures and activity), electrophysiology, computation … Read more
I used the tools of operations research (optimization, stochastic modeling, and game theory), machine learning, and statistics to study problems in operations management broadly defined, including supply chains, service systems, transportation and mobility, and markets. My current research focus is on sustainable operations and innovative business models, including sharing economy, on-demand services, and online marketplaces.
Changxiao Cai’s research interests lie broadly in the intersection of statistics, optimization, and machine learning. He is interested in developing provably scalable methods for information extraction from high-dimensional data, with an aim to achieve the optimal interplay between statistical accuracy and computational efficiency.
3D reconstruction and generative models. I use neural and physical 3D representations to generate realistic 3D objects and scenes. The current focus is large-scale, dynamic, and interactable 3D scene generations. These generative models will be greatly useful for content creators, like games or movies, or for autonomous agent training in virtual environments. For my research, … Read more
My research lies at the intersection of computer vision, human vision, and machine learning. Visual perception presents not just a fascinating computational problem, but more importantly an intelligent solution for large-scale data mining and pattern recognition applications. My research has thus three themes. 1. Actionable Representation Learning Driven by Natural Data. I attribute our fast … Read more
I design, develop, and deploy hybrid human-AI intelligent interactive systems to provide access to visual information in the real world. By combining the advantages of humans and AI, these systems can be nearly as robust and flexible as humans, and nearly as quick and low-cost as automated AI, enabling us to solve problems that are … Read more
Max’s research interests lies in the design, management, and optimization of large-scale infrastructure systems, focusing on the air transportation system and emerging aerial mobility systems. He is interested in the application of methods applicable to networked systems, especially with resource constraints (e.g., airspace and airport capacity), diverse stakeholders (e.g., passenger-centric, airline-centric), and complex dynamics (e.g., … Read more
I am interested in principled approaches to machine learning with focus on data-driven decision making, deep learning foundations, and heterogeneous data. My research integrates optimization methods (specifically convex and first-order) and statistical learning theory to design efficient algorithms/architectures that address these data-science problems. Additional Information How did you end up where you are today? I … Read more
My lab’s research focuses on understanding computation in large-scale neural circuits through adaptive perturbations and real-time inference. We develop statistical machine learning algorithms to adaptively build models of neural and behavioral data online, and use them for understanding the mapping between multidimensional neural stimulations and complex behavioral outcomes. We emphasize data-driven Bayesian approaches suited for … Read more