I direct the Artificial Intelligence and Systems Laboratory (AISys). AISys is located at the Storey Innovation Center (Office: 2212).

At AISys, we investigate a variety of open problems that sit at the intersection of artificial intelligence, machine learning, and computer systems (embedded, cloud, robotics). We investigate the development of novel algorithmic and theoretically principled ML methods for systems problems such as optimizing the performance and energy efficiency of highly-configurable systems. We also look into the design and architecture of system software that treat ML computation as a first-class citizen such as optimizing training and inference. Our overarching goal is to develop the next generation of on-device and cloud-based systems able to perceive, reason and react to complex real-world environments and users with high levels of precision and efficiency. The algorithms that we develop use and extend theory from deep learning and neural networks, transfer learning, representation learning, nonconvex optimization, causal learning, reinforcement learning, and robust optimization. We aim to conduct cutting-edge and high impact research through full-stack approaches that encourage lab members with skills in algorithms, systems, statistics, mathematics and software to work closely together to solve critical and practical challenges in the areas at the intersection of AI+Systems.

At AISys, fruitful collborations and constant learning matters a lot to all of us. We have a culture where students frequently collaborate with each other. We typically combine theoretical and empirical insights to build a principled and thorough understanding of key techniques in machine learning, such as deep learning, as well as the challenges we face in this context. Currently, a major theme in our lab is to develop secure, robust, reliable, and performant machine learning systems.

Current Members

Ying Meng

Ying Meng phd

Ying is a PhD student in computer science. She is interested in adversarial machine learning and software testing.

Jianhai Su

Jianhai Su phd

Jianhai is a PhD student in computer science. He is interested in transfer learning, autonomic computing, and reinforcement learning.

Shahriar Iqbal

Shahriar Iqbal phd

Shahriar is a PhD student in computer science. He is interested in multi-objective optimization of deep neural networks in embedded systems.

Peter Mourfield

Peter Mourfield phd

Peter is a PhD student in computer science. He is interested in autonomic computing and reinforcement learning.

Mohammad Ali Javidian

Mohammad Ali Javidian postdoc

Mohammad Ali is a postdoctorate student in computer science. He is interested in probabilistic graphical models, Bayesian networks, and transfer learning.

Blake Edwards

Blake Edwards undergrad

Blake is a honors college undergraduate student in computer science and math. He is interested in deep neural network model compression and distillation.

Stephen Baione

Stephen Baione undergrad

Stephen is a honors college undergraduate student in computer science and math. He is interested in deep neural network model compression and distillation.