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Spring 2020

Fei Wang

In the field of metabolomics, mass spectrometry (MS) is the most widely adopted method for identifying metabolites. Conventionally, metabolite identification involves matching the target mass spectrum against experimentally acquired reference mass spectral libraries. However, the limited coverage...

Fall 2023

Kearney, Alexandra K

Of all the capabilities of natural intelligence, one of the most exceptional is the ability to expand upon and refine knowledge of the world through subjective experience. Therefore, a longstanding goal of Artificial Intelligence has been to replicate this success: to enable artificial agents to...

Spring 2023

Ashrafi Asli, Seyed Arad

With machine learning models becoming more complicated and more widely applied to solve real-world challenges, there comes the need to explain their reasoning. In parallel with the advancements of deep learning methods, Explainable AI (XAI) algorithms have been proposed to address the issue of...

Fall 2022

Vega Romero, Roberto Ivan

Machine learning has the potential to help medical experts to deliver better healthcare. There are, however, important technical challenges that need to be solved before we can develop reliable models for clinical practice, including: (1) Limited number of labeled instances, (2) Uncertainty of...

Fall 2021

Mei, Jincheng

The optimization of non-convex objective functions is a topic of central interest in machine learning. Remarkably, it has recently been shown that simple gradient-based optimization can achieve globally optimal solutions in important non-convex problems that arise in machine learning, including...

Spring 2021

Samuel, Hamman W

It has gotten increasingly harder for laypersons to determine the veracity of online health information. This is because of the explosion of content in health social media, allowing anyone with an Internet connection to create and propagate health-related content. This includes both innocuous and...

Fall 2019

Sajed, Touqir

We present two provably optimal differentially private algorithms for the stochastic multi-arm bandit problem, as opposed to the private analogue of the UCB-algorithm (Mishra and Thakurta 2015; Tossou and Dimitrakakis 2016) which doesn’t meet the recently discovered lower-bound of Ω( K log(T) /...

Spring 2019

Stanescu, Adrian M

For many years, traditional boardgames such as Chess, Checkers or Go havebeen the standard environments to test new Artificial Intelligence (AI) algorithms for achieving robust game-playing agents capable of defeating the best human players. Presently, the focus has shifted...

Fall 2024

Zhang, Shupei

Perceptual factors in vision can facilitate the development of more effective multimedia algorithms. In particular, the wide dynamic range of the human vision system is a motivation for developing image lighting enhancement algorithms. Image lighting enhancement can be achieved by capturing...

Fall 2023

Krishna Guruvayur Sasikumar, Aakash

The application of reinforcement learning (RL) to the optimal control of building systems has gained traction in recent years as it can reduce building energy consumption and improve human comfort, without requiring the knowledge of the building model. However, existing RL solutions for building...