Advances in technology and science have spurred an increasing accumulation of complex data sources, leading modern researchers into a diverse present- day data revolution. The new tenor of data collection has created a two-part problem: historical models are often not malleable …
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People who analyze images of biological tissue often rely on segmentation of structures as a preliminary step. In particular, laboratories studying the rat brain manually delineate brain regions to position scientific findings on a brain atlas to propose hypotheses about the rat…
In this research, we propose to use deep learning to predict crimes in small neighborhoods (regions) of a city, by using historical crime data collected from the past. The motivation of crime predictions is that if we can predict the number crimes that will occur in a certain we…
Deep learning is a new area of machine learning in artificial intelligence that consists of networks to learn representations from data in a supervised, semi-supervised and unsupervised manner. Deep learning has a relatively long history, but it does not gain great attention unt…
Attempting to characterize, image or quantify the subsurface using geophysical data for exploration and development of earth resources presents interesting and unique challenges. Subsurface heterogeneities are the result of abstract paleo geological events, exhibiting variabilit…
This thesis is focused on Hand Pose Estimation from videos captured with wearable cameras. I first present a history of methods in solving this problem especially using convolutional neural networks. Then I will present my novel method for solving this problem, adaptive graph co…
Online social networks provide people with convenient platforms to communicate and share life moments. However, because of the anonymous property of these social media platforms, the cases of online hate speeches are increasing. Hate speech is defined by the Cambridge Dictionary…
Breast cancer frequently occurs in women over the world. It was one of the most serious diseases and the second common cancer among women in 2019. The survival rate of stages 0 and 1 of breast cancer is closed to 100%. It is urgent to develop an approach that can detect breast c…
Autonomous robots will soon play a significant role in various domains, such as search-and-rescue, agriculture farms, homes, offices, transportation, and medical surgery, where fast, safe, and optimal response to different situations will be critical. However, to do so, these ro…
This thesis explores reinforcement learning (RL) based approaches to create adaptive Medium Access Control (MAC) protocols that learn from past transmission history. As apposed to canonical RL algorithms, a policy tree is used to represent both the decision space and the environ…
Probabilistic models have a rich history in machine learning, offering a theoretical and practical framework for learning from observed data. Probabilistic models describe relationships between observed data and latent variables in terms of probability distributions. Practitione…
Gestational diabetes mellitus and hypertensive disorders in pregnancy are serious maternal health conditions with immediate and lifelong mother-child health consequences. These obstetric pathologies have been widely investigated, but mostly in silos, while studies focusing on th…
Binge drinking and non-suicidal self-injury are significant health-risk behaviors that are often initiated during adolescence and contribute to a host of negative outcomes later in life. Selective prevention strategies are targeted toward individuals most at-risk for developing …
Always-on sound classification is a desirable but power-intensive function for a variety of emerging applications such as wearables and IoT devices. The hardware energy consumption of sound classifiers is typically driven by signal digitization, feature extraction, classificatio…
Consumption binds the worlds of production and marketing to possession and ownership, satisfying the consumer’s functional wants and needs, but also fulfilling hedonic desires related to self-gratification and recreational aspiration. Across the last fifty years, growing consume…
In the modern world of Intelligent Transportation System (ITS), time headway is a key traffic flow parameter affecting ITS operations and planning. Defined as “the time difference between any two successive vehicles when they cross a given point”, time headway is used in various…
A deep neural network is a deep learning algorithm that uses artificial neural networks with multiple layers. The goal of a deep neural network is to learn a function from observation samples. In many real-world problems, this function is unknown and there is a need to learn it …
Early efforts to predict the spread of disease have been traced back to the 14 th century. Most notable in historical disease prediction is the Black Death which engulfed Europe from 1347 to 1351, killing an estimated 200 million people. Attempts to predict the spread of disease…
Field studies in ecology provide the basis for much of our insight into natural processes and the anthropogenic effects upon them. But the scale of inquiry, both spatial and temporal, and the speed with which questions can be posed and answered, is only partly driven by the proc…