2021 Capstone Projects
This project will utilize publicly available LiDAR data to estimate carbon stocks across The Conservation Fund’s nationwide portfolio of working forestlands. Students will create computational tools for processing NASA’s newest LiDAR data – Global Ecosystem Dynamics Investigation (GEDI) and utilize field data to validate and interpret data. In addition, students...
Saving Nature is a non-profit organization that works with local partners to purchase land and restore forests to connect habitat fragments in areas of high conservation concern. Part of this effort includes monitoring the area with camera traps. These camera traps can collect hundreds of images and videos each month...
The “small-watershed” ecology approach measures all precipitation chemistry (inputs) and stream solute fluxes (outputs) within a watershed. This has led to key environmental insights such as the discovery of acid rain. Currently, upwards of 150 different federally funded sites have implemented this watershed approach to evaluate site-specific questions about climate...
The goal of capstone project is to apply and extend custom analytics solutions to discover how life remains resilient in extreme environments. An explosion of data has resulted from recent discoveries of tiny single-celled life hiding out in the most extreme places on Earth. These single-celled creatures, or microbes, thrive...
Wild animals eaten by humans are known as “wild meat”, or “bushmeat” in sub-Saharan Africa. Hunting for bushmeat is both an ancient and modern practice, but as we step into the Anthropocene, bushmeat hunting has become unsustainable in many areas, threatening biodiversity and the food, financial, and cultural security of...
Wild animals eaten by humans are known as “wild meat”, or “bushmeat” in sub-Saharan Africa. Hunting for bushmeat is both an ancient and modern practice, but as we step into the Anthropocene, bushmeat hunting has become unsustainable in many areas, threatening biodiversity and the food, financial, and cultural security of...
This project examines a number of questions using raw data on course enrollment at Duke University. Questions range from how do grades impact the order of courses students take to are there certain courses that are bottlenecks for majors. A tangible product will be a recommendation engine for course suggestion...
This project will focus on a power service restoration problem in the design of the smart grids. Due to increasingly severe weather events and cyber-physical security threats, a more resilient and reliable power system is needed to ensure the continuous operation and availability of power applications and services. Traditionally, a...
Earth observation data such as satellite imagery offers great potential for better assessing and planning for vital infrastructure systems and increasing our understanding the flow of resources in our global society. Automated analysis of such data provide their greatest benefit when they are automated and deployed at scale, being able...
Investment banking and asset management use regular market summary updates to manage risk and exposure on all equity products across markets. These Market Risk data are variable in quality based on the user who develops them. This project will aim to derive key statistical insights from Market Risk data using...
This project will apply deep reinforcement learning to solve a vehicle routing problem (VRP). VRP is a typical problem in combinatorial optimization and operations research, and it has direct applications in logistics and supply chain. A solution to VRP determines what is the optimal set of routes (in terms of...
Malicious webpages will often display brand logos to feign legitimacy; however, these brand logos are often distorted from official versions. The goal of this project is to build a classifier that recognizes and identifies logos in a screenshot of a legitimate or malicious webpage. The classifier must also be able...
In today’s world, datasets are much larger and more complex and thus require new and innovative techniques to make reliable inferences. The data also reflect existing human biases and social inequalities, which are compounded by the use of algorithms and machine learning models. This can lead to unfair outcomes and...
The goal of this project is to find a better way of presenting data from an exercise tolerance test to enable the clinician to make more precise diagnoses and better understanding results of the test. The students will create a model for this test, showing the interaction between the three...
The goal of our team was to establish an automated ETL (Extract, Transform, Load) Pipeline that extracts raw wearable data (from Fitbit and Garmin APIs), transforms the data, and loads it to the PostgreSQL database (Covidentify Analysis Database) in Microsoft Azure. This repository is a mirror of the code that...
Since the 1980s, American schools have been steadily re-segregating, despite extensive research documenting the harms of this process. This is driven by factors such wealth and opportunity which are heavily correlated with race. However, research demonstrates that the socioeconomic makeup of a school may play a more significant role in...
Every election cycle, the use of digital advertising by U.S. political campaigns becomes more commonplace. The past few years have seen extensive public debate about the use of targeted digital advertising by political campaigns. Unlike other forms of political advertising, campaign ads in the digital sphere remain largely unregulated by...
Showing all 17 results