The team-based projects are industry-inspired and conducted under the mentorship of a faculty member. You will earn between 3-6 credits for your project work – its pace, start time, final report format, and appropriate credit hours will be decided in consultation with your project mentor and sponsor.
In order to replicate real-world scenarios and implications, M.Eng. projects will be team based and incorporate a financial analysis and feasibility study component. This requirement, based in project management principles, builds your skills in teamwork, leadership, effective communication skills and design aspects of industrially-relevant processes and products.
Recent M.Eng. Projects
Artificial Intelligence and Machine Learning for Molecular Design
Faculty Sponsor: Fengqi You
The optimal design of compounds through manipulating properties at the molecular level is often the key to considerable scientific advances and improved process systems performance. Despite century-long efforts in chemical synthesis and the large set of synthesized molecules (~107), the so-called chemical space is still an unexplored galaxy with an estimated number of small organic molecules populating the space of more than 1060. This project focuses on computer-aided molecular design using machine learning techniques, such as variational autoencoders, generative adversarial networks, self-supervised learning, and reinforcement learning.
Cornell Campus as a Living Laboratory for Renewable Energy Transition
Faculty Sponsor: Fengqi You
Cornell University campus aims to be Carbon Neutral by 2035. To support this renewable energy transition, hybrid energy systems should be integrated, designed and optimized to satisfy the campus-wide demand on electricity, heat and cooling. This project aims to deliver energy systems analysis and optimization methods and insights to support the renewable energy transition of the campus. The campus energy systems will also provide a living laboratory for this study.
Development of an Application Programming Interface (API) for Real Time Financial Data in the Julia Programming Language
Faculty Sponsor: Jeff Varner
Data driven stock and currency trading approaches require access to high quality financial data streams. Unfortunately, there are only a limited number of free or low cost vendors for this type of data. One such vendor is Alpha Vantage, a leading provider of free APIs for realtime and historical data on stocks, forex (FX), and digital/crypto currencies that provides intraday, daily streams along with a large number of technical indicators. However, while Alpha Vantage is free it does require fairly detailed knowledge of web-based programming approaches. Toward this challenge, in this project, we will develop a wrapper around the Alpha Vantage API that allows users to access the data stream without having to directly make the web-based API calls. In addition, this wrapper should transform the raw data produced by the Alpha Vantage into a common format that is easier to work with. This wrapper will be written in the Julia Programming Language, a modern high performance computing language developed at MIT [1] that is gaining popularity in the financial community, including the Federal Reserve Bank of New York [2]. The Julia framework developed on this project will be published as a Julia package under an MIT software license, and released to the financial technology community via GitHub and released on arXiv.org. Taken together, this project offers students training in the development of application programming interfaces (APIs), the Julia programming language, realtime financial data streams and financial modeling approaches.
Reducing U.S. Children’s Antibiotic Exposure via Non-Invasive Immune Therapy
Faculty Sponsor: Rong Yang
Assess the market viability and perform a techno-economic analysis of a nanodelivery platform developed at Cornell to realize a one-dose, non-invasive treatment of acute otitis media (AOM). AOM is the primary reason for pediatric antibiotic usage, accounting for 24% of the antibiotic prescriptions written to U.S. Children. An estimated 19.5 million AOM cases in the U.S. each year led to an annual cost of $3-4 billion from outpatient visits, emergency department/urgent care visits, and hospitalization. Globally, ~ 80% of all children experience at least one episode of AOM by school age, making AOM the most common reason for pediatrician visits around the world. The Yang Lab at Cornell CBE has developed a fresh concept to target the delivery of antibiotics to the infected middle ear. Teams working on this project identify market viability, analyze the regulatory landscape, and design a scalable production process.