If you are interested in participating in research projects, please email me your resume and a short personal statement.

 

PhaNtoMouse – An Accessible Prosthetic Computer Interface

• Student Author/s: Sumanth Aluri and Arham Khan
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: This project aims to create a prosthetic to computer interface that allows the user to control the mouse cursor using a prosthetic. The key objectives are to make sure the solution is easy to use, accurate, and accessible for everyone. To do this we designed a system that packages a computer vision algorithm into a mobile app. The algorithm uses the phone’s camera to track how the user’s prosthetic moves. This data is then translated into mouse movements and sent to the target computer by the phone via Bluetooth. Altogether the solution is highly accessible to anyone with a smartphone as it does not require any extra hardware or purchases.

TweetPy

• Student Author/s: Christian Walk
• Undergraduate Research, EGN 4912
• Brief Description: This project concentrates on the development of automatic scripts for big data collection using Twitter API.

Generative Models for Continual Learning

• Student Author/s: Sambanna Krishnan
• Graduate Research, EEL 5905
• Brief Description: This project focuses on the implementation and development of generative models such as GANs and VAEs for synthetic text generation. Advancements to the current research were employment to provide semantic topic modeling in latent spaces.

Textify AI

• Student Author/s: Raymond Yu, Rafe Krase, Richard Liu, and Jeffrey Liang
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: This project implements a pipeline for video text summarization that relies upon a model that utilizes frame captioning and abstract text summarization techniques on short form video content.

Hardware for Horticulture Help (HHH)

• Student Author/s: Chandler Trousdale and Christopher Posada
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: Hardware for Horticulture Help (HHH) strives to provide an implementation that bridges the gap between hardware and biology. Utilizing microcontrollers and various sensors, HHH captures real-world data (light exposure, temperature, quantity of water, humidity) to train machine learning models that will predict and provide optimal feedback as to what the plant needs to promote the most efficient growth. The experimental results were acquired for specifically the green onion, or scallion, but the robust framework may serve as an excellent baseline for a variety of plants in the future.

Forecasting Walmart Sales with LSTM Recurrent Neural Networks

• Student Author/s: Natalia Lisiecka, Sarwaan Ansari, and Xhino Lita
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: This project used machine learning tools such as long-short-term recurrent neural networks and auto-regressive models to predict inventory stock from Walmart sales’ goods. This project was inspired by a Kaggle competition.

Stock Prices Forecasting

• Student Author/s: Yadi Qian
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: This project used machine learning tools such as long-short-term-memory networks and auto-regressive models to predict a variety of stock’s prices. A web interface was developed for users to visualize the stock price prediction, along with other summary statistics on model performance.

Continual Learning

• Student Author/s: Ritvik Palvankar
• Graduate Research, EEL 5905
• Brief Description: This work focused on the development of existing and new techniques to combat catastrophic forgetting with neural networks.

Sentiment Analysis and Recommender Systems

• Student Author/s: Pratiksha Sharma
• Graduate Research, EEL 5905
• Brief Description: This work focused on the development of machine learning models focused on natural language processing to perform sentiment analysis, topic modeling, recommender systems and generative modeling.

Better Code Search

• Student Author/s: Sydney Achinger
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: The Better Code Search project centers around education by providing an interactive tool to any student learning how to code. Better Code Search incorporates machine learning and a unique searching algorithm that adapts based on user feedback to offer beginner coders an easier way to find code snippet resources.

WoofCheck

• Student Author/s: Rahul Dani, Gal Levy, Christopher Hoyek, and Jonathan Peritz
• Undergraduate Senior Design Project, CIS/CEN 4914
• Brief Description: The WoofCheck project team developed a machine learning algorithm and mobile app to automatically classify more than 100 dog breeds.