Sensing and Modeling in Interactive Virtual Reality Environment – Part-time RA, Fall 2022
** Priority will be given to current Ph.D. students and master’s students with clear intent to pursue Ph.D. degree. Interested student may apply through this link. Only qualified students will be contacted. Please do not email Dr. Chen directly.
** The RA will be paid with a stipend at department standard, no tuition waiver, no health, with in-state tuition benefit
Our lab is looking for a part-time RA who will work about $10 hours/week to support a data science/ML/AI project using sensing data collected from the interactive VR while participants choose food items from a virtual buffet, which is modeled after UMBC’s True Grit Cafeteria. The over-arching goal of the project is to characterize the decision-making process in food choices using sensing data. This is part of the larger effort in using VR technology to support the development of healthy eating habits among young adults. A large corpus of multimodal densely-sampled data streams was collected and available for analysis and modeling. This dataset includes (1) Neuro signals from fNIRS devices; (2) biophysical signals (e.g. heart rate and skin conductance) from ECG and GSR sensors.
Additional information about this project can be found here.
- Conducting exploratory data analysis and visualization of multimodal model signals
- Data cleaning for artifact detection and removal
- Build machine learning/statistical models to understand the dynamics and heterogeneity of neuro-biophysical signals
- Contribute to the writing manuscript for publication
- Conduct a relevant literature review
- Support ongoing data collection efforts, as needed
- Highly motivated and focused with strong work ethics
- Strong background in data science/machine learning/AI methodology (at the level of IS 733), and deep learning
- Hands-on experience with working with real-world data, ideally with a massive amount of multimodal/multivariate time series data
- Excellent communication skills (with data), oral and written
- Can work productively in a team
- Thrive in working with an unstructured and open-ended problem
- Detail-orientated and great organization/time management skills
- Curious and a life-long learner