RAPIDS Contributors¶
Currently, RAPIDS is being developed by the Mobile Sensing + Health Institute (MoSHI) but if you are interested in contributing feel free to submit a pull request or contact us.
Julio Vega, PhD¶
Postdoctoral Associate
Julio Vega is a postdoctoral associate at the Mobile Sensing + Health Institute. He is interested in personalized methodologies to monitor chronic conditions that affect daily human behavior using mobile and wearable data. In the long term, his goal is to explore how we can enable patients to inform, amend, and evaluate their health tracking algorithms to improve disease self-management.
Meng Li, MS¶
Data Scientist
Meng Li received her Master of Science degree in Information Science from the University of Pittsburgh. She is interested in applying machine learning algorithms to the medical field.
Kwesi Aguillera, BS¶
Intern
Kwesi Aguillera is currently in his first year at the University of Pittsburgh pursuing a Master of Sciences in Information Science specializing in Big Data Analytics. He received his Bachelor of Science degree in Computer Science and Management from the University of the West Indies. Kwesi considers himself a full stack developer and looks forward to applying this knowledge to big data analysis.
Echhit Joshi, BS¶
Intern
Echhit Joshi is a Masters student at the School of Computing and Information at University of Pittsburgh. His areas of interest are Machine/Deep Learning, Data Mining, and Analytics.
Nicolas Leo, BS¶
Intern
Nicolas is a rising senior studying computer science at the University of Pittsburgh. His academic interests include databases, machine learning, and application development. After completing his undergraduate degree, he plans to attend graduate school for a MS in Computer Science with a focus on Intelligent Systems.
Nikunj Goel, BS¶
Intern
Nik is a graduate student at the University of Pittsburgh pursuing Master of Science in Information Science. He earned his Bachelor of Technology degree in Information Technology from India. He is a Data Enthusiasts and passionate about finding the meaning out of raw data. In a long term, his goal is to create a breakthrough in Data Science and Deep Learning.
Agam Kumar, BS¶
Research Assistant at CMU
Agam is a junior at Carnegie Mellon University studying Statistics and Machine Learning and pursuing an additional major in Computer Science. He is a member of the Data Science team in the Health and Human Performance Lab at CMU and has keen interests in software development and data science. His research interests include ML applications in medicine.