Using statistical and algorithmic techniques to give computer systems the ability to "learn" from data, without being explicitly programmed.
Protecting computer systems from theft or damage to their hardware, software or electronic data, as well as from disruption or misdirection of the services they provide.
Studying the theory, experimentation, and engineering that form the basis for the design and use of information, computation, and their implementation in computer systems.
Hi, I'm the founding faculty and research educator of FIRE Capital One Machine Learning, a FIRE: First-Year Innovation & Research Experience innovation & research stream experience at the University of Maryland.
FIRE Capital One Machine Learning is a year-long (2-3 semester) CURE: Course-based Undergraduate Research Experience that immerses first-year (new freshman, freshman connection, transfer) undergraduate students in faculty-led research and mentorship experience in machine learning.
We focus on helping students develop research and career-ready skills by training them to work on technical projects in the field of machine learning, deep learning, or artificial intelligence using recently developed techniques and perspectives, and apply them to market-relevant areas such as computer vision, natural language processing, automation, and data analytics.
Some of our recent machine learning projects include:
- 3D Object Detection and Localization for Autonomous Vehicles
- Object Recognition and Tracking for Surveillance Videos
- Extreme Image Compression from Learned Objects
If you are a prospective or newly admitted new freshman, freshman connection, or transfer student and would learn more about applying to join FIRE Capital One Machine Learning, please find the program application information here.
Upon the completion of the FIRE Capital One Machine Learning stream experience, students will also have the opportunity to become an accredited AMP peer mentor, and receive recommendation help them succeed in their next steps, such as be hired at a company and startup, be recruited as a student researcher, or be admitted as a graduate student at our university or beyond.
If you are prospective academic, industry, or government partner, and would like to collaborate with FIRE Capital One Machine Learning on a research project, or would like to provide sponsorship of your products or services, sponsorship of your funds, please find the collaboration and sponsorship information here.
Email: [email protected]
Location: 3136 A.V. Williams Building, University of Maryland, College Park