Technology is woven into our lives, and machines are playing a larger role in society. Scientists are creating intelligent machines that think and work more like people. Today, artificial intelligence systems are vital in many fields, including medicine, agriculture, and education.
Our educational programs help students prepare for new discoveries and work in a post-pandemic world.
Mason Engineering has robust course offerings in artificial intelligence (AI) and machine learning, including a concentration in machine learning for students earning a master's degree in computer science.
Our students work on real-world problems and apply theoretical processes, which prepare them for the work challenges they will face after graduation. Our industry partners provide internships, capstone projects, competitions, and research opportunities that reinforce classroom instruction and application of AI techniques to pressing problems.
Student opportunities include:
- Research projects under the supervision of numerous Computer Science (CS) and Information Sciences and Technology (IST) faculty who work in the field.
- A data mining course which incorporates competition-based learning where students engineer predictive solutions for problems related to text classification, drug activity monitoring, and image recognition.
- A 10-week summer program called Research Experience for Undergraduates in Educational Data Mining, sponsored by the National Science Foundation.
Credentials and Certificates
We make sure our students, regardless of their chosen major, have the opportunity to become proficient in a technical field. Options include:
- A Data Analysis Credential for non-engineers/computing majors. By partnering with the Greater Washington Partnership, we provide students who are studying humanities, communications, accounting, human resources, and policy an opportunity to gain expertise in data analytics and cybersecurity.
- A Business Analytics Graduate Certificate, which prepares students to use AI-based techniques for businesses.
- In fall 2020, we will launch credentials in Cloud Computing and Data Analytics.
Mason's exploration of AI includes research on theory, technology, and applications of computer systems, such as visual perception, speech recognition, decision-making, and translation between languages. But we don't stop there.
Mason’s AI research portfolio serves as a rich training ground for undergraduate and graduate students. It informs our curriculum and ensures that what we are teaching will be relevant and useful now and in the future.
Artificial intelligence and machine learning impact many scientific disciplines. By embracing this trend, Mason has become a leader in geospatial computing, agriculture, computational biology, neuroscience, and climate science. Our high-quality research receives funding from many government agencies, and our dedicated research centers and initiatives are constantly expanding.
Our research and educational opportunities are enriched by our numerous multi-disciplinary centers and labs.
Centers and Labs
The Autonomous Robotics Laboratory does collaborative research in a variety of topics involving robotics, computer vision, and networks, including:
- Multi-robotics and swarm robotics
- Multi-agent learning and stochastic optimization
- Swarm simulation
- Distributed sensor networks and mobile sensor networks
- Computer vision, tracking, situated vision, and multi-robot vision
The joint Center for Intelligent Spatial Computing (CISC) focuses on geospatial information interoperability, high-performance geospatial information processing, geospatial pattern analysis, and spatial GEOSS.
Phil Yang, director
The Center for Spatial Information Science and Systems (CSISS) is an interdisciplinary research center chartered by the provost and affiliated with the College of Science.
CSISS Research Foci:
- Theory and methodology of spatial information science
- Standards and Interoperability of spatial data, information, knowledge, and systems
- Architecture and prototype of widely distributed large spatial information systems, such as NSDI, GSDI, and GEOSS, as well as service-based spatial knowledge and decision-making systems
- Exploration of new information technologies that have potential applications in Spatial Information Science (SIS)
- The applications of SIS in the social sectors having either national interests or major commercial values, such as renewable energy, location-based mobile services, intelligent transportation, and homeland security
Liping Di, director
The DMML lab works on a variety of machine learning topics including:
- Anomaly detection
- Data mining for genomics and bioinformatics
- Time-series and spatio-temporal pattern discovery
- Text mining and information retrieval
The Evolutionary Computation Laboratory consists of a group of faculty, students, and affiliated scientists and engineers who conduct theoretical and applied research in the area of Evolutionary Computation.
The Learning Agents Center conducts basic and applied research on the development of cognitive assistants that learn complex problem-solving expertise directly from human experts, support experts and non-experts in evidence-based problem solving and decision making, teach their problem-solving expertise to students.