The following Oregon State University faculty members have expertise related to robotics and artificial intelligence and are willing to speak with journalists. Their specific expertise, and contact information, is listed below. For help with other OSU faculty experts, contact Sean Nealon, 541-737-0787, [email protected].

Thomas Dietterich, 541-737-1300, [email protected]

Dietterich is one of the founders of the field of machine learning. He frequently speaks about the potential dangers of AI and ways of making AI safe and robust, and his research is motivated by challenges ranging from weather station networks to computer security. The three main branches of his research are: How machine learning can provide the basis for building integrated intelligent systems; how people and computers can collaborate to solve challenging problems; how machine learning can assist in ecosystem management and other aspects of the ecological sciences. Among the specific areas that Dietterich can discuss:

  • Managing uncertainty and detecting novelty in machine learning applications
  • Automated data cleaning for sensor networks
  • Reinforcement learning in risk-sensitive applications

Alan Fern, 541-737-9202, [email protected]

Fern conducts research in the areas of artificial intelligence, machine learning, automated planning and control, and computer vision. His work is centered around making machines smarter by studying the critical computational problems that progress hinges on. Possible interview topics:

  • Algorithms that can learn to interpret complex data such as videos
  • AI techniques for anomaly detection
  • Techniques for integrating planning and machine learning
  • The complementary areas of machine learning, automated planning and knowledge representation
  • “Explainable AI,” i.e. getting the program to explain how decisions were reached

Bill Smart, 541-737-0670, [email protected]

Smart’s work centers around how robots and people interact, how we can integrate robots and automation into our daily lives, and how we can get robots to do useful work for long periods of time. He can answer questions about:

  • Privacy issues related to robotics and AI
  • Robots in the home and other assistive robots
  • Robots Robots related to health, including robots to combat infectious diseases

Kagan Tumer, 541-737-9899, [email protected]

Tumer is the director of OSU’s Collaborative Robotics and Intelligent Systems Institute, which advances the theory, design, development and deployment of robots and intelligent systems. The institute also explores public policy and ethical questions surrounding the deployment of robots and intelligent systems. Tumer’s own research focuses on AI; learning with multiple rewards, coordination in multiagent systems, and evolutionary algorithms for control and optimization. Among his potential interview areas:

  • Multirobot coordination
  • Intelligent robots
  • AI ethics
  • AI/robots in society

Houssam Abbas, 541-737-3617, [email protected]

Abbas’ research spans the design, control and verification of cyber-physical systems – in particular, he is interested in the development of lightweight verification and control techniques that can run onboard autonomous systems. He is also investigating distributed control algorithms for complex aerial missions. Among the topics he can talk about:

  • Security and safety of autonomous systems such as self-driving cars and drones, including F1/10 (miniature car) racing
  • Programming languages for medical devices

Cindy Grimm, 541-737-4914, [email protected]@oregonstate.edu

Cindy Grimm works in the area of robotic grasping and manipulation for both industry and agriculture, as well as ethics, law and policy related to robotics. Her previous projects include modeling the developing heart, understanding how the shape of bat ears influences their sonar patterns, 3D sketching, and interfaces for 3D medical image segmentation. Other areas of expertise include:

  • Computer graphics and human-computer interaction
  • The relationship between shape and biological function
  • Artistic-based modeling and visualization