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Events for September 21, 2017
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CS Colloquium: Dr. Kris Zacny (Honeybee Robotics) - Honeybee Robotics
Thu, Sep 21, 2017 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Kris Zacny, PhD, Honeybee Robotics Spacecraft Mechanisms Corporation
Talk Title: Honeybee Robotics
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Research Colloquium.
Honeybee Robotics, based in Pasadena, develops cutting edge robotic systems for solar system destinations such as the Moon, Mars, Venus, and comets. We are currently operating our hardware on the surface of Mars. Our technologies are also used for Oil & Gas, mining, and U.S. Special Forces.
The presentation will initially provide some background to space exploration and then introduce several exciting missions in the works. These include Lunar Resource Prospector with a goal of identifying volatiles at the lunar South Pole, Mars2020 mission with a goal of returning samples from Mars, Europa deep drill mission with a purpose of penetrating through >10 km thick ice crust and reaching subglacial ice, as well as Planetary Volatiles Extractor with a goal of mining the Moon and Mars.
We will also discuss various ways USC faculty and students could collaborate with Honeybee Robotics. Our company currently employs several USC alumni as well as interns, and works with USC professors on space technologies.
Biography: Dr. Kris Zacny is Vice President and Director of Exploration Technology Group at Honeybee Robotics in Pasadena. His expertise includes terrestrial and extraterrestrial robotic drilling, excavation, sample handling and processing, geotechnical systems, and sensors.
In his previous capacity as an engineer in the South African mining industry, Dr. Zacny managed numerous underground mining projects. Dr. Zacny received his PhD at UC Berkeley in Geotechnical Engineering with an emphasis on Mars drilling, and his ME at UC Berkeley in Petroleum Engineering with emphasis on Drilling and Materials Science. He received his BSc cum laude in Mechanical Engineering at U. Cape Town.
He has participated in several Arctic, Antarctic, Atacama, and Greenland expeditions. Dr. Zacny has over 200 publications related to extreme drilling and excavation and has managed over 100 technology projects. He has over 40 NASA New Technology Records and four NASA Group Achievement Awards.
Host: Computer Science Department
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CAIS Seminar: Dr. Ece Kamar (Microsoft Research) - Directions in Hybrid Intelligence: Discovering Blind Spots of AI
Thu, Sep 21, 2017 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Ece Kamar, Microsoft Research
Talk Title: Directions in Hybrid Intelligence: Discovering Blind Spots of AI
Series: Center for AI in Society (CAIS) Seminar Series
Abstract: Despite advances in AI, machines still have limitations in accomplishing tasks that come naturally to humans. When AI systems are fielded in the open world, these limitations cause concerns around reliability, biases and trust. In this talk, Dr. Kamar will argue that hybrid systems that combine the strengths of machine and human intelligence is key to overcoming the limitations of AI algorithms and developing reliable systems. She will provide an overview of multiple projects, which investigate how to integrate human intelligence into the training, execution and troubleshooting of AI systems.
Biography: Dr. Ece Kamar is a Senior Researcher in the Adaptive Systems and Interaction Group at Microsoft Research. She received her Ph.D. in computer science from Harvard University. Her work spans several subfields of AI, including planning, machine learning, multi-agent systems and human-computer teamwork and is inspired by real-world applications.
Host: Milind Tambe
Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
