Malware Attribution and Vision-based Gesture Recognition | February 26, 2014
“Malware Attribution and Vision-based Gesture Recognition”
What do Malware Attribution and Vision-based Gesture Recognition have in common? They are both highly challenging problems and are two of the dozens of active R&D programs at Charles River Analytics (www.cra.com). We will present our latest work in these areas and demonstrate the tools we are developing. We will also discuss the unique culture of Charles River Analytics that enables such a diverse set of R&D opportunities for both scientists and engineers.
JOB OPPORTUNITIES WILL BE DISCUSSED.
| Date: | Wednesday, February 26, 2014 |
| Time: | 5:00 – 5:45 pm |
| Location: | BU College of General Studies
871 Commonwealth Avenue, Boston, Room 511 |
| RSVP: | Contact Katherine Moran, MET College Enrollment Services at kcmeyer@bu.edu or (617) 358 -4610. Include name, BU ID, email address, and BU college/program. |
Guest Speakers
Mr. Curt Wu is Chief Software Engineer at Charles River Analytics and a part-time student at Boston University (MS Computer Science with Concentration in Security expected in 2014). Mr. Wu’s research interests are in network security, software trustworthiness, and cloud computing technologies. He has successfully led multidisciplinary teams in the development of innovative research programs for DoD, DHS, and NASA. Mr. Wu will provide an overview of Charles River Analytics and discuss career opportunities for BU students.
Mr. Lee Kellogg is a Software Engineer at Charles River Analytics. His interests and research focus on cyber security, malware detection and analysis, and military simulation-based training systems. He will be presenting his work as the software engineering lead for the Malware Analysis and Attribution using Genetic Information (MAAGI) effort, which applies functional semantics, probabilistic modeling, and techniques from evolutionary biology to identify the source and intent of new malware attacks as part of DARPA’s Cyber Genome program.
Mr. Camille Monnier is a Senior Scientist at Charles River Analytics. Mr. Monnier has an extensive background in machine learning and pattern recognition with an emphasis on object detection, recognition and tracking. He will be presenting his work as the Principal Investigator for MULE-F, an autonomous vision-based leader-follower system for mobile robots and TOPGUN, a vision-based system to track flight deck directors and automatically recognize their gestures. Both MULE-F and TOPGUN are collaborations with researchers at Boston University.