Kevin successfully defended his PhD thesis
Kevin Leahy successfully defended his PhD thesis titled Multi-Agent Persistent Surveillance under Temporal Logic Constraints
Calin elevated to IEEE Fellow
effective 1 January 2017, with the following citation:
"for contributions to automated control synthesis and robot motion planning and control".
6 papers accepted at 55th CDC from HyNeSs group
6 papers from the HyNeSs Group have been accepted at the 55th Conference on Decision and Control:
Derya Aksaray, Austin Jones, Zhaodan Kong, Mac Schwager, Calin Belta, Q-Learning for Robust Satisfaction of Signal Temporal Logic Specifications, 55th IEEE Conference on Decision and Control, Las Vegas, NV, 2016 (to appear)
Sadra Sadraddini, Calin Belta, Feasibility Envelopes for Metric Temporal Logic Specifications, 55th IEEE Conference on Decision and Control, Las Vegas, NV, 2016 (to appear)
Cristian Ioan Vasile, Kevin Leahy, Eric Cristofalo, Austin Jones, Mac Schwager, Calin Belta, Control in Belief Space with Temporal Logic Specifications, 55th IEEE Conference on Decision and Control, Las Vegas, NV, 2016 (to appear)
Demarcus Briers, Iman Haghighi, Douglas White, Melissa Kemp, Calin Belta, Pattern Synthesis in a 3D Agent-Based Model of Stem Cell Differentiation, 55th IEEE Conference on Decision and Control, Las Vegas, NV, 2016 (to appear)
Sadra Sadraddini, Calin Belta, Safety Control of Monotone Systems with Bounded Uncertainties, 55th IEEE Conference on Decision and Control, Las Vegas, NV, 2016 (to appear)
Iman Haghighi, Sadra Sadraddini, Calin Belta, Robotic Swarm Control from Spatio-Temporal Specifications, 55th IEEE Conference on Decision and Control, Las Vegas, NV, 2016 (to appear)
Calin is awarded the inaugural Tegan Family Faculty Fellowship
”The Tegan Family Distinguished Faculty Fellow honors a mid-career (Associate to early Full Professor) faculty for extraordinary performance and impact in research, teaching and service to the College and profession. The Distinguished Faculty Fellow is an honor awarded to tenured faculty who are on a clear trajectory to extraordinary leadership careers in all dimensions of engineering science and education.”
For more information see:
http://www.bu.edu/systems/2016/04/11/congratulations-to-calin-belta-inaugural-holder-of-the-tegan-family-distinguished-faculty-fellowship/
Cristian begins Postdoc position at MIT
Cristian-Ion Vasile successfully defended his PhD thesis, and has moved on to a postdoc position at MIT.
Cristian successfully defended his PhD thesis
Cristian-Ioan Vasile successfully defended his PhD thesis titled Motion Planning and Control: A Formal Methods Approach
Derya is moving to a postdoctoral position at MIT
Derya Aksaray is moving to a postdoctoral position at MIT: Computer Science and Artificial Intelligence Laboratory.
BU Robotics Lab in New Scientist
The new BU Robotics Lab was featured in the January 30 issue of New Scientist. The full article is available at https://www.newscientist.com/article/2075364-future-delivery-drones-start-learning-how-to-fly-on-their-own/
BU-led NSF CPS Frontier grant
We bring together synthetic biology and micron-scale robotics to engineer the emergence of desired behaviors in populations of bacterial and mammalian cells. This project is supported by a National Science Foundation (NSF) five-year, $4.5 million Cyber-Physical Systems Program (CPS) Frontier grant.Drawing on experts in control theory, computer science, synthetic biology, robotics and design automation, the team includes Professor Calin Belta (ME, ECE, SE), the lead principal investigator, and Assistant Professor Douglas Densmore (ECE, BME, Bioinformatics) from the BU College of Engineering; University of Pennsylvania Professor Vijay Kumar; and MIT Professor Ron Weiss, who directs the Institute’s Synthetic Biology Center; and members of SRI International.
NSF press release
http://nsf.gov/news/news_summ.jsp?cntn_id=135105&org=NSF&from=news
BU COE press release:
http://www.bu.edu/phpbin/news-cms/news/?dept=666&id=62547
Collaboration with DENSO Corporation, Japan on anomaly learning and monitoring for automotive systems
Anomaly detection is the problem of finding patterns from data that do not conform to “expected” or “normal” behavior. Anomaly detection has been used in a wide range of applications, such as intrusion detection for cyber-security, fault detection in safety critical systems, video surveillance of illicit activities, and maritime surveillance. In this project, we focus on automotive applications, where there seems to be a particular need for systems that can automatically monitor, detect, and respond to such behaviors. To this goal, we bring together concepts and tools from formal methods and machine learning.
