Skip to:

Special Seminar: Machine Learning and Uncertainty Quantification research at United Technologies Research Center

Presenters: Dr. Andrzej Banaszuk, Dr. Kishore Reddy, Dr. Tuhin Sahai, and Dr. Tong Sun

Abstract: We will present a broad overview of UTRC’s Systems Department research with particular focus on the areas of robotics, intelligent systems, machine learning, and advanced uncertainty management methods. The research, conducted by a diverse team of researchers in robotics, dynamical systems, control, applied mathematics, computer vision, machine learning, and human factors (in partnership with several leading universities including CMU, MIT, UPenn, and UC Berkeley) includes:

  • The cutting edge predictive and prescriptive analytics to automate decision processes and optimize human-machine efficiency for aerospace engineering, smart building and digital manufacturing. We will also present how we apply the state-of-art deep learning techniques to tackle the challenges in relevant industrial domains. 
  • The scalable algorithms and framework for uncertainty quantification and graph analytics. We leverage a combination of distributed graph clustering and adaptive waveform relaxation. Then we explore extensions to scalable inference for rare events in a Bayesian setting. We will give a short overview of our work on efficient algorithms for structure learning of Bayesian networks that is inspired from the efficient computations for NP-hard problems.

We will conclude with research problems of interest to UTRC and discuss existing and future career and internship opportunities in the broad area of robotics and machine learning.  

Speakers Bios: 

Dr. Andrzej Banaszuk is a Director of Systems Department at the United Technologies Research Center. Before his current appointment he was a Program Leader of Autonomous and Intelligent Systems and Sikorsky Program Offices at UTRC. Since joining UTRC in 1997, he has conducted research in analysis, design, and control of dynamical systems applied to jet engines, rotorcraft, electric power networks, and buildings. Since 2000 he has led collaborative multi-university research teams in the area of flow control, control of combustion instabilities, robust design of large uncertain dynamic networks, and autonomy. He is an author of 44 journal papers, 71 conference papers, and 9 patents. For his work on active and passive control of flow instabilities in jet engines he received IEEE Controls Systems Technology Award in 2007. He became an IEEE Fellow in 2011. He was elected to the Connecticut Academy of Science and Engineering in 2015. He holds Ph.D. in EE from Warsaw University of Technology and Ph.D. in Mathematics from Georgia Institute of Technology. 

Dr. Kishore Reddy is a Staff Research Scientist at the United Technologies Research Center (UTRC) working in the area of computer vision, human machine interaction (HMI) and machine learning. He is currently leading the Data Analytics initiative at UTRC primarily focusing on Deep Learning applications in aerospace and building systems to perform outliers and anomalies detection, multi-modal sensor fusion and data compression. He is also working with Department of Homeland Security (DHS) to develop algorithms for continuous authentication of mobile devices. Kishore earned his Ph.D. in 2012 from University of Central Florida, where he developed advanced video and image analysis algorithms, primarily segmentation and classification approaches, for multiple contracts funded by DARPA, IARPA and NIH. 

Dr. Tuhin Sahai is a Principal Research Scientist at the United Technologies Research Center (UTRC), broadly interested in the design, analysis and uncertainty quantification of complex systems. At UTRC, Tuhin has served as a principal investigator on multiple DARPA programs. In 2013, he was invited by the National Academy of Engineering to attend the Frontiers of Engineering Symposium. Furthermore, he was awarded the Grainger Foundation Frontiers of Engineering (FOE) grant by the National Academy of Engineering in 2014. Tuhin earned his Ph.D. in January 2008 from Cornell University, where he was a McMullen Fellow and won the H.D. Block teaching award. He received his Masters and Bachelors in Aerospace Engineering from the Indian Institute of Technology, Bombay in 2002.

Dr. Tong Sun is Group Leader for Decision Support & Machine Intelligence at the United Technologies Research Center. Her research portfolio includes using large-scale text and graph analytics to understand user behavior and social influence, applying deep neural network, active learning and online stream analytics to uncover actionable insights from heterogeneous data in distributed computing environments. Tong held 22 US Patents and co-authored over 35 peer-reviewed publications. She earned her Ph.D. in Distributed and Parallel Computing from University of Rhode Island in 1996. She is also an accomplished research thought-leader and technology innovator with 10+ years proven track of leadership in incubating new concepts through state-of-art machine learning methods/tools, developing advanced rapid prototypes that lead to impactful outcomes.

Date: 
Tuesday, March 7, 2017 -
12:30pm to 1:15pm