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PROFILE:

 

Bhaskar Saha

Bhaskar Saha joined PARC's intelligent automation team with an initial focus on applying Bayesian inference techniques expertise to classification, state estimation, and prediction problems — for intelligent system design and health management.

Before joining PARC, Bhaskar worked at NASA Ames Research Center as a research scientist at the Prognostics Center of Excellence. While there, he developed an integrated Bayesian framework to determine remaining-useful-life probability densities. He also built a hardware-in-the-loop testbed to benchmark his prognostic algorithm for a battery health management system for electric UAVs, which successfully provided real-time battery status and remaining useful life during multiple flight tests. With the goal of standardizing research in prognostics — and advancing the state-of-the-art — Bhaskar helped formulate a set of metrics tailored towards evaluating the performance of prognostic algorithms.

Dr. Saha received Ph.D. and M.S. degrees in electrical and computer engineering from Georgia Institute of Technology, and earned his bachelor's degree in electrical engineering from the Indian Institute of Technology in Kharagpur, India. In addition to organizing conferences and sessions for several IEEE events and the Prognostics and Health Management Society, Bhaskar won three best-paper awards. His other interests include photography, motorcycling, and woodworking.

 

PARC publications

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2014

A Simulation and Modeling based Reliability Requirement Assessment Methodology

26th International Conference on Design Theory and Methodology (DTM)

17 August 2014

SENSOR: embedded fiber optic sensing for accurate state estimation in advanced battery management systems

Materials Research Society Spring 2014 Symposium Q: : Materials, Technologies and Sensor Concepts for Advanced Battery Managemen

21 April 2014

Embedded Fiber Optic Chemical Sensing for Internal Cell Side-Reaction Monitoring in Advanced Battery Management Systems

Materials Research Society Spring 2014 Symposium Q: : Materials, Technologies and Sensor Concepts for Advanced Battery Managemen

21 April 2014

SENSOR: embedded fiber-optic sensing systems for improved battery management

Advanced Automotive Battery Conference 2014

3 February 2014

2013

Algorithm design for automated transportation camera image and video quality check modules

SPIE Conference on Electronic Imaging - Video Surveillance and Transportation Imaging Applications

3 February 2013

2012

Reference image-independent fault detection in transportation camera systems for nighttime scenes

IEEE Conference on Intelligent Transportation Systems 2012

16 September 2012