The cutting edge of large scientific experiments is the generation of petabytes and exabytes of data. Such large volumes of data require advances in computing, networking, software and storage. Spinoffs to engineering and business apllications should follow.
For the past 30 years work at Stony Brook has developed a very tractable model of scheduling divisible (partitionable) loads. The methodology is very well suited to integrating communication and computation issues. A world wide publication list on this topic up to 2014 is available at this web site.
A research effort into electric and other energy systems, Prof. Robertazzi was a co-P.I. on the Stony Brook Smart Grid Corridor project funded by LIPA and DOE.
- Y. Gao, J. Chen, T.G. Robertazzi and K. Brown, "Reinforcement Learning Based Schemes to Manage Client Activities in Large Distributed Control Systems, " Physical Review Accelerators and Beams, accepted in November 2018 for publication.
- P. Chitnis, T.G.Robertazzi, K.A. Brown, C. Theisen, "Quantitative Fault Tree Analysis of the Beam Permit System Elements of Relativistic Heavy Ion Collider (RHIC) at BNL," Proceedings of ICALEPCS2013, San Francisco, CA, USA
- P. Chitnis, T.G.Robertazzi, K.A. Brown, "A Monte Carlo Simulation Appraoch to the Reliability Modelling of the Beam Permit System of Relativistic Heavy Ion Collider (RHIC) at BNL," Proceedings of ICALEPCS2013, San Francisco, CA, USA
- P. Chitnis, T.G.Robertazzi, K.A. Brown, "Understanding the Failure Characterictics of the Beam Permit System of RHIC at BNL," Proceedings of ICALEPCS2015, Melbourne, Australia
- P. Chitnis, K.A.Brown, "Nonlinear System Identifiaction of Superconducting Magnets of RHIC at BNL," Proceedings of ICALEPCS 2015, Melbourne, Australia (K. Brown was BNL advisor and T. Robertazzi was Stony Brook advisor)
- P. Chitnis, K.A.Brown, "Bayesian Reliability Model for Beam Permit System of RHIC at BNL, " Proceedings of ICALEPCS 2015, Melbourne, Australia (K. Brown was BNL advisor and T. Robertazzi was Stony Brook advisor)
K. Wang, S. Skiena and T. G. Robertazzi, "Phase Balancing Algorithms", Electric Power Systems Research, vol. 96, Mar 2013, pp. 218-224.
K. Wang, S. Skiena, and T. G. Robertazzi, "Optimal Phase Balancing using Dynamic Programming with Spatial Consideration", Stony Brook University, CEAS Technical Report 840, October 12, 2017
US Patent 9,728,971 "Apparatus and Method for Optimal Phase Balancing using Dynamic Programming with Spatial Consideration" S. Skiena, K. Wang and T.G. Robertazzi, issued Aug 8, 2017
This research seeks to gain an understanding of the fine structure of Markov chains, particularly in terms of conditions leading to tractable product form solutions. Its major successes were in (1) relating Markov chain structure and labeling to the chain flow structure and product form solutions (2) a new family of stochastic Petri net with product form solution (3) identifying recursive structure in certain non-product form queueing models leading to efficient solutions for equilibrium probabilities and (4) identifying a simple flow structure for non-product form networks.
Prof. Robertazzi was the faculty director of the Science and
at Stony Brook for about 13 years. This was an academic unit in the O'Neil residence hall that offered courses, minors and hosted speakers to bring an academic dimension to residential life. In fact over 150 speakers in science, engineering, the liberal arts and medicine gave presentations during Prof. Robertazzi's tenure as faculty director. Two minors, one in interdiscplinary science and engineering and one in technical leadership, were available to all Stony Brook undergraduates. Due to budgetary problems, the Center is now inactive. For his work in the Living Learning Center, Prof. Robertazzi received the Long Island IEEE section Papoulis Outstanding Educator Award in 2012. Engineering Living Learning Center
Phone: (631) 632-8412/8400
Fax: (631) 632-8494
Email: Thomas dot Robertazzi AT stonybrook dot edu
Last modified December, 4, 2018