Jibonananda Sanyal

Jibonananda Sanyal

Team Leader and Staff Scientist


Jibo leads a select team of ~20+ individual researchers to provide their vision and leadership to define and align their activities with the projects, the group, and the division science agenda. He brings a unique blend of computer science with applications in geosciences, technical, institutional, and strategic leadership with a track record of technology development, commercialization, and national recognition. His research falls at the intersection of high performance computing leaning towards the exascale, extreme scale data and analytics, simulation and modeling, visualization, scalable machine learning, and sensors and controls building both research and operational systems. The applications are many: geographic information sciences, climate, IAV research, situational awareness, large scale image processing, multi-scale and multi-resolution simulation and modeling in buildings, transportation, controls, across simulations, and agent-based models. His prior research focused on visualization techniques and creating operational tools for meteorological and hydrological ensemble simulations. He has a strong interest in devising sustainable solutions that bridges disciplines and requires synergy across energy, water, geophysical, and anthropomorphic processes in our environment at local, regional, and global scales.

The specific applications are many: GIS, climate, IAV research, situational awareness, remote sensing, urban-science, multi-scale and multi-resolution simulation and modeling, building energy modeling, transportation, model-predictive control, as well as agent-based models.

Leading the group’s multi-petabyte image processing needs and defining the growth strategy for future hardware, software, and scalable computational needs. This includes architecting multi-objective workflows across multiple clusters and strategies to scale to the Titan supercomputer and beyond.


Knoxville Business Journal’s 40 under 40 honoree , 2018

Significant Event Award, "Seamless transition of EAGLE-I from DOE HQ to ORNL", December 2016

"Original 6 Trailblazers", Oak Ridge National Laboratory, October, 2014.

"Lightning Talks", Plenary Session, XSEDE, San Diego, July 2013

Outstanding Research Award, Geosystems Research Institute, 2011

Graduate Student of the Month of August 2010, CSE, Mississippi State University, 2010

3rd Position, Posters, Northern Gulf Institute Annual Conference, 2010

Best Overall Award, Photo Contest, Northern Gulf Institute Annual Conference, 2009

Best Poster Award, IEEE Visweek, 2008

10th Rank in B.Tech. Computer Science and Engineering, 2005 (class of 38)

1st Rank and Gold Medal in B.Sc. Computer Science, 2001 (class of 45)

Gold Medal for the Best Graduate Award, 2001 (in about 5000 university students)


EAGLE-I: Serving as the program manager for EAGLE-I, DOE’s operational situational awareness tool for the energy sector, and provides high-resolution real-time data of the sub-sectors of electricity, oil and natural gas, petroleum, and coal resources. EAGLE-I is used by FEMA, DHS, USDA, and several other federal, state, and local agencies to deliver the emergency response function for the nation.

Exascale Systems to build the Metropolitan Systems Energy and Economic Dynamics (Metro-SEED) Framework: Cities comprise many interdependent, interconnected, critical infrastructures, and human systems, many of which are modeled individually, but in order to optimize the design, planned evolution, and operation of cities, it is essential that we not only characterize these systems and processes, but also understand how they interact. Coupled multi-scale models to combine localized weather, human activity to inform agent-based transportation model, the resulting building energy models, and governed by socio-economic drivers, are being used to facilitate this discovery process. This is multi-DOE lab effort and I serve as the ORNL technical lead.

Energy-Water Nexus Knowledge Discovery Framework: To meet this need of the energy-water nexus (EWN) community, an Energy-Water Knowledge Discovery Framework (EWN-KDF) is being built  accomplish the objective of creating a robust data management and geovisual analytics platform that provides access to disparate geospatial Earth science and critical infrastructure data, socioeconomic data, and emergent ad-hoc sensor data, and to provide a powerful toolkit of analysis algorithms and compute resources to empower user-guided data analysis and inquiries. Serving as the Co-PI and systems lead.

Global Accelerated Settlement Discovery: The objective of this effort is to deliver a suite of high performance machine learning and specifically deep learning model training and prediction strategies, effective data management at the pre-exascale, and super-efficient image data workflows to support the need to accelerate global scale human settlement knowledge discovery using very high resolution (0:5 m) imagery for various humanitarian as well as intelligence needs. Serving as the PI. This includes a 25 million core hours allocation on the Titan supercomputer.

Lab-Corps Team-Tunation: Entrepreneurial Lead of ‘Team Tunation’ in DOE’s 7-week technology incubator program aimed at developing a viable business model from DOE funded research.

Modernizing the AMO Software Suite: Overhauling the software suite for DOE’s Advanced Manufacturing Office to use latest software development tools and techniques to create cross-platform software. The final suite will operate on desktop, web, as well as tablet devices across different operating systems. Served as PI.

IGATE-E CHP: Development of web-based national scale analytics to understand the potential and opportunities of using combined heat and power generation. Served as an investigator.

OpenStudio Results Framework: Development of an interoperable results schema for EnergyPlus simulation engine for interoperability. Served as the PI.

Autotune: A methodology for calibrating building energy models (BEM) is aimed at developing an automated BEM tuning methodology that enables models to reproduce measured data such as utility bills, sub-meter, and/or sensor data accurately and robustly by selecting best-match E+ input parameters in a systematic, automated, and repeatable fashion. Big-data management and data movement of about 270 TB+ was undertaken and a web interface to enable data access from the database was made in addition to creating dashboards for simple visual analytics. Served as an investigator.

XSEDE and OLCF computational allocation for Autotune: Massively parallel simulations using competitively allocated HPC resources from the Extreme Science and Engineering Discovery Experiment (XSEDE) and the Oak Ridge Leadership Computing Facility (OLCF). Machines include Nautilus and Kraken from the National Institute of Computational Sciences, Gordon at the San Diego Supercomputer Center, Blacklight at the Pittsburg Supercomputer Center, Wrangler at the Texas Advanced Computing Center, and Titan at the OLCF. Served as Co-I.

Roof Savings Calculator: Department of Energy’s advanced roof and attic simulation calculator to enable comparisons of energy saving retrofits for roofs.

Provenance Data Management: Creation of provenance enabled data management for real-time sensor data from ORNL's Flexible Research Platforms (FRP), including web-enabled visualization of the provenance graph and interactive exploration of the FRP models. Architected multi-level authentication with individual user permissions with a de-coupled, multi-system database architecture.

Modbus XML schematization for seamless interoperability: Development of interoperable schemas for interoperability of sensors and controls based on the Modbus Protocol.

Volttron Agent Development: Development of control agents for device control and data archival on the Volttron platform. Investigation includes scalability studies of the platform.

Others: EnergyPlus – whole building energy simulation engine enhancements, OpenStudio Refrigeration module design, and web-enabled heat-pump design simulation model, Flexible Research Platforms data architecture, consolidation, and readiness.


Selected publications:

Evaluation of “Autotune” calibration against manual calibration of building energy models, G Chaudhary, J New, J Sanyal, P Im, Z O'Neill, V Garg, Applied Energy, 2016

Eric Ragan, Alex Endert, Jibonananda Sanyal, and Jian Chen, “Characterizing Provenance in Visualization and Data Analysis: An Organizational Framework of Provenance Types and Purposes”, In IEEE Transactions in Visualization and Computer Graphics, pp. 31-40, 22(1), 2015.

James Nutaro , David Fugate , Teja Kuruganti , Jibonananda Sanyal , Michael Starke, “Cost Effective Retrofit Technology for Reducing Peak Power Demand in Small and Medium Commercial Buildings”, In Science and Technology for the Built Environment, 2015, doi:10.1080/23744731.2015.1047719

Castello, Charles C., Sanyal, Jibonananda, Rossiter, Jeffrey S., Hensley, Zachary P., and New, Joshua R., “Sensor Data Management, Validation, Correction, and Provenance for Building Technologies.” Technical paper TRNS-00223-2013.R1. In ASHRAE Transactions and Proceedings of the ASHRAE Annual Conference, Seattle, WA, June 28-July 2, 2014

Mellot, Joe, New, Joshua R., and Sanyal, Jibonananda, “Cool Roofing: Analysis of Energy Consumption for Cool Roofing”, In Western Roofing - Insulation and Siding, pp. 50-56, issue January/February, 2014

Jibonananda Sanyal, Richard Edwards, Joshua New, and Lynne Parker, “Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents”, In Concurrency and Computation: Practice and Experience, vol. 26, no. 13, 2014

Zachary Hensley, Jibonananda Sanyal, and Joshua New, “Provenance in sensor data management”, In Communications of the Association for Computing Machinery, vol. 57, no. 2, pp. 55-62, 2014. DOI=10.1145/2556647.2556657 http://doi.acm.org/10.1145/2556647.2556657

Zachary Hensley, Jibonananda Sanyal, and Joshua New, “Provenance in Sensor Data Management”. In Queue, vol. 11, no. 12, 2013. DOI=10.1145/2559899.2574836 http://doi.acm.org/10.1145/2559899.2574836

Mellot, Joseph W., New, Joshua R., and Sanyal, Jibonananda. “Preliminary Analysis of Energy Consumption for Cool Roofing Measures.” In RCI Interface Technical Journal, vol. 31, no. 9, pp. 25-36, October, 2013

Jibonananda Sanyal, Song Zhang, Jamie Dyer, Andrew Mercer, Phil Amburn, and Robert J. Moorhead, “Noodles – A Tool for Visualization of Numerical Weather Model Ensemble Uncertainty”, In IEEE Transactions on Visualization and Computer Graphics, vol. 16, no 6, pp. 1421-1430, November/December, 2010.

Jibonananda Sanyal, Song Zhang, Gargi Bhattacharya, Phil Amburn, Robert Moorhead, “A User Study to Compare Four Uncertainty Visualization Methods for 1D and 2D Datasets”, In IEEE Transactions on Visualization and Computer Graphics, vol. 15, no. 6, pp. 1209-1218, November/December, 2009.

J. Sanyal, Phil Amburn, S. Zhang, J. Dyer, P. J. Fitzpatrick, Robert J. Moorhead II, “User Experience of Hurricane Visualization in an Immersive 3D Environment”, In Lecture Notes in Computer Science, Springer-Verlag, ISVC (1) 2008: 867-878.

Budhendra Bhaduri, Mark Tuttle, Amy Rose, Jibonananda Sanyal, Devin White, Gautam Thakur, Hsiuhan Yang, Melanie Laverdiere, Matthew Whitehead, Taylor Hauser, Jacob McKee, Data and Geocomputation: Time Critical Mission Support for the 2017 Hurricane Season, AGU Annual Meeting, New Orleans, 11-15 December, 2017.

Bhaduri, Budhu; Foster, Ian; Chandola, Varun; Chen, Bob; Sanyal, Jibonananda; Allen, Melissa, and McManamay, Ryan, Energy-Water Nexus Knowledge Discovery Framework, AGU Annual Meeting, New Orleans, 11-15 December, 2017.

Helia Zandi, Ed Vineyard, Jibonananda Sanyal, David Fugate, Teja Kuruganti, Home Energy Management Retrofit Control Platform, IEA Heat Pump Conference, Rotterdam, Netherlands, 15-18 May, 2017.

Sanyal, Jibonananda, Nutaro, James J., New, Joshua Ryan, Fugate, David L., and Kuruganti, Teja, The Modbus Definition Language Specification: A first step towards device interoperability, Building Simulation 2015, Hyderabad, India, December 2015.

Jackson Stone, Jibonananda Sanyal, Charles Castello and Joshua New, “Gamification and Visualization of Sensor Data Analysis in Research Buildings”, In MODSIM World 2015, Virginia Beach, VA, March 31 – 2 April, 2015. (Special Guest)

Sanyal, Jibonananda and New, Joshua R., “Building Simulation Modelers - Are We Big Data Ready?”, In Proceedings of the ASHRAE/IBPSA-USA Building Simulation Conference, pp. 449-456, Atlanta, GA, September 10-12, 2014.

Adams, Mark, Sanyal, Jibonananda, Fricke, Brian, and Benne, Kyle, “Refrigeration Modeling Components in OpenStudio”, In Proceedings of International Refrigeration and Air Conditioning Conference, Purdue, West Lafayette, IN, USA, July 14-17, 2014

Sanyal, Jibonananda and New, Joshua R, Pragneshkumar Patel, George Ostruchov, “Uncertainty Analysis of a Heavily Instrumented Building at Different Scales of Simulation”, In Proceedings of 3rd International High Performance Buildings Conference, Purdue, West Lafayette, IN, USA in July 14-17, 2014.

New, Joshua R. and Sanyal, Jibonananda, “Supercomputers (Titan!), Big Data Analytics, and Energy Efficient Robo-Homes”, In Codestock, 77 slides. Knoxville, TN, July 11-12, 2014

Sanyal, Jibonananda and New, Joshua R., “Supercomputer Assisted Generation of Machine Learning Agents for the Calibration of Building Energy Models”, In Proceedings of the Extreme Science and Engineering Discovery Environment (XSEDE13) Conference, San Diego, CA, July 22-25, 2013. Selected as a prestigious ‘Lightning Talk’ for the plenary session.

Mellot, Joseph W., Sanyal, Jibonananda, and New, Joshua R., “Preliminary Analysis of Energy Consumption for Cool Roofing Measures”, Presented at the International Reflective Roofing Symposium, the American Coating Association's (ACA) Conference, and in Proceedings of the ACA's Coating Regulations and Analytical Methods Conference, Pittsburgh, PA, May 14-15, 2013.

Jibonananda Sanyal and Joshua New, “Simulation and Big Data Challenges in Tuning Building Energy Models”, In IEEE Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, Berkeley, May, 2013.

Jones, Chad, New, Joshua R., Sanyal, Jibonananda, and Ma, Kwan-Liu, “Visual Analytics for Roof Savings Calculator Ensembles”, In Proceedings of the 2nd Energy Informatics Conference, Atlanta, GA, Oct. 6, 2012.

New, Joshua R., Sanyal, Jibonananda, Bhandari, Mahabir S., Shrestha, Som S., “Autotune E+ Building Energy Models”, In Proceedings of the 5th SimBuild of IBPSA-USA, International Building Performance Simulation Association (IBPSA), Aug. 1-3, 2012.

Sanyal, Jibonananda, Al-Wadei, Yusof H., Bhandari, Mahabir S., Shrestha, Som S., Karpay, Buzz, Garret, Aaron L., Edwards, Richard E., Parker, Lynne E., and New, Joshua R, “Building Energy Model Calibration using EnergyPlus, Machine Learning, and Supercomputing”, In Proceedings of the 5th SimBuild of IBPSA-USA, International Building Performance Simulation Association (IBPSA), Aug. 1-3, 2012.

Jibonananda Sanyal, Song Zhang , Philip Amburn, Jamie Dyer, John van der Zwaag, Derek Irby, Robert J. Moorhead , “FloodViz – An Ensemble Enabled Tool for River Flood and Inundation Mapping”, In IEEE Visweek 2011, Providence, Rhode Island, USA, 23 – 28 October, 2011.

Jibonananda Sanyal, Song Zhang, Jamie Dyer, Andrew Mercer, Phil Amburn, and Robert J. Moorhead, “Uncertainty Visualization of Ensemble Weather Forecasts”, In Bays and Bayous Symposium 2010, Mobile, Alabama, USA, December 1-2, 2010.

Jibonananda Sanyal, Phil Amburn, Song Zhang, Patrick J Fitzpatrick, Robert Moorhead, “Applying Immersive Visualization Techniques to Analyze Model Outputs: A Case Study of Hurricane Lili”, Proceedings of IEEE Visualization 2008, Columbus, Ohio, USA. Recipient of the Best Poster Award

Jibonananda Sanyal, Phil Amburn, Song Zhang, Patrick J Fitzpatrick, and Robert J Moorhead, “3D Immersive Visualization for Evaluation of Mesoscale Model Outputs Simulating Hurricane Lili's (2002) Rapid Weakening”, Proceedings of IEEE Oceans 2008, Quebec City, Canada, 2008.