The Siebel Energy Institute, a global consortium for innovative and collaborative energy research dedicated to advancing the science of smart energy, today announced the winners of its fourth round of seed grant awards.
Eleven research teams, led by engineering and computer science experts from the Siebel Energy Institute consortium member universities, were each awarded $50,000 to develop proposals that accelerate energy science research. Many of the proposals are cross-collaborative between universities worldwide.
The Siebel Energy Institute has an Advisory Board of industry partners that drives active collaboration and translation of new research between academia and the private sector. Since the Institute launched in 2015, nearly $3 million in research grants have been awarded to engineering and computer science experts from the consortium member universities, with the Institutes leveraged funding model helping consortium researchers secure $52 million in large grant support for their work.
Our outcome-oriented approach has made meaningful progress in generating new technologies designed to have impactful real-world applications, said Thomas M. Siebel, Chairman of the Siebel Energy Institute. This round of grants is particularly significant, as it marks an evolution of our work. In 2019, we will expand our scope to catalyze cooperative research activities in Machine Learning, Artificial Intelligence, and the Internet of Things to establish a fundamental set of scientific advances, algorithms, designs and business change management practices necessary to effect a digital transformation in diverse industry sectors and critical infrastructures.
Research supported by the Siebel Energy Institute in this fourth round of funding aims to develop technologies, tools, policies, and techniques focused on security and privacy solutions for cloud-based CPS that operate in restricted environments or with rigorous operational performance requirements and high mission criticality.
Much of todays infrastructure operates on cloud-based technologies, so it is critical to address security, privacy, and resilience, especially as more companies embrace the digital transformation affecting their industries, noted S. Shankar Sastry, Siebel Energy Institute Director and Thomas M. Siebel Professor in Computer Science at the University of California, Berkeley.
The awarded projects investigate topics such as privacy-preserving system design and data analytics; improved resilience via attack detection and mitigation; security enhancing architectures, applications, and configurations; and security focused analytics and machine learning for modern cyber-physical systems.
The 11 fourth round seed grant recipients are:
- Subhonmesh Bose from the University of Illinois at Urbana-Champaign for Privacy by Design for Smart Energy and Transportation
- Pulkit Grover from Carnegie Mellon University for Coded Blockchain Architectures for Secure Cyber-Physical Systems (CPS) Based on Physical Proof-of-Work
- Gauri Joshi from Carnegie Mellon University for Privacy-Preserving Data Analytics in Cloud-Based Cyber-Physical Systems
- Christian Kaestner from Carnegie Mellon University for Analysis of Security-Relevant Configuration Options in CPS Infrastructure
- Max Liu from the University of Illinois at Urbana-Champaign for Secure Cloud-Based Applications for Enhancing Power Grid Resilience
- Sayan Mitra from the University of Illinois at Urbana-Champaign for A Formal Verification and Synthesis Tool for Safety Critical Power Grid Infrastructures and Cyber-Physical Systems
- Prateek Mittal from Princeton University for Exploiting Machine Learning Techniques for Power Grid State Estimation Following Cyber-Physical Attacks
- Catuscia Palamidessi from ‰cole Polytechnique for Privacy-Friendly Data Analytics
- William Sanders from the University of Illinois at Urbana-Champaign for The Design and Implementation of a Distributed Denial of Service (DDoS)-Tolerant Network Architecture for the Future CPS Cloud
- Max Shen from the University of California, Berkeley for Attack Detection and Mitigation for Distributed Water Grid Management
- Somayeh Sojoudi from the University of California, Berkeley for Secure Data Analysis Tools to Accelerate Efficiency, Resiliency, and Sustainability of Power Systems
Siebel Energy Institute seed grants enable researchers at consortium member universities to develop larger research proposals and grant submissions to government entities and foundations within a leveraged funding model. To maximize the impact of any findings and potential long-term benefits to society, all research supported by the Siebel Energy Institute will be freely available in the public domain.
About the Siebel Energy Institute
The Siebel Energy Institute is a global consortium for collaborative energy research, dedicated to accelerating and sharing advancements in machine learning applied to power systems and Internet-of-Things (IoT) infrastructures.
By funding cooperative and innovative research grants in data analytics, including artificial intelligence and machine learning, the Siebel Energy Institute hopes to accelerate advancements in the safety, security, reliability, efficiency, and environmental integrity of energy and cyber-physical systems.
The nine Siebel Energy Institute consortium member universities are: Carnegie Mellon University; ‰cole Polytechnique; Massachusetts Institute of Technology; Politecnico di Torino; Princeton University; Tsinghua University; University of California, Berkeley; University of Illinois at Urbana-Champaign; and The University of Tokyo.
Industry partners include C3, CESI, Enel Group, Engie, Eversource, Honeywell, innogy, Johnson Controls, and PG&E.
Since the Institute launched in 2015, nearly $3 million in research grants have been awarded to engineering and computer science experts from the consortium member universities. To date, the Institute leveraged funding model has helped consortium researchers secure $52 million in large grant support for their work.
For more detailed information about research projects funded by the Siebel Energy Institute, visit http://www.siebelenergyinstitute.org/.
The Thomas and Stacey Siebel Foundation
Jennifer Stern, +1