Cybersecurity Quantification Lab

Cybersecurity Quantification Lab (CyQL)

Principal Investigator(s): Michel Cukier

The research conducted in CyQL focuses on quantifying cybersecurity. The research team has conducted various empirical studies using security data collected in-house and across the world. The research team collaborates closely with the university Division of Information Technology Security and Policy team. The security data is collected in-house, and consist of incidents, intrusions alerts, networks flows and malicious activity towards/from target computers. Furthermore, at various organizations across the world, we collect malicious activity towards/from target computers. We are also collaborating with of the Department of Criminology and Criminal Justice at UMD to conduct specific empirical experiments related to criminological theories.

Glenn Martin Hall Building

Design Decision Support Laboratory (DDSL)

Principal Investigator(s): Shapour Azarm

DDSL was founded in 1999. The labs current research areas include deterministic and stochastic (robust) design optimization; multi-attribute design decision making under uncertainty; multi-disciplinary multi-objective sensitivity analysis; reduced-order modeling; product design for market systems.

Glenn Martin Hall Building

Laboratory for Reliable Nanoelectronics

Principal Investigator(s): Aris Christou

The Laboratory for Reliable Nanoelectronics is an advanced facility for semiconductor device process development, test structure design for reliability and reliability measurements at the University of Maryland. It includes a broad variety of advanced materials processes and supporting processes for fabricating of devices and reliability test structures.

Lab Acoust Emiss

Probabilistic Physics of Failure and Fracture Mechanics Laboratory

Principal Investigator(s): Mohammad Modarres

The Probabilistic Physics of Failure and Fracture Mechanics Laboratory is currently researching MTS Uniaxial Fatigue Testing Machines; Optical Microscopy for Short Fatigue Crack; Acoustic Emission Technique for Crack Initiation and Growth; Heating Chamber for Creep Testing; and Corrosive Medium Chamber.

Risk and Decision Analysis Laboratory

Principal Investigator(s): Yunfei Zhao

Research Research in the Risk and Decision Analysis Laboratory is focused on risk analysis and decision analysis for complex industrial systems, for example, nuclear power plants, electric power systems. Particularly, we focus on developing dynamic methods for probabilistic risk assessment that are suitable for modeling the dynamic and complex interactions and dependencies between these different aspects. We use risk analysis to support risk-informed decision-making to cost-effectively improve system reliability and performance through risk-informed design optimization, maintenance policy optimization, cyber attack response optimization, etc. We use existing and develop new methods, models, and algorithms to address these risk analysis and decision analysis problems, for example, dynamic probabilistic risk assessment, game theory, Bayesian analysis, Bayesian networks, cognitive modeling and simulation, dynamic programming, Markov decision process. We are also interested in probabilistic inference problems, for example, cyber attack detection, system health monitoring, the solution to which can support decision analysis. Research areas Risk analysis and reliability engineering Probabilistic risk assessment Dynamic probabilistic risk assessment Human reliability analysis Cybersecurity risk analysis Decision analysis Maintenance policy optimization Cyber attack response optimization Nuclear emergency response Probabilistic inference Fault diagnosis Cyber attack detection Health monitoring Applications Nuclear power plants Electric power systems Methods used and developed Bayesian analysis Bayesian networks Monte Carlo simulation Game theory Particle filtering Dynamic programming Markov decision process (including Partially observable Markov decision process) Neural networks

Risk-Informed Solutions in Engineering (RISE) Lab

Principal Investigator(s): Michelle (Shelby) Bensi

The RISE Lab team conducts research related to probabilistic assessment of natural hazards and associated risks as well as a variety of topics involving the applications of statistics and machine learning in engineering. RISE Lab researchers are engaged in projects involving seismic, inland flooding, precipitation, storm surge, and compound hazards. Projects often focus on issues of relevance to nuclear power plants and other critical infrastructure. In addition, RISE Lab researchers are engaged in a number of cross-disciplinary projects looking at topics as diverse as exploring the potential combined impacts of COVID and natural hazard events on communities of color, understanding the potential effects of climate change on contaminated sites and agriculture, and exploring seismic hazards to human lunar installations.

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Systems Risk and Reliability Analysis (SyRRA) Lab

Principal Investigator(s): Katrina Groth

The SyRRA lab conducts innovative research in risk and reliability modeling and simulation methods for analysis of complex engineering systems. Researchers in the lab combines advanced computational techniques, diverse types of data and information, with system-level thinking. We use Bayesian methods, machine learning, and causal models to fuse sparse data, big data, and qualitative information from multiple sources into models that support decisions and prediction under uncertainty. Our research contributes to the fields of safety, risk and reliability from both a mathematical perspective and from an applied perspective, with direct impact on systems ranging from hydrogen gas stations and infrastructure to nuclear power plants, natural gas transportation, pipelines, aviation, and more.