Short Bio

Roman Lysecky is a Professor of Electrical and Computer Engineering at the University of Arizona. He received his Ph.D. in Computer Science from the University of California, Riverside in 2005. His research focuses on embedded systems with emphasis on medical device security, automated threat detection and mitigation, runtime adaptable systems, performance and energy optimization, and non-intrusive observation methods. He is an author on more than 100 research publications in top journals and conferences. He received the Outstanding Ph.D. Dissertation Award from the European Design and Automation Association (EDAA) in 2006, a CAREER award from the National Science Foundation in 2009, and seven Best Paper Awards. He is an inventor on one US patent. He has authored eight textbooks on topics including C, C++, Java, Data Structures, VHDL, and Verilog, and he has contributed to several more. His recent textbooks with zyBooks utilize a web-native, active-learning approach that has shown measurable increases in student learning and course grades. He has also received multiple awards for Excellence at the Student Interface from the College of Engineering at the University of Arizona.

Recent News

  • Oct 08, 2018: Paper on Composable Template Attacks using Templates for Individual Architectural Components received Best Paper Award at the IEEE International Conference on Computer Design (ICCD). Congrats Bozhi!
  • Apr 10, 2018: Paper on Mixed Cryptography Constrained Optimization for Heterogeneous, Multicore, and Distributed Embedded Systems accepted for publication in Computers.
  • Apr 09, 2018: Paper on Non-Intrusive In-Situ Requirements Monitoring of Embedded System accepted to ACM Transactions on Design Automation for Electronic Systems (TODAES).
  • February 08, 2018'''. Research project on medical device security highlighted in article on Keeping medical devices safe from cybersecurity threats.
  • January 25, 2018: Presented at the session on "Becoming Hackproof in Medtech Through Blockchain and Engineering" at The MedTech Forum 2018. For more info, check at this MedTech Views blog post.
  • January 02, 2018: New zyBook on Fundamental Programming Concepts.
The Fundamental Programming Concepts zyBooks first teaches programming concepts in a language-neutral manner, thereby enabling students to master those concepts before having to learn details of a specific programming language. Then, the zyBookl teaches programming using a flowchart language, which is more approachable yet maintains the rigor of a programming language. The zyBook also teaches how to convert a flowchart to a simple pseudocode language, Coral, enabling a gradual learning path from flowcharts to pseudocode to an industry programming language.
  • October 06, 2017: Paper on Probabilistic Security Threat Detection for Risk Management in Cyber-physical Medical Systems Accepted to IEEE Software.
  • September 20, 2017: Paper on Subcomponent Timing-based Detection of Malware in Embedded Systems, Accepted to International Conference on Computer Design.
  • July 07, 2017: Paper on Time and Sequence Integrated Runtime Anomaly Detection for Embedded Systems Accepted to ACM Transactions on Embedded Computing Systems (TECS).
  • May 31, 2017: NSF featured our research on detecting malware in medical devices on an episode of "The Discovery Files". Give it listen: Cardi-Hack
  • March 23, 2017: Research on malware detection and mitigation for medical devices featured in a KOLD news story on UA researchers working to stay a step ahead of medical device hackers.
  • March 08, 2017: Just zyBook on Introduction to Computer Systems and Assembly Programming.
The zyBook provides an very approachable introduction to computer organization. The zyBook covers topics including information as bits, assembly programming on a simple MIPS subset called MIPSzy, translating C constructs to assembly, designing the MIPSzy processor, etc.
The zyBook teaches a systematic approach to troubleshooting and debugging using both everyday examples and programming. Feedback welcome.
  • August 23, 2016: NSF has funded a new project on TWC: Small: Time-Centric Modeling of Correct Behaviors for Efficient Non-intrusive Runtime Detection of Unauthorized System Actions with Co-PI Jerzy Rozenblit. National Science Foundation (NSF), CNS-1615890, $453,413, October 2016 September 2019.
Abstract: This project investigates formal timing-centric system behavior models that robustly capture the correct system execution behavior, which thereby enables efficient runtime detection of unauthorized system actions. The formal models will combine well-founded techniques relying on execution call graphs, sequence models, system timing requirements, and statistical analysis of execution times. Secure, non-intrusive, and efficient hardware-based identification will be developed to detect deviations from the timing and sequence characteristics defined within the nominal system behavior models. The project will investigate performance models to evaluate the area and energy overhead of our monitoring hardware. To maintain efficiency, systematic methods will be developed to evaluate and optimize the tradeoffs between security achieved by these methods and the area and energy overheads. This research will further investigate novel methods for analyzing the timing of networked embedded systems to separate the intrinsic software execution time from the incidental execution time resulting from the underlying hardware architecture, operating system, and physical environment.
  • August 01, 2016: NSF has funded a new project on CSR:Medium: Modeling and Synthesis for Application-Specific Systems-on-a-Chip. with PI Frank Vahid (UC Riverside) and Co-PI Tony Givargis (UC Irvine). National Science Foundation (NSF), CNS-1563652, $1,000,000, August 2016 July 2020.
Abstract: State-of-the-art computer chips cost tens of millions of dollars to build. Companies that build such chips make them as configurable as possible, so the same chip that is used in a digital TV application can also be used in a medical device application. However, engineers who use these chips have a hard time setting all the configurable features to get the chip's performance and power optimal for their one application. This project will investigate and develop techniques to automatically tune a state-of-the-art chip's many configurable features to serve any one particular application well, thus substantially improving performance and power for any application implemented on such a chip. The project will develop a unified computation model that ideally supports such techniques, empowering engineers to make best use of state-of-the-art chips. The project not only will improve the performance and power of a wide variety of popular devices, but also includes a web-based tool for capturing the unified computation model. Such a tool will positively impact university education as well as practicing engineers, and can catalyze research.
  • April 01, 2016: Army Research Office ARO has funded a new project on Theoretical Foundations, Modeling, and Exploration for Analyzing Power Obfuscation in Secure Embedded Systems with Co-PI Dr. Janet Wang. Army Research Office (ARO), W911NF-16-1-0130, $445,000, April 2016 March 2019.
Abstract: As embedded systems are at the heart of these mission-critical systems, verifying and maintaining the security and integrity of these devices is paramount. Side-channel attacks (SCAs) are a critical threat to the security of these systems. SCAs analyze variations in timing, power consumption, and electromagnetic radiation that can be exploited by attackers to extract critical information, e.g., cryptographic keys, from software operations. Although cryptography provides some level of security, SCAs demonstrate a critical weakness that must be properly addressed to secure embedded systems within mission critical systems. In this project, we aim at securing embedded systems by developing new mathematical models for precisely evaluating the susceptibility of embedded systems software and hardware to SCAs and the increased resilience to SCAs afforded by power obfuscation methods.
  • Here's a great video showing the benefits of the "Less text, more action" approach for zyBooks.

Recent Publications

  1. A. Rao, N. Carreon, R. Lysecky, J. Rozenblit. Probabilistic Security Threat Detection for Risk Management in Cyber-physical Medical Systems, IEEE Software, Accepted 2017.
  2. S. Lu, R. Lysecky. Time and Sequence Integrated Runtime Anomaly Detection for Embedded Systems, ACM Transactions on Embedded Computing Systems (TECS), Accepted 2017.
  3. N. Sandoval, C. Mackin, S. Whitsitt, V. S. Gopinath, S. Mahadevan, A. Milakovich, K. Merry, J. Sprinkle, R. Lysecky. Task Transition Scheduling for Data-Adaptable Systems. ACM Transactions on Embedded Computing Systems (TECS), Vol. 16, No. 4, Article 105 (May 2017), 28 pages, 2017.
  4. S. Lu, R. Lysecky, J. Rozenblit. Subcomponent Timing-based Detection of Malware in Embedded Systems, International Conference on Computer Design, 2017.
  5. M. Seo, R. Lysecky. Hierarchical Non-Intrusive In-Situ Requirements Monitoring for Embedded Systems, International Conference on Runtime Verification, 2017.
  6. S. Lu, L. Lazos, R. Lysecky. FEAL: Fine-Grained Evaluation of Active Learning in Collaborative Learning Spaces, ASEE Annual Conference, 2017.
  7. A. Edgcomb, F. Vahid, R. Lysecky, S. Lysecky. An Analysis of Incorporating Small Coding Exercises as Homework in Introductory Programming Courses, ASEE Annual Conference, 2017.
  8. A. Rao, J. Rozenblit, R. Lysecky, J. Sametinger. Composite Risk Modeling for Automated Threat Mitigation in Medical Devices. Modeling and Simulation in Medicine, Spring Simulation Multi-conference, 2017. Received Best Paper Award for Modeling and Simulation in Medicine
  9. A. Edgcomb, F. Vahid, R. Lysecky, S. Lysecky. Getting students to earnestly do reading, studying, and homework in an introductory programming class. ACM Technical Symposium on Computer Science Education (SIGCSE), 2017.
  10. S. Sargur, R. Lysecky. Non-Intrusive Dynamic Profiler for Multicore Embedded Systems. Asia and South Pacific Design Automation Conference (ASP-DAC), 2017.