- Adjunct Faculty Computer, Software and Electrical Engineering
- Samuel.Siewert@erau.edu Email
- Electrical, Computer & Software Engr Department
- Prescott College of Engineering
Areas of Expertise
Computer Vision, Real-Time, Embedded, Machine Learning, Interactive Systems
- Ph.D. - Doctor of Philosophy in Computer Science, University of Colorado - Boulder
- M.S. - Master of Science in Computer Science, University of Colorado - Boulder
- B.S. - Bachelor of Science in Aerospace Engineering, University of Notre Dame
- CEC 450: Real-Time Systems
CEC 450, Real-Time Systems
SE 545, Specification & Design of Real-Time Systems
CS 332, Organization of Programming Languages
CS 317, File and Database Management Systems
SE 420, Software Quality Assurance
SE 310, Analysis and Design of Software Systems
CS 415, Human Computer Interactive Systems
CEC 322, Microprocessor Systems Lab
SE 300, Software Engineering Practices
ECEE 5763, Embedded Machine Vision and Intelligent Automation
ECEE 5623, Real-Time Embedded Systems
ECEE 5653, Real-Time Digital Media
S. Siewert, M. Andalibi, S. Bruder, J. Buchholz, D. Chamberlain, A. Erno, T. Shiroma, and D. Stockhouse, “Comparison of RADAR, Passive Optical with Acoustic, and Fused Multi-Modal Active and Passive Sensing for UAS Traffic Management Compliance and Urban Air Mobility Safety”, AIAA SciTech, Orlando, January 2020.
S. Siewert, R. Sampigethaya, J. Buchholz, S. Rizor, “Fail-Safe, Fail-Secure Experiments for Small UAS and UAM Traffic in Urban Airspace”, IEEE Digital Avionics Systems Conference, San Diego, September 2019.
S. Siewert, R. Sampigethaya, S. Bruder, M. Andalibi, “Multi-modal Active and Passive Sensing Experiments for Fail-Safe and Fail-Secure Urban UAS Traffic Management”, AUVSI Xponential, Chicago, May 2019.
S. Siewert, “Sensor Fusion Infrastructure for Urban Drone Traffic Management”, Dronesphere Colloquium and Panel, University of Toronto, February 23, 2019.
S. Siewert, M. Andalibi, S. Bruder, J. Buchholz, S. Rizor, R. Fernandez, “Slew-to-Cue Electro-Optical and Infrared Sensor Network for small UAS Detection, Tracking and Identification”, AIAA SciTech, San Diego, January 2019.
S. Siewert, M. Andalibi, S. Bruder, I. Gentilini, A. Dandupally, S. Gavvala, O. Prabhu, J. Buchholz, D. Burklund., “Drone Net, a passive instrument network driven by machine vision and machine learning to automate UAS traffic management”, AUVSI Xponential poster, Denver, Colorado, May 2018.
S. Siewert, “Social Networking Trolls, Fakes and Phishing, Oh My!”, position paper, November 2018.
S. Siewert, “Why software engineers and developers should care about blockchain technology”, white paper, April 2018.
S. Siewert, M. Andalibi, S. Bruder, I. Gentilini, J. Buchholz, “Drone Net Architecture for UAS Traffic Management Multi-modal Sensor Networking Experiments”, IEEE Aerospace Conference, Big Sky, Montana, March 2018.
S. Siewert, Andalibi, S. Bruder, I. Gentilini, J. Buchholz, “UAS Integration, Application, Education and Innovation - Drone Net Architecture for UAS Traffic Management Status”, ERAU President’s Council on UAS National Airspace Integration and Applications, Daytona Beach, Florida, November 30, 2017.
S. Siewert, M. Andalibi, S. Bruder, I. Gentilini, J. Buchholz, “Drone Net: Using Tegra for Multi-Spectral Detection and Tracking in Shared Air Space”, GPU Technology Conference, Silicon Valley, May 8-11, 2017.
S. Siewert, “Beyond the Textbook: Embedded Code”, American Astronautical Society, 40th Guidance and Control Conference, Rocky Mountain Section, Breckenridge, Colorado, February 5, 2017.
S. Siewert, M. Vis, R. Claus, R. Krishnamurthy, S. B. Singh, A. K. Singh, S. Gunasekaran, “Image and Information Fusion Experiments with a Software-Defined Multi-Spectral Imaging System for Aviation and Marine Sensor Networks”, AIAA SciTech 2017, Grapevine, Texas, January 2017.
S. Siewert, V. Angoth, R. Krishnamurthy, K. Mani, K. Mock, S. B. Singh, S. Srivistava, C. Wagner, R. Claus, M. Vis, “Software Defined Multi-Spectral Imaging for Arctic Sensor Networks”, SPIE Proceedings, Volume 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII, Baltimore, Maryland, April 2016.
S. Siewert, “Exploring Internet of Things Processing on Curie with Quark”, Intel Corporation, June 2016.
S. Siewert, J. Pratt, Real-Time Embedded Components and Systems Using Linux and RTOS, Mercury Learning and Information, Dulles Virginia, December 2015, ISBN 978-1-942270-04-1.
S. Siewert, J. Shihadeh, Randall Myers, Jay Khandhar, Vitaly Ivanov, “Low Cost, High Performance and Efficiency Computational Photometer Design”, SPIE Proceedings, Volume 9121, Sensing Technology and Applications, Baltimore, Maryland, May 2014.
S. Siewert, M. Ahmad, K. Yao, “Verification of Video Frame Latency Telemetry for UAV Systems Using a Secondary Optical Method”, AIAA SciTech 2014, National Harbor, Maryland, January 2014.
S. Siewert, “Big data interactive: Machine Data Analytics – Drop in Place Security and Safety Monitors”, IBM developerWorks, January 2014.
US Pat. 8,473,779 – Systems and methods for error correction and detection, isolation, and recovery of faults in a fail-in-place storage array, granted June 25, 2013.
S. Siewert, “Big data interactive - The world of interactive media systems and applications”, IBM developerWorks, December 2013.
S. Siewert, “Big data in the cloud – Data velocity, volume, variety, veracity”, IBM developerWorks, July 2013.
S. Siewert, “Cloud scaling, part 3: Explore video analytics in the cloud”, IBM developerWorks, June 2013.
S. Siewert, “Cloud scaling, part 2: Tour high-performance cloud system design advances”, IBM developerWorks, May 2013.
S. Siewert, “Cloud scaling, part 1: Build your own and scale with HPC on demand”, IBM developerWorks, April 2013.
S. Siewert, “Revolutionary Methods to Handle Data Durability Challenges for Big Data”, Intel White Paper, September 2012.
S. Siewert, “Cloud-based education, Part 3: Cloud-based robotics for education”, IBM developerWorks, February 2012.
S. Siewert, “Cloud-based education, Part 2: Tapping Cloud-based High Performance Computing for Education”, IBM developerWorks, January 2012.
S. Siewert, “Cloud-based education, Part 1: E-learning strategy for instructors”, IBM developerWorks, December 2011.
S. Siewert, D. Nelson, “Solid State Drives in Storage and Embedded Applications”, Intel Technical Journal, Volume 13, Issue 1, pp. 29-53, July 2009.
S. Siewert, “Using Intel® VTune™ Performance Analyzer and Intel® Performance Primitives for Real-time Media Optimization”, Intel Corporation, June 2009.
S. Siewert, “Using SSE and IPP to Accelerate Image Processing Algorithms”, Intel Corporation, August 2009.
S. Siewert, “Infrastructure architecture essentials, Part 7: High-performance computing off the shelf”, IBM developerWorks, December 2008.
S. Siewert, “Infrastructure architecture essentials, Part 5: Content delivery and distribution network design”, IBM developerWorks, November 2008.
S. Siewert, “Infrastructure architecture essentials, Part 4: Scalable enterprise systems management”, IBM developerWorks, October 2008.
S. Siewert, “Infrastructure architecture essentials, Part 3: System design methods for scaling”, IBM developerWorks, October 2008.
S. Siewert, “Infrastructure architecture essentials, Part 2: Find, avoid, and eliminate system bottlenecks”, IBM developerWorks, October 2008
US Pat. 7,370,326 - Prerequisite-based scheduler, granted May 6, 2008.
Sam Siewert has studied at University of California Berkeley, University of Notre Dame, University of Houston and University of Colorado Boulder and has a B.S. in Aerospace and Mechanical Engineering and M.S. and Ph.D. in Computer Science. He has worked in the computer engineering industry for twenty four years before starting an academic career in 2012. Half of his time was spent on NASA space exploration programs including the Spitzer space telescope, Space Shuttle mission control, and deep space programs. The other half of that time he has spent on commercial product development. His commercial work has ranged from I/O chip firmware architecture to systems design of storage and networking solutions for high performance computing. In 2014 Dr. Siewert joined Embry Riddle Aeronautical University Prescott as full time faculty and retains an adjunct professor role in addition with University of Colorado Boulder. Overall, his focus has been embedded systems with an emphasis on autonomous systems, computer and machine vision, hybrid re-configurable architecture and operating systems.
Memberships and CredentialsSenior member of AIAA and IEEE. Member of ASEE and Council on Undergraduate Research.
Awards, Honors and Recognitions
2019 National Academies of Science, Engineering and Medicine – TRB ACRP 07-18, Airfield Design Guidelines for Large UAS
2018 College of Engineering, Research, Scholarship and Design Award for Drone Net, ERAU Prescott
2017-2020 PI, Drone Net Project, Accelerate Research Initiative, ICARUS Research Group
2017 College of Engineering, Research Group of the Year, UAS & Autonomous Systems, ERAU Prescott
NASA Group Achievement Award, Tech. Demonstration flown on STS-85