Imagars LLC is a lean company with strong technological management structure.
Baldur S
teingrimsson, Ph.D., PMP
President, General Manager
Professional Appointments
1. President and General Manager, Imagars LLC (2012 – present)
2. Algorithm Support Manager, Image Sensing Systems Inc. (2009 – 2012)
3. Manager of the Rapid Development Team, Image Sensing Systems Inc. (2007 – 2009)
4. Senior Algorithm Development Engineer, Image Sensing Systems Inc. (2007)
5. Algorithm Development Engineer, Image Sensing Systems Inc. (2004 – 2007)
6. Senior Digital Signal Processing Engineer, Samsung Semiconductor Inc. (2003 – 2004)
7. Post-Doctoral Research Fellow, McMaster University (2001 – 2003)
Funded Research
1. Principal Investigator, Developing Alloy Compositions Conducive to Additive Manufacturing, Small Business Innovative Research Phase I project, sponsored by the United States Navy, 2021.
2. Principal Investigator, Use of Artificial Intelligence (Joint Optimization) to Accelerate Development of New Energetic Materials, Small Business Technology Transfer Phase I project, sponsored by the United States Air Force, 2021.
3. Principal Investigator, Ecosystem for Learning and Team Design, Small Business Innovative Research Phase IIa project, sponsored by the National Science Foundation, 2018 – 2019.
4. Principal Investigator, Ecosystem for Learning and Team Design, Small Business Innovative Research Phase II project, sponsored by the National Science Foundation, 2016 – 2018.
5. Principal Investigator, Ecosystem for Learning and Team Design, Small Business Innovative Research Phase I project, sponsored by the National Science Foundation, 2015.
Patents
1. X. Fan, B. Steingrimsson, A. Kulkarni and P.K. Liaw, Machine Learning to Accelerate Alloy Design, US Patent No. 11,915,105, https://patents.google.com/patent/US20200257933A1/, granted on Feb. 27, 2024.
2. B. Steingrimsson, R. Jones, M. Kisialiou, A. Kulkarni and K. Yi, Decisions with Big Data, US Patent No. 11,501,042, https://patents.google.com/patent/US20190087529A1/, granted on Nov. 15, 2022.
3. B. Steingrimsson, Machine Learning to Accelerate Design of Energetic Materials, Utility Patent Application No. 17,497,900, https://patents.google.com/patent/US20220067249A1/, filed on Oct. 9, 2021.
4. B. Steingrimsson and A. Kulkarni, Automatic Requirement Verification Engine and Analytics, US Patent No. 10,853,536, https://patents.google.com/patent/US10853536B1/, granted on December 1, 2020.
5. B. Steingrimsson, All-Electronic Ecosystems for Design and Collaboration, US Patent No. 9,923,949, https://patents.google.com/patent/US9923949B2/, granted on March 20, 2018.
6. K. Aubrey, K. Govindarajan, B. Brudevold, B. Steingrimsson, C. Anderson, Hybrid Traffic System and Associated Method, Utility Patent, US Patent No. 8,849,554 B2, https://patents.google.com/patent/US8849554B2/, granted on Sept. 30, 2014.
Selected Journal Publications
1. S. Chen, X. Fan, H. Shortt, B. Steingrimsson, W. Li and P.K. Liaw, “Fatigue Behavior of High-Entropy Alloys”, manuscript no. PMS-S-24-00016, under review, submitted to Progress in Material Science on January 8, 2024.
2. B. Steingrimsson, A. Agrawal, X. Fan, A. Kulkarni, D. Thoma and P.K. Liaw, “Construction of Multi-Dimensional Functions for Optimization of Additive-Manufacturing Process Parameters”, manuscript no. ADDMA-D-23-04783, under review, submitted to Journal of Additive Manufacturing on November 10, 2023.
3. B. Steingrimsson, X. Fan, B. Adam and P.K. Liaw, “Physics-Based Machine Learning Approach for Modeling the Temperature-Dependent Yield Strength of Superalloys”, article no. 2201903, DOI: 10.1002/adem.202201903, https://doi.org/10.1002/adem.202201903, published in Advanced Engineering Materials on March 24, 2023.
4. B. Steingrimsson, X. Fan, R. Feng and P.K. Liaw, “A Physics-Based Machine-Learning Approach for Modeling the Temperature-Dependent Yield Strengths of Medium- or High-Entropy Alloys”, vol. 31, no. 101747, https://doi.org/10.1016/j.apmt.2023.101747, published in Applied Materials Today in April, 2023.
5. X. Fan, S. Chen, B. Steingrimsson, Q. Xiong, W. Li and P.K. Liaw, “Dataset for Fracture and Impact Toughness of High-Entropy Alloys”, article no. 37, DOI: 10.1038/s41597-022-01911-4, https://www.nature.com/articles/s41597-022-01911-4, published in Nature Scientific Data on January 19, 2023.
6. S. Chen, X. Fan, B. Steingrimsson, Q. Xiong, W. Li and P.K. Liaw, “Fatigue database of high-entropy alloys”, article no. 381, DOI: 10.1038/s41597-022-01368-5, https://www.nature.com/articles/s41597-022-01368-5, published in Nature Scientific Data on July 6, 2022.
7. B. Steingrimsson, X. Fan, X. Yang, M.C Gao, Y. Zhang and P.K. Liaw, “Predicting Temperature-Dependent Ultimate Strengths of BCC High-Entropy Alloys”, vol. 7, no. 152, DOI 10.1038/s41524-021-00623-4, https://www.nature.com/articles/s41524-021-00623-4.pdf, published in NPJ Computational Materials on Sept. 24, 2021.
Textbook Chapters
• B. Steingrimsson, X. Fan, A. Kulkarni, M.C. Gao and P.K. Liaw, “Machine Learning and Data Analytics for Design and Manufacturing of High-Entropy Materials Exhibiting Mechanical or Fatigue Properties of Interest”, in the textbook titled “Fundamental Studies in High-Entropy Materials”; Publisher: Springer, Editors: Dr. Jamieson Brechtl and Dr. Peter K. Liaw; Available through Barnes and Noble or Springer, eBook ISBN 978-3-030-77641-1, print ISBN-978-3-030-77640-4, DOI: 10.1007/978-3-030-77641-1_4, e-Book released by Springer on January 7, 2022.
Selected Presentations
1. H. Kersell, X. Fan, A. Herman, Z. Lyu, B. Steingrimsson, P.K. Liaw and G. Herman, “In-Situ Characterization of O2 Gas-Induced Rearrangement of Near-Surface Composition in Refractory High-Entropy Alloys”, the American Vacuum Science Conference, Pittsburgh PA, Nov. 6 – 11, 2022.
2. B. Steingrimsson, B. Adam, M.C. Gao, G. Tewksbury, E.W. Huang and P.K. Liaw, “Defect Minimization in Additive Manufacturing through a Customized High-Throughput Experimental Methodology and Machine Learning Approach”, the 1st World Congress on Artificial Intelligence in Materials and Manufacturing, Pittsburgh PA, April 4 – 11, 2022.
3. B. Steingrimsson, X. Fan, M.C. Gao and P.K. Liaw, “Predicting Temperature-Dependent Ultimate Strengths of BCC High-Entropy Alloys”, the Minerals, Metals & Materials Society Conference (invited talk), Anaheim CA, Feb. 27 – March 3, 2022.
4. B. Steingrimsson, M.C. Gao, G. Tewksbury and P. K. Liaw, “Early Investigation of Hybrid Approaches to Joint Optimization for Accelerating the Design of Refractory High Entropy Alloys”, poster presented at the 2021 HEA World Congress, Charlotte NC, December 5 – 8, 2021.
5. B. Steingrimsson, X. Fan, M.C. Gao and P. K. Liaw, “Modeling, Prediction and Analysis of the Temperature-Dependent Strength Properties of High-Entropy Alloys, and Comparison with Nickel-Based Superalloys”, presented at the 2021 MRS Spring Meeting, virtual, April 23, 2021.
6. B. Steingrimsson, J. Poon, M. Widom, A. Kulkarni, X. Fan, C. Lee, C. Zhang, M. Kirka, J. El-Awady and P. K. Liaw, “Accelerated Design of High-Entropy Alloys for Gas-Turbine Blade Components”, presented at the Minerals, Metals & Materials Society Conference (invited talk), virtual, March 16, 2021.
7. X. Fan, B. Steingrimsson, A. Kulkarni and P.K. Liaw, “Machine Learning and Data Analytics for Accelerating High-Temperature, Corrosion-Resistant Materials Design”, presented at the Material Science & Technology Conference, virtual, Nov. 3, 2020.
8. X. Fan, B. Steingrimsson, O. Rios, A. Kulkarni, D. Kim and P.K. Liaw, “Machine Learning and Data Analytics for Identification of HEA Compositions and Processing Conditions Resulting in Enhanced Fatigue Resistance”, presented at the Material Science & Technology Conference, virtual, Nov. 2, 2020.
9. X. Fan, B. Steingrimsson, D.B. Kim and P.K. Liaw, “Machine Learning for Accelerating the Design of Additively-Manufactured Turbine Blades Yielding Ultra-High Energy Efficiency”, presented at the Minerals, Metals & Materials Society Conference (invited talk), San Diego CA, Feb. 23 – 27, 2020.
10. X. Fan, B. Steingrimsson, D.B. Kim and P.K. Liaw, “Prediction of Fatigue Life of Flight-Critical Metallic Components Fabricated by Additive Manufacturing”, presented at the Minerals, Metals & Materials Society Conference, San Diego CA, Feb. 23 – 27, 2020.
11. X. Fan, R. Jones, B. Steingrimsson, K. Yi, P.K. Liaw and S. Yi, “Data Analytics and Machine Learning to Accelerate Materials Design and Processing Development of High Entropy Alloys”, High-Entropy Alloy World Congress, Seattle WA, Nov. 17 – 20, 2019.
12. B. Steingrimsson, S. Yi, R. Jones, M. Kisialiou, K. Yi and Z. Rose, “Big Data Analytics for Improving Fidelity of Engineering Design Decisions”, SAE World Congress, Detroit MI, April 10 – 12, 2018.
Reviewing and Conference Organization
• Session Chair (on record) at the TMS 2020 and 2022 Conferences.
• Department of Energy ARPA-E SCALE-UP – – Seeding Critical Advances for Leading Energy Technologies with Untapped Potential, Merit Review Board Chair (Tech-to-Market Commercialization Expert): Jonathan Glass, 2023.
• Department of Energy ARPA-E ASCEND – Aviation-Class Synergistically Cooled Electric-Motors with Integrated Drives, Program Director: Dr. Michael Ohadi, 2020.
• Department of Energy ARPA-E DIFFERENTIATE – Design Intelligence for Formidable Energy Reduction Engendering Numerous Totally Impactful Advanced Technology Enhancements, Program Director: Dr. David Tew, 2019.
Primary Awards
• Albert Nelson Marquis Lifetime Achievement award, 2021.
Professional Certifications
• Certified Project Management Professional, since 2008 (PMP #1201855).
Imagars LLC
P.O. Box 261
Wilsonville, OR 97070
USA
TEL: 763-439-6905
USA