Summary

• Specialized in traditional pyrometallurgy and modern data-driven prediction for manufacturing industry (including metal additive manufacturing and continuous casting)
• 10-year research experience in metallic alloys, including aluminum, iron & steel, titanium, and nickel
• Professional training in data science & machine learning
• Strong academic record with 7 first-author peer-reviewed journal articles and > 1500 citations (GoogleScholar)

Education

• PhD in Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, 2017
• MS in Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, 2014
• BS in Materials Science and Engineering, Beihang University, Beijing, 2012

Work experience (Linkedin)

• Exponent, 2022-08 - present
  • Senior Associate, 2022-08 - present
  • Menlo Park, CA
  • Proactive Projects: Acting as the Sherlock Holmes for medical devices, sports gear, and tech toys, figuring out why they failed and how to prevent from happening
  • Reactive Projects: Providing technical expertise for litigation support, covering intellectual property disputes, protection of trade secrets, and issues arising from medical device malfunctions. This encompasses detailed analysis and evidence gathering to support legal claims and defenses.

• ArcelorMittal Global R&D, 2018-03 - 2022-07
  • Research Engineer, 2018-03 - 2021-12
  • Senior Research Engineer, 2021-12 - 2022-07
  • East Chicago, IN
  • Managed the steel cleanliness characterization facility in support for product development, root cause analysis, and quality evaluation
  • Led projects on R&D fundamental steelmaking research to sustain new AHSS product manufacturability for the automotive customers, such as Tesla, Toyota, Nissan, and GM
  • Provided technical support to steelmaking operations to optimize the reliability of steelmaking process and minimize residual defects in the product
  • Co-chaired and organized the annual North America Innovation Awards (highest internal technical award)

• Carnegie Mellon University, 2014-08 - 2017-05
  • PhD research assistant
  • Pittsburgh, PA
  • Thesis: Inclusions, Porosity, and Fatigue of AlSi10Mg Parts Produced by Selective Laser Melting (link)
  • Discovered the oxide-induced porosity as a novel type of defect which dominates the fatigue performance of additively manufactured aluminum alloy
  • Collaborated closely with researchers in the Department of Mechanical Engineering and industrial partner (Arconic) on fatigue, tension, and compression tests

Skills

• Materials Science
  • Mechanical tests: fatigue, tension, bendability, hole expansion, nano-indentation
  • Characterization: SEM/EDX (highly skilled in automated-SEM), micro-CT, XRD, DSC
• Data Science (in Python)
  • Machine learning: sklearn, pandas, Keras/TensorFlow (image classification), xgb
  • Web application: streamlit, Heroku
  • Advanced statistics: rpy2 (for extreme value analysis)
  • Project posts: available on my GitHub site
• Of course, if my hobbies also count as skills …

Publications (Google Scholar, 1000+ citations)

Journal articles

• S. Yang, A. Rebmann, M. Tang, R. Moravec, D. Behrmann, M. Baird, W. Bequette, “Process monitoring using causal graphical models, with application to clogging detection in steel continuous casting,” J. Process Control, vol. 105, pp. 259-266, 2021, doi: 10.1016/j.jprocont.2021.08.006
• M. Tang and P. C. Pistorius, “Fatigue Life Prediction for AlSi10Mg Parts Produced by Selective Laser Melting,” Int. J. Fatigue, vol. 125, pp. 479-490, 2019. doi: 10.1016/j.ijfatigue.2019.04.015
• M. Tang and P. C. Pistorius, C. Montgomery, J. Beuth, “Build Rate Optimization for Powder Bed Fusion,” J. Mater. Eng. Perform., vol. 28, pp. 641–647, 2019. doi: 10.1007/s11665-018-3647-5
• M. Tang and P. C. Pistorius, “Anisotropic Mechanical Behavior of AlSi10Mg Parts Produced by Selective Laser Melting,” JOM, vol. 69, pp. 516–522, 2017. doi: 10.1007/s11837-016-2230-5
• M. Tang, P. C. Pistorius, and J.L. Beuth, “Prediction of Lack-of-fusion Porosity for Powder Bed Fusion,” Addit. Manuf., vol. 14, pp. 39-48, 2017. doi: 10.1016/j.addma.2016.12.001
• M. Tang and P. C. Pistorius, “Oxide, Porosity and Fatigue performance of AlSi10Mg Parts Produced by Selective Laser Melting,” Int. J. Fatigue, vol. 94, pp. 192-201, 2017. doi: 10.1016/j.ijfatigue.2016.06.002
• M. Tang, P. C. Pistorius, S. Narra, and J.L. Beuth, “Rapid Solidification: Selective Laser Melting of AlSi10Mg,” JOM, vol. 68, pp. 960-966, 2016. doi: 10.1007/s11837-015-1763-3
• M. Tang, H. J. Cho, and P. C. Pistorius, “Early Gaseous Oxygen Enrichment to Enhance Magnetite Pellet Oxidation,” Metall. Mater. Trans. B, vol. 45, pp. 1304-1314, 2014. doi: 10.1007/s11663-014-0064-5
• H. J. Cho, M. Tang, and P. C. Pistorius, “Magnetite Particle Size Distribution and Pellet Oxidation,” Metall. Mater. Trans. B, vol. 45, pp. 1213-1220, 2014. doi: 10.1007/s11663-014-0104-1

Conference proceedings

• M. Tang, P. C. Pistorius, and J.L. Beuth, “Geometric Model to Predict Porosity of Part Produced in Powder Bed System,” in Materials Science & Technology, Columbus, OH, 2015, pp. 129-136.
• P. C. Pistorius and M. Tang, “Prediction of Non-Isothermal Oxidation of Magnetite Pellets,” in Drying, Roasting, and Calcining of Minerals, Orlando, FL, 2015, pp. 203-208.
• M. Tang and P. C. Pistorius, “Magnetite Pellet Oxidation: Effects of Water Vapor and Non-Isothermal Reaction,” in AISTech, Indianapolis, IN, 2014, pp. 635-642.

Talks at International Conferences

• M. Tang and P. C. Pistorius, “Fatigue Life Prediction for AlSi10Mg Parts Produced by Selective Laser Melting,” RAPID + TCT Conference, Pittsburgh, PA, May 2017.
• M. Tang and P. C. Pistorius, “Anisotropic Mechanical Behavior of AlSi10Mg Parts Produced by Selective Laser Melting,” TMS, San Diego, CA, Mar 2017.
• M. Tang and P. C. Pistorius, “Relationship between Porosity Size and Fatigue Life Distributions of AlSi10Mg Parts Produced by Selective Laser Melting,” MS&T, Salt Lake City, UT, 2016.
• M. Tang, P. C. Pistorius, “Oxide, Porosity and Fatigue Performance of AlSi10Mg Parts Produced by Selective Laser Melting,” TMS, Nashville, TN, 2016.
• M. Tang, P. C. Pistorius, and J.L. Beuth, “Geometric Model to Predict Porosity of Part Produced in Powder Bed System,” MS&T, Columbus, OH, 2015.
• M. Tang and P. C. Pistorius, “Magnetite Pellet Oxidation: Effects of Water Vapor and Non-isothermal Reaction,” AISTech, Indianapolis, IN, 2014.

Service and leadership

• Co-chair of the Innovation Award Committee in ArcelorMittal Global R&D
  • largest award within the North America division (Canada, Mexico, and USA)
• Reviewers
  • AISTech Transactions (Key reviewer)
  • Materials Science and Engineering A (Outstanding reviewer)
  • Journal of Materials Processing Technology (Outstanding reviewer)
  • Materials & Design
  • International Journal of Fatigue
  • Metallurgical and Materials Transactions B
  • JOM
  • Journal of Alloy and Compounds
  • Ironmaking and Steelmaking: Processes, Products and Applications