Xiaoning “Sarah” Jin
Associate Professor, Mechanical and Industrial Engineering
Contact
- xi.jin@northeastern.edu
- 334 SN
360 Huntington Avenue
Boston, MA 02115
Office
- 359 SN
- 617.373.8733
Related Links
Research Focus
Developing advanced models for prognostics and health management using physics-based models and data analytics; designing preventive strategies for manufacturing operations
Education
- 2012 PhD in Industrial and Operations Engineering, University of Michigan
- 2008 MS in Industrial and Operations Engineering, University of Michigan
- 2006 BS in Mechanical Engineering, Shanghai Jiao Tong University, China
Honors & Awards
- Faculty Research Team Award, 2024
- College of Engineering Faculty Fellow, 2023
- Faculty Research Team Award, 2022
- National Science Foundation CAREER Award, 2020
- Constantinos Mavroidis Translational Research Award, College of Engineering, Northeastern University, 2020
Professional Affiliations
- American Society of Mechanical Engineers
- Institute for Operations Research and Management Science
- Institute of Industrial Engineering
- Manufacturing & Service Operations Management Society
- Society of Women Engineers
Research Overview
Developing advanced models for prognostics and health management using physics-based models and data analytics; designing preventive strategies for manufacturing operations
Selected Research Projects
- Developing Integrative Manufacturing and Production Engineering Curricula That Leverage Data Science
- – Co-Principal Investigator, National Science Foundation
- Precision Alignment of Roll-to-Roll Printing Electronics
- – Principal Investigator, National Science Foundation
Department Research Areas
Selected Publications
- R. Bokade, A. Navato, R. Ouyang, X. Jin, C. Chou, S. Ostadabbas, and A. V. Mueller. (2021). A Cross-Disciplinary Comparison of Multimodal Data Fusion Approaches and Applications: Accelerating Learning Through Trans-Disciplinary Information Sharing. Expert Systems with Application, 165, 113885
- A. He, X. Jin, Failure Detection and Remaining Life Estimation for Ion Mill Etching Process Through Deep-Learning Based Multimodal Data Fusion, Journal of Manufacturing Science and Engineering 141(10), 2019
- C. Chou, X. Jin, A. Mueller, S. Ostadabbas Multimodal Data Fusion-Moving From Domain-Specific Algorithms to Transdomain Understanding for Accelerated Solution Development, IEEE Sensors Letters, 3(1), 2019, 1-4
- M. Xu, S.Radhakrishnan, S. Kamarthi, X. Jin Resiliency of Mutualistic Supplier-Manufacturer Networks, Scientific Reports 9, 2019, 13559
- X. Jin, H. Shui, M. Shpitalni, Virtual Sensing and Virtual Metrology for Spatial Error Monitoring of Roll-To-Roll Manufacturing Systems, CIRP Annals-Manufacturing Technology 68(1), 2019, 491-494
- M. Xu, X. Jin, S. Kamarthi, Md. Noor-E-Alam, A Failure-Dependency Modeling and State Discretization Approach for Condition-Based Maintenance Optimization of Multi-Component Systems, Journal of Manufacturing Systems, 47, 2018, 141-152
- H. Shui, X. Jin, J. Ni, Twofold Variation Propagation Modeling and Analysis for Roll-To-Roll Manufacturing Systems, IEEE Transactions on Automation Science and Engineering, 16(2), 2018, 599-612
Aug 13, 2024
How This Gordon Fellow Found Career Growth Through Leadership and Technical Skills
Mark Andersson, MS’24, advanced and intelligent manufacturing, credits his career success at Bose Corporation to the Gordon Engineering Leadership program. This allowed him to step into his current managerial role with a combination of technical knowledge and leadership abilities.
Feb 01, 2024
Faculty and Staff Awards 2024
The College of Engineering recognized faculty and staff at the annual faculty and staff awards event and thanked everyone for their hard work and dedication in support of our students, college, and university during the 2023-2024 academic year. View award recipients and photo gallery.
Nov 13, 2023
$1.5M ARL Grant To Improve Cybersecurity and Robustness in Additive Manufacturing
MIE Professor Sinan Müftü and Assistant Professor Ozan Özdemir were awarded a $1.5 million research grant by the Army Research Laboratories (ARL) to spearhead innovative initiatives in cybersecurity and enhancement of mechanical robustness in parts and coatings produced through Cold Spray Additive Manufacturing.
Apr 15, 2022
Faculty and Staff Awards 2022
Congratulations to all the winners of the faculty and staff awards, and to everyone for their hard work and dedication during the 2021-2022 academic school year.
Sep 10, 2020
Faculty and Staff Awards 2020
Congratulations to all the winners of the faculty and staff awards, and to everyone for their hard work and dedication during the 2019-2020 academic school year.
Apr 11, 2020
FY21 TIER 1 Award Recipients
Congratulations to the 19 COE faculty and affiliates who were recipients of FY21 TIER 1 Interdisciplinary Research Seed Grants for 13 different projects.
Mar 12, 2020
Cybersecurity: Your Secrets Are Safe With Us
Northeastern researchers are at the forefront of cybersecurity research, protecting everything from the phone in your pocket to the city of the future.
Mar 11, 2020
Jin Awarded NSF CAREER Award for High Precision Micromanufacturing
MIE Assistant Professor Xiaoning “Sarah” Jin was awarded a $500K NSF CAREER award for “Unifying Sensing, Machine Perception and Control for High-precision Micromanufacturing.”
Oct 07, 2019
$2M NSF Grant to Develop Data Science Modular Courses for Production Engineering Workforce
MIE Professors Sagar Kamarthi, Interim Dean Jacqueline Isaacs, Assistant Professors Xiaoning Jin, Mohsen Moghaddam, and Assistant Vice Chancellor for Digital Innovation and Enterprise Learning Kemi Jona were awarded a $2M NSF grant for “Developing Integrative Manufacturing and Production Engineering Curricula That Leverage Data Science”.
Jul 01, 2019
NSF Award for Roll-to-Roll Printing of Multi-layer Flexible Substrate Electronics
MIE Assistant Professors Xiaoning “Sarah” Jin and Hongli Zhu were awarded a $544K NSF grant for “Manufacturing USA: Precision Alignment of Roll-to-Roll Printing of Flexible Paper Electronics Through Modeling and Virtual Sensor-based Control.”