Accolades

Awards

1. Early Career Distinguished Speaker, Materials Research Society 2025

   • Recognized as an outstanding early career researcher at the MRS Fall Meeting for significant contributions advancing new research directions in the field of AI/ML in materials science

2. Director’s Award, UT-Battelle, ORNL 2024

   • "Awarded for pioneering work integrating atomistic simulations with causal machine learning. Her innovative methods for real-time, autonomous experimental workflows are advancing the design and characterization of novel chemicals and materials, establishing her as a leader in computational sciences and materials research." 

   • Recognized as the highest scientific honor at ORNL, selected by the Laboratory Director and senior leadership for outstanding individual accomplishment in science and technology

3. Early Career Research Accomplishment, UT-Battelle, ORNL 2024

   • Recognized for high-impact research demonstrating technical breakthroughs, influential publications, and leadership in advancing the field within 7 years of PhD completion or equivalent experience

4. Early Discovery Award, American Ceramic Society - Basic Science Division 2024

   • Recognizes an early career researcher for significant contributions to basic science in glass and ceramics

5. Travel Awards and Fellowships 2023–2024

   • Microscopy & Microanalysis Meeting 2024

   • SIAM Conference on Mathematical Aspects of Materials 2024

   • Career Mentoring Workshop organized by Computing Research Association 2023

6. Rising Star in Computational Materials Science, Sandia National Laboratories 2022

   • Selected for the prestigious Rising Stars workshop (acceptance rate 26%) in recognition of significant contributions to computational materials science

7. Graduate School Awards and Fellowships, University of Connecticut 2016–2020

   • Best Student Poster Presentation Award, ACerS Electronic Materials and Applications Meeting

   • Doctoral Dissertation Fellowship and Travel Fellowship

   • ΦκΦ John Tanaka Graduate Student Award

   • Winner of 5th Annual Graduate Poster Competition, MSE School of Engineering

8. Undergraduate Awards and Scholarships, University of Michigan–Flint 2011–2015

   • B. D. Proffer Student Excellence Award; Student Involvement & Leadership Emerging Award

   • Volunteer Service Awards

   • Scholarships: 

     • David G. Zick

     • Freeman International Student

     • A. J. Trela Honors International Center Freshman 

     • Science & Technology

     • International Institute of Foreign National

Invited Presentations at Conferences

20. Learning the why in materials behavior, Materials Research Society (MRS), Boston, USA, 2025

19. Ferroics reimagined with causal machine learning, Materials Science & Technology (MS&T), Ohio, USA, 2025

18. AI-enhanced ferroelectric physics, IEEE Ferro School, Oak Ridge National Laboratory, USA, 2025

17. Learning materials physics from causal structures, ML in Chemical and Materials Sciences, Santa Fe, USA, 2025

16. Advanced materials meet causal learning, ARROWS Workshop, Colorado School of Mines, USA, 2025

15. Causal learning for advanced materials, TMS Annual Meeting, Las Vegas, USA, 2025

14. Theory, ML & experiments in materials, SIAM Computational Sciences & Engineering, Dallas, USA, 2025

13. Physics-informed causal AI for materials, Materials Science & Technology (MS&T), Pittsburgh, USA, 2024

12. ML & Causal Models for materials design, SIAM Mathematical Aspects of Materials Science, Pittsburgh, USA, 2024

11. Hypothesis-driven active learning for materials, Conference on Data Analysis (CoDA), Santa Fe, USA, 2023

10. Physics-informed ML for microscopy-to-simulation workflows, Materials Research Society (MRS), Boston, USA, 2023

9. Predictive materials design & discovery with causal ML, Materials Research Society (MRS), Boston, USA, 2023

8. Adaptive materials learning, International Microscopy Congress, Busan, South Korea, 2023

7. Learning distortion modes in perovskite oxides, International Microscopy Congress, Busan, South Korea, 2023

6. Microscopy meets atomistic simulations, Materials Science & Technology, Columbus, Ohio, USA, 2023

5. Interpretable ML Models of Ferroics, Materials Science & Technology, Columbus, Ohio, USA, 2023

4. Causal models for structure-property relations in perovskites, EMA, ACerS, Florida, USA, 2023

3. Causal insights into perovskites, EESTER Conference, Chennai, Tamil Nadu, India, 2023

2. Keynote lecture: Generative & causal models for ferroics from microscopy, German Materials Congress, 2022

1. Exploring Functional Materials with ML, Asia Pacific Microscopy Conference, Hyderabad, India, 2020

Invited Colloquia Presentations 

16.  AI-driven insights into materials physics, University of Idaho, USA, 2025

15. Physics-guided AI for complex materials, University of Delaware, USA, 2025

14. Causal learning in advanced materials discovery, NASA Glenn Research Center, USA, 2025

13. Causal ML Insights into Ferroics from Atomistic Simulations, 3DFeM, Pennsylvania State University, USA, 2024

12. Mechanism-informed AI for materials, Seagate Virtual AI/ML Distinguished Speaker Series, USA, 2024

11. Atomistic insights for materials design, MRS/ACerS Joint AI and ML Virtual Workshop, USA, 2024

10. Artificial intelligence for physical sciences, Invited technology talk, Oak Ridge Public Library, Oak Ridge, USA, 2024

9. Learning materials design rules, Dept. of Physics, Rensselaer Polytechnic Institute, NY, USA, 2023

8. ML-guided structural mode engineering, Center for Nanophase Materials Sciences workshop, Knoxville, USA, 2023

7. Active learning meets causal ML for materials, AI Initiative all-hands meeting, ORNL, TN, USA, 2023

6. Causal mapping of structure–property space, CSE Division, ORNL, TN, USA, 2023

5. Physics-informed ML across scales, SRM Institute of Science and Technology, Chennai, India, 2022

4. ML workflows for microscopy-simulations, Indian Institute of Technology, Indore, India, 2022

3. From electron microscopes to atomistic simulations, Argonne National Laboratory, Illinois, USA, 2022

2. 3Ms of My Career: Materials, Machine Learning & Michigan 2020, University of Michigan-Flint, USA, 2020

1. Machine learning studies of functional materials, Indian Institute of Technology, Bombay, India, 2020