Mingda Li

Bio

Education

• PhD, Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 2015.
• BS, Department of Engineering Physics, Tsinghua University, China, 2009.

Appointment

• Summer researcher, MIT Energy Initiative, 2015.
• Postdoctoral Associate, Department of Mechanical Engineering, MIT, 2015-2017.

Awards

• U.S. Department of Energy (DOE) Early Career Research Program Award, 2021
• Ruth and Joel Spira Award for Distinguished Teaching, School of Engineering, 2021

Research

The research focus of Mingda and his group (Quantum Measurement Group) is to design novel materials characterization methods and to augment existing characterization methods to probe key properties of quantum materials that were either considered not measurable or not readily measurable with existing technique and analysis methods.

Materials characterization is essential for materials science. The birth of a new characterization method, such as X-ray diffraction (XRD), photoemission spectroscopy (PES), or inleastic neutron scattering (INS), all comes with great discoveries. However, the finite type of probe particles (e.g., photons, electrons, or neutrons) in one or more spaces (r, k, E, t) restricts the combination of measurable correlation functions, and even so, it is not always easy to interpret the experimental data.

To tackle the challenge, we take an integrated quantum theory, machine-learning, unconventional use of spectroscopies, and new architecture design approach: Quantum theory lays the foundation on measurable correlation functions, machine-learning aids to uncover hidden properties buried in data, unconventional use of neutron, x-ray, and electron spectra empowers existing techniques to a broader scope, and an integration of all these into new architecture can enable the detection of materials’ properties that evade experimental detection.

Publications

Recent Publications

Please visit our group website for the updated publication list

Teaching

22.02 Introduction to Applied Nuclear Physics
22.12 Radiation Interactions, Control, and Measurement
22.042 Modeling with Machine Learning: Nuclear Science and Engineering Applications
22.S902 Quantum Theory of Materials Characterization

News

• MIT-led teams win National Science Foundation grants to research sustainable materials
• Seeing an elusive magnetic effect through the lens of machine learning
• A peculiar state of matter in layers of semiconductors
• Four MIT faculty members receive 2021 US Department of Energy early career awards
• A streamlined approach to determining thermal properties of crystalline solids and alloys
• A cool advance in thermoelectric conversion
• Newly observed phenomenon could lead to new quantum devices
• Mapping the effects of crystal defects
• Carbon nanotubes improve metal’s longevity under radiation
• Radiation physics today for materials science tomorrow
• Unusual magnetic behavior observed at a material interface
  
• Solving mysteries of conductivity in polymers
• Long-Sought Magnetic Mechanism Observed in Exotic Hybrid Materials