Education

• Ph.D. in Electrical Engineering, Rice University (May 2023)
  • Advisor: Prof. Richard Baraniuk
• M.S. in Electrical Engineering, Rice University (2020)
  • Advisor: Prof. Richard Baraniuk
• B.S in Electrical Engineering, Rice University (2016)
  • Magna Cum Laude

Work experience

• Research intern, Google AI, USA (2022)
  • Mentors: Caile Collins, Nathan Dass, Christian Plagemann, Mike Mozer
  • Project: Large language models for human learning
• Research intern, NVIDIA Research, USA (2022)
  • Mentors: Weili Nie, Chaowei xiao, Anima Anandkumar
  • Project: Controllable generative models
• Research intern, Microsoft Research Cambridge, UK (2019)
  • Mentors: Cheng Zhang, Sebastian Tschiatschek, Simon Peyton Jones
  • Project: Large scale educational data mining framework via variational inference
• Research intern, University of Oldenburg, Germany (2015)
  • mentors: Ante Jukic, Simon Doclo
  • Project: Speech dereverberation

Awards

• Grand prize winner, NAEP Reading Automated Scoring Challenge (2022)
• The Loewenstern Expanding Horizons Fellowship (2021)
• Ken Kennedy Institute Schlumberger Graduate Fellowship (2021)
• AIED Student Scholarship (2021)
• AAAI Student Scholarship (2021)
• Senior Merit Award in Engineering, Rice University (2016)
• 2nd place, ASAIO Student Design Competition (2016)
• Louis J. Walsh Scholarship in Engineering, Rice University (2015)
• 1st Place, IEEE Region 5 Conference Student Paper Competition (2015)
• German Academic Exchange Service (DAAD) Scholarship (2015)
• President's Honor Roll, Rice University (2012 – 2016)

Talks and presentations

• NWEA (2023)
• EMNLP conference (2022)
• AI4Science workshop, NeurIPS (2022)
• University of Chicago Data Science Institute (2022)
• Adobe Research (2022)
• Apple iCloud Education (2022)
• Google Research, PhD intern research conference (2022)
• IEEE BigData Conference (2021)
• EMNLP conference (2021)
• Ken Kennedy AI and Data Science Conference (2021)
• Nvidia ML Research (2021)
• AIED conference (2021)
• AIED Workshop on Intelligent Textbooks (2021)
• AAAI conference (2021)
• NeurIPS Competition Track (2020)
• EDM conference (2020)
• Data to Knowledge Lab (D2K) at Rice (2020)
• CSL student conference at UIUC (2019)
• L@S conference (2018)
• KDD workshop on Advancing Education with Data (2017)
• EDM conference (2017)

Teaching

• TA, Data Science Capstone Projects, Rice University (2020 - 2021)
• TA, Electrical Engineering First-Year PhD Student Projects, Rice University (2021)
• Fellow, Data to Knowledge Lab (D2K), Rice University (2019 - 2020)
• TA, Computer Architecture, Rice University (2017 - 2018)
• Co-instructor and course designer, Introduction to Computer Music, Rice University (2016)
• TA, Signals and Systems, edX (2015)
• TA, Fundamentals of Electrical Engineering, Rice University (2015)

Service

• Reviewer, NeurIPS (2019, 2021), ICML (2020), IJCAI (2021, 2022), ICLR (2022), NAACL (2022)
• Volunteer, ICML (2018, 2021), ICLR (2021)
• Lead organizer, NeurIPS Diagnostic Questions Competition (2020)

Mentorship

• Cheng Peng, BS Computer Science at Rice, now research intern at OpenStax (2022 - now)
• Jakob Valdez, BS Electrical Engineering at Rice, now engineer at Micron (2021 - now)
• Kyle Manning, BA Statistics at Rice, now data scientist at SBIA (2020)
• Camille Little, BA Statistics at Rice, now PhD student in Electrical Engineering at Rice (2019)
• Yanjun Chen, BS Electrical Engineering at Rice, now MS student in Computer Science at Stanford (2019)