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

• Rising Star in Data Science, University of Chicago Data Science Institute (2022)
• 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)
• World Ranking 35/1853 (top 2%) in IEEEXtreme Coding Competition (2014)
• President's Honor Roll, Rice University (2012 – 2016)

Talks and presentations

• ACL conference and workshops (2023)
• 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, IJAIED (2023), Springer MACH (2022), ICLR (2022, 2023), NeurIPS (2019, 2021, 2022, 2023), ICML (2020, 2022), IJCAI (2021, 2022), NAACL (2022), AIED (2022), EDM (2022), DL4Ed workshop (2019), iTextbook workshop (2019, 2022), BEA Workshop (2023)
• Volunteer, ICML (2018, 2021), ICLR (2021)
• Organizer, NeurIPS Education Competition (2022)
• 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)