I'm Nirmal, and I do Learning Engineering research at Playpower Labs. I'm also the Co-Founder of Smart Paper, an upcoming AI in education startup.
I build innovative technologies to solve challenging problems in modern education. I have fifteen years of hands-on experience spanning across software engineering, data science, AI, and learning science. I have published award-winning research around educational data, and I actively work with the education community to materialize grand visions.
I created grant-winning technologies that led to the beginning of Playpower Labs.
Fairness & Equity in India's National Tests
Technology for Learning Science
I work with Dr. Steve Ritter, Founder of Carnegie Learning to build UpGrade - an open-source platform for A/B testing in education.
Winner, 2021-2022 Learning Engineering Tools Competition (30 Worldwide Winners)
Winner, 2022 Educational Measurement: Issues and Practice (EM:IP) Cover Graphic/Data Visualization Competition
Best Paper, 2022 IEEE International Conference on Artificial Intelligence Trends and Pattern Recognition
Winner, 2019 NAEP Data Mining Challenge
Best Short Paper, 2018 Intelligent Tutoring Systems Conference
Honorable Mention, 2017 ACM CHI
Winning Team, 2011 National STEM Video Game Challenge
Bold = First author
Improving Mathematics Assessment Readability: Do Large Language Models Help? Journal of Computer Assisted Learning, 2023
Equitable Access to Intelligent Tutoring Systems Through Paper-Digital Integration. International Intelligent Tutoring Systems Conference, 2022
Variable Length Digit Recognition for the Gujarati Language. IEEE International Conference on Artificial Intelligence Trends and Pattern Recognition, 2022.
Modeling NAEP Test-Taking Behavior Using Educational Process Analysis. Journal of Educational Data Mining Vol. 13 No. 2, 2021
UpGrade: An open source tool to support A/B testing in educational software. First Workshop on Educational A/B Testing at Scale (at Learning@ Scale), 2020.
Optimizing an Educational Game Using UpGrade: Challenges and Opportunities. First Workshop on Educational A/B Testing at Scale (at Learning@ Scale), 2020.
Explainable Knowledge Tracing Models for Big Data: Is Ensembling an Answer? arXiv preprint arXiv:2011.05285, 2020.
Visualizing Cronbach's Alpha for a Large Number of Assessments. First Workshop on Educational Data Visualization (at Learning Analytics and Knowledge), 2019.
Curriculum pacing: A new approach to discover instructional practices in classrooms. International Intelligent Tutoring Systems Conference, 2018
Is difficulty overrated? The effects of choice, novelty and suspense on intrinsic motivation in educational games. CHI conference on human factors in computing systems, 2017.
Mining frequent learning pathways from a large educational dataset. arXiv preprint arXiv:1705.11125, 2017.
Interface design optimization as a multi-armed bandit problem. CHI conference on human factors in computing systems, 2016.
A Workshop on Process Analysis Methods For Educational Data, In Educational Data Mining Conference, Paris, France. 2021.
A Workshop on Educational Data Visualization, In Learning Analytics and Knowledge Conference, Arizona, United States. 2019.
How Covid-19 Created a New Wave of Digital Learning in India, American Education Research Association Annual Meeting, 2022
A Talk on Process Mining and A/B Testing in Educational Applications, CMU Open Learning Initiative AI/ML Group, 2022
Thank you for reading and have a wonderful day!