See all my publications on Google Scholar
Selected publications
A. Felipe Zambrano, R. S. Baker, and A. S. Lan,
"Active Learning for a Classroom Observer who Can't Time Travel,"
What’s next in Affect Modelling Workshop at Conference of the Association for the Advancement of Affective Computing (ACII), Sept. 2023
A. Scarlatos and A. S. Lan,
"Tree-Based Representation and Generation of Natural and Mathematical Language,"
Annual Meeting of the Association for Computational Linguistics (ACL), July 2023
M. Zhang, Z. Wang, Z. Yang, W. Feng, and A. S. Lan,
"Interpretable Math Word Problem Solution Generation via Step-by-step Planning,"
Annual Meeting of the Association for Computational Linguistics (ACL), July 2023
N. Ashok Kumar, N. Fernandez, Z. Wang, and A. S. Lan,
"Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank,"
Workshop on Innovative Use of NLP for Building Educational Applications (BEA@ACL), July 2023
N. Ashok Kumar, W. Feng, J. Lee, H. McNichols, A. Ghosh, and A. S. Lan,
"A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing,"
International Conference on Educational Data Mining (EDM), July 2023
M. Zhang, N. Heffernan, and A. S. Lan,
"Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions,"
International Conference on Educational Data Mining (EDM), July 2023
J. Lee and A. S. Lan,
"SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual Cues,"
International Conference on Artificial Intelligence in Education (AIED), July 2023
H. McNichols, M. Zhang, and A. S. Lan,
"Algebra Error Classification with Language Models,"
International Conference on Artificial Intelligence in Education (AIED), July 2023
W. Feng, A. Ghosh, S. Sireci, and A. S. Lan,
"Balancing Test Accuracy and Security in Computerized Adaptive Testing,"
International Conference on Artificial Intelligence in Education (AIED), July 2023
A. Ghosh and A. S. Lan,
"DiFA: Differentiable Feature Acquisition,"
AAAI Conference on Artificial Intelligence (AAAI), Feb. 2023
N. Liu, Z. Wang, R. Baraniuk, and A. S. Lan,
"GPT-based Open-ended Knowledge Tracing for Computer Science Education,"
Conference on Empirical Methods in Natural Language Processing (EMNLP), Dec. 2022
Y. Chu, S. Hosseinalipour, E. Tenorio, L. Castro, K. Douglas, A. S. Lan, and C. Brinton
"Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning,"
ACM International Conference on Information and Knowledge Management (CIKM), Oct. 2022
N. Fernandez, A. Ghosh, N. Liu, Z. Wang, R. Baraniuk, and A. S. Lan,
"Automated Scoring for Reading Comprehension via In-context BERT Tuning,"
International Conference on Artificial Intelligence in Education (AIED), July 2022
M. Zhang, S. Baral, N. Heffernan, and A. S. Lan,
"Automatic Short Math Answer Grading via In-context Meta-learning,"
International Conference on Educational Data Mining (EDM), July 2022
A. Scarlatos, C. Brinton, and A. S. Lan,
"Process-BERT: A Framework for Representation Learning on Educational Process Data,"
International Conference on Educational Data Mining (EDM), July 2022
A. Ghosh, S. Mitra, and A. S. Lan,
"DiPS: Differentiable Policy for Sketching in Recommender Systems,"
AAAI Conference on Artificial Intelligence (AAAI), Feb. 2022
D. S. McNamara, T. Arner, R. Butterfuss, D. B. Mallick, A. S. Lan, R. D. Roscoe, H. L. Roediger III, and R. G. Baraniuk,
"Situating AI (and Big Data) in the Learning Sciences: Moving Toward Large-Scale Learning Sciences,"
In Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology, CRC Press
Y. Chu, E. Tenorio, L. Castro, K. Douglas, A. S. Lan, and C. Brinton,
"Click-Based Student Performance Prediction: A Clustering Guided Meta-Learning Approach,"
IEEE International Conference on Big Data, Dec. 2021
Z. Wang, M. Zhang, R. G. Baraniuk, and A. S. Lan,
"Scientific Formula Retrieval via Tree Embeddings,"
IEEE International Conference on Big Data, Dec. 2021
Z. Wang, R. G. Baraniuk, and A. S. Lan,
"Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints,"
Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov. 2021
G. Lan, M. Imani, Z. Liu, J. Manjarres, W. Hu, A. S. Lan, D. Smith, and M. Gorlatova,
"MetaSense: Boosting RF Sensing Accuracy using Dynamic Metasurface Antenna,"
IEEE Internet of Things Journal, Vol. 8, Issue 18, Sep. 2021
A. Ghosh and A. S. Lan,
"BOBCAT: Bi-level Optimization-Based Computerized Adaptive Testing,"
International Joint Conference on Artificial Intelligence (IJCAI), Aug. 2021
M. Zhang, Z. Wang, R. G. Baraniuk, and A. S. Lan,
"Math Operation Embeddings for Open-ended Solution Analysis and Feedback,"
International Conference on Educational Data Mining (EDM), June 2021
A. Ghosh and A. S. Lan,
"Contrastive Learning Improves Model Robustness Under Label Noise,"
Learning from Limited or Imperfect Data (L^2ID) Workshop at CVPR, June 2021
A. Ghosh, J. Raspat, and A. S. Lan,
"Option Tracing: Beyond Correctness Analysis in Knowledge Tracing,"
International Conference on Artificial Intelligence in Education (AIED), June 2021
Z. Wang, A. S. Lan, and R. G. Baraniuk,
"Mathematical Formula Representation via Tree Embeddings,"
3rd Workshop on Intelligent Textbooks @ AIED, June 2021
S. Maghsudi, A. S. Lan, J. Xu, and M. van der Schaar,
"Personalized Education in the AI Era: What to Expect Next?"
IEEE Signal Processing Magazine, Vol. 38, Issue 3, Apr. 2021
B. Zylich and A. S. Lan,
"Linguistic Skill Modeling for Second Language Acquisition,"
International Conference on Learning Analytics and Knowledge (LAK), Apr. 2021
S. Karumbaiah, A. S. Lan, S. Nagpal, R. Baker, A. Botelho, and N. Heffernan,
"Using Past Data to Warm Start Active Machine Learning: Does Context Matter?"
International Conference on Learning Analytics and Knowledge (LAK), Apr. 2021, best paper nominee
A. Ghosh and A. S. Lan,
"Do We Really Need Gold Samples for Sample Weighting under Label Noise?"
Winter Conference on Applications of Computer Vision (WACV), Jan. 2021
A. Ghosh, B. Woolf, S. Zilberstein, and A. S. Lan,
"Skill-based Career Path Modeling and Recommendation,"
IEEE International Conference on Big Data, Dec. 2020, best student paper award
A. Ghosh and A. S. Lan,
"Option Tracing: Beyond Binary Knowledge Tracing,"
3rd Place, Tasks 1&2, NeurIPS 2020 Education Challenge
A. Ghosh and A. S. Lan,
"A Meta-learning Framework for Personalized Question Selection,"
1st Place, Task 4, NeurIPS 2020 Education Challenge
A. Winchell, A. S. Lan, and M. C. Mozer,
"Highlights as an Early Predictor of Student Comprehension and Interests,"
Cognitive Science, Vol. 44, Issue 11, Nov. 2020
S. Pandey, A. S. Lan, G. Karypis, and J. Srivastava,
"Learning Student Interest Trajectory for MOOC Thread Recommendation,"
IEEE International Conference on Data Mining Workshops (ICDMW), Nov. 2020
T. Yang, A. S. Lan, and K. Narasimhan,
"Robust and Interpretable Grounding of Spatial Referencesw ith Relation Networks,"
Conference on Empirical Methods in Natural Language Processing (EMNLP) Findings, Nov. 2020
Y. Zhang, H. Dai, Y. Yun, S. Liu, A. S. Lan, and X. Shang,
"Meta-knowledge Dictionary Learning on 1-bit Response Data for Student Knowledge Diagnosis,"
Knowledge-Based Systems 205(12), Oct. 2020
A. Ghosh, N. Heffernan, and A. S. Lan,
"Context-Aware Attentive Knowledge Tracing,"
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Aug. 2020
S. Sonkar, A. S. Lan, A. E. Waters, P. Grimaldi, and R. G. Baraniuk,
"qDKT: Question-centric Deep Knowledge Tracing,"
International Conference on Educational Data Mining (EDM), July 2020
Z. Wang, Y. Gu, A. S. Lan, and R. G. Baraniuk,
"VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics,"
International Conference on Educational Data Mining (EDM), July 2020
B. Zylich, A. Viola, B. Toggerson, L. Al-Hariri, and A. S. Lan,
"Exploring Automated Question Answering Methods for Teaching Assistance,"
International Conference on Artificial Intelligence in Education (AIED), July 2020
A. S. Lan, A. Botelho, S. Karumbaiah, R. S. Baker, and N. Heffernan,
"Accurate and Interpretable Sensor-free Affect Detectors via Monotonic Neural Networks,"
International Conference on Learning Analytics & Knowledge (LAK), Mar. 2020
B. Woolf, A. Ghosh, A. S. Lan, S. Zilberstein, T. Juravich, A. Cohen, and O. Geho,
"AI-Enabled Training in Manufacturing Workforce Development,"
AAAI Spring Sympoisum on AI in Manufacturing, Mar. 2020
R. Ghods, A. S. Lan, T. Goldstein, and C. Studer,
"MSE-Optimal Neural Network Initialization via Layer Fusion,"
Conference on Information Sciences and Systems (CISS), pp. 1-6, Mar. 2020
Z. Ren, X. Ning, A. S. Lan, and H. Rangwala,
"Grade Prediction with Neural Collaborative Filtering,"
IEEE International Conference on Data Science and Advanced Analytics (DSAA), Oct. 2019
I. Manickam, A. S. Lan, G. Dasarathy, and R. G. Baraniuk,
"Tracing Political Ideology on Twitter During the 2016 U.S. Presidential Election,"
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Aug. 2019
Z. Wang, A. S. Lan, A. E. Waters, P. Grimaldi, and R. G. Baraniuk,
"A Meta-Learning Approach to Automatic Short Answer Grading,"
International Conference on Educational Data Mining (EDM), pp. 667-680, July 2019
T. Yang, C. Studer, R. S. Baker, N. Heffernan, and A. S. Lan,
"Active Learning for Student Affect Detection,"
International Conference on Educational Data Mining (EDM), pp. 208-217, July 2019
Z. Ren, X. Ning, A. S. Lan, and H. Rangwala,
"Grade Prediction Based on Cumulative Knowledge and Co-taken Courses,"
International Conference on Educational Data Mining (EDM), pp. 158-167, July 2019
W. Tu, C. Brinton, A. S. Lan, and M. Chiang,
"Adaptive Remediation with Multi-modal Content,"
International Conference on Human-Computer Interaction (HCII), pp. 455-468, July 2019 (invited paper)
C. Brinton, T. Yang, P. Hansen, R. Bustamante, E. Tenorio, M. Chiang, and A. S. Lan,
"Joint Prediction of Response Quality and Timing in Online Discussion Forums,"
IEEE International Conference on Distributed Computing Systems (ICDCS), pp. 1931-1940, July 2019
P. Naghizadeh, M. Gorlatova, A. S. Lan, and M. Chiang,
"Hurts to Be Too Early: Benefits and Drawbacks of Communication in Multi-Agent Learning,"
IEEE International Conference on Computer Communications (INFOCOM), pp. 622-630, Apr. 2019
T. Yang, C. Brinton, P. Mittal, M. Chiang, and A. S. Lan,
"Learning Informative and Private Representations via Generative Adversarial Networks,"
IEEE International Conference on Big Data, pp. 1534-1543, Dec. 2018
C. Brinton, S. Buccapatnam, L. Zheng, D. Cao, A. S. Lan, F. Wong, S. Ha, M. Chiang, and H. V. Poor,
"On the Efficiency of Online Social Learning Networks,"
IEEE Transactions on Networking (TON), Vol. 26, Issue 5, pp. 2076-2089, Oct. 2018
A. S. Lan, J. Spencer, Z. Chen, C. Brinton, and M. Chiang,
"Personalized Thread Recommendation for MOOC Discussion Forums,"
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), pp. 725-740, Sep. 2018
A. Aghazadeh, M. Golbabaee, A. S. Lan, and R. G. Baraniuk,
"Insense: Incoherent Sensor Selection for Sparse Signals,"
Signal Processing, Vol. 150, pp. 57-65, Sep. 2018
A. S. Lan, M. Chiang, and C. Studer,
"An Estimation and Analysis Framework for the Rasch Model,"
International Conference on Machine Learning (ICML), pp. 2889-2897, July 2018
R. Ghods, A. S. Lan, T. Goldstein, and C. Studer,
"Linear Spectral Estimators and an Application to Phase Retrieval,"
International Conference on Machine Learning (ICML), pp. 1729-1738, July 2018
W. Chen, A. S. Lan, D. Cao, C. Brinton, and M. Chiang,
"Behavioral Analysis at Scale: Learning Course Prerequisite Structures from Learner Clickstreams,"
International Conference on Educational Data Mining (EDM), pp. 66-75, July 2018
A. Winchell, M. C. Mozer, A. S. Lan, P. Grimaldi, and H. Pashler,
"Textbook Annotations as an Early Predictor of Student Learning,"
International Conference on Educational Data Mining (EDM), pp. 431-437, July 2018
Z. Wang, A. S. Lan, W. Nie, P. Grimaldi, R. Schloss, and R. G. Baraniuk,
"QG-Net: A Data-Driven Question Generation Model for Educational Content,"
ACM Conference on Learning at Scale (L@S), pp. 1-10, June 2018
D. Cao, A. S. Lan, W. Chen, C. Brinton, and M. Chiang,
"Learner Behavioral Feature Refinement and Augmentation using GANs,"
International Conference on Artificial Intelligence in Education (AIED), pp. 41-46, June 2018
M. Khodak, L. Zheng, A. S. Lan, C. Joe-Wong, and M. Chiang,
"Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies,"
IEEE International Conference on Computer Communications (INFOCOM), Apr. 2018
A. S. Lan, M. Chiang, and C. Studer,
"Linearized Binary Regression,"
Conference on Information Sciences and Systems (CISS), pp. 1-6, Mar. 2018
R. Ghods, A. S. Lan, T. Goldstein, and C. Studer,
"PhaseLin: Linear Phase Retrieval,"
Conference on Information Sciences and Systems (CISS), pp. 1-6, Mar. 2018
A. S. Lan, A. E. Waters, C. Studer, and R. G. Baraniuk,
"BLAh: Boolean Logic Analysis for Graded Student Response Data,"
IEEE Journal of Selected Topics in Signal Processing (JSTSP), Vol. 11, Issue 5, pp. 754-764, Aug. 2017
A. Aghazadeh, A. S. Lan, A. Shrivastava, and R. G. Baraniuk,
"RHash: Robust Hashing via \ell_{\infty}-norm Distortion,"
International Joint Conference on Artificial Intelligence (IJCAI), pp. 1386-1394, Aug. 2017
A. S. Lan, C. Brinton, T. Yang, and M. Chiang,
"Behavior-Based Latent Variable Model for Learner Engagement,"
International Conference on Educational Data Mining (EDM), pp. 64-71, June 2017
J. Michalenko, A. S. Lan, and R. G. Baraniuk,
"Data-mining Textual Responses to Uncover Misconception Patterns,"
International Conference on Educational Data Mining (EDM), pp. 208-213, June 2017
Z. Wang, A. S. Lan, and R. G. Baraniuk,
"A Latent Factor Model For Instructor Content Preference Analysis,"
International Conference on Educational Data Mining (EDM), pp. 290-295, June 2017
A. E. Waters, P. Grimaldi, A. S. Lan, and R. G. Baraniuk,
"Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact,"
International Conference on Educational Data Mining (EDM), pp. 374-375, June 2017
J. Michalenko, A. S. Lan, and R. G. Baraniuk,
"Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks,"
International Conference on Educational Data Mining (EDM), pp. 350-351, June 2017
J. Michalenko, A. S. Lan, and R. G. Baraniuk,
"Data-mining Textual Responses to Uncover Misconception Patterns,"
ACM Conference on Learning at Scale (L@S), pp. 245-248, Apr. 2017 (work-in-progress session)
I. Manickam, A. S. Lan, and R. G. Baraniuk,
"Contextual Multi-armed Bandit Algorithms for Personalized Learning Action Selection,"
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6344-6348, Mar. 2017 (invited paper)
D. Vats, A. S. Lan, C. Studer, and R. G. Baraniuk,
"Optimal Ranking of Test Items using the Rasch Model,"
Annual Allerton Conference on Communication, Control, and Computing, Sep. 2016
A. S. Lan and R. G. Baraniuk,
"A Contextual Bandits Framework for Personalized Learning Action Selection,"
International Conference on Educational Data Mining (EDM), pp. 424–429, June 2016
A. S. Lan, T. Goldstein, R. G. Baraniuk, and C. Studer,
"Dealbreaker: A Nonlinear Latent Variable Model for Educational Data,"
International Conference on Machine Learning (ICML), pp. 266–275, June 2016
A. S. Lan, C. Studer, and R. G. Baraniuk,
"Self-Expressive Clustering of Binary Data via Group Sparsity,"
Signal Processing with Adaptive Sparse Structured Representations (SPARS), July 2015
A. S. Lan, D. Vats, A. E. Waters, and R. G. Baraniuk,
"Mathematica Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions,"
ACM Conference on Learning at Scale (L@S), pp. 167–176, Mar. 2015
A. S. Lan, C. Studer, and R. G. Baraniuk,
"Time-Varying Learning and Content Analytics via Sparse Factor Analysis,"
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp 452–461, Aug. 2014
A. S. Lan, C. Studer, and R. G. Baraniuk,
"Quantized Matrix Completion for Personalized Learning,"
International Conference on Educational Data Mining (EDM), pp. 292–295, July 2014
A. S. Lan, A. E. Waters, C. Studer, and R. G. Baraniuk,
"Sparse Factor Analysis for Learning and Content Analytics,"
Journal of Machine Learning Research (JMLR), Vol. 15, pp. 1959–2008, June 2014
A. S. Lan, C. Studer, and R. G. Baraniuk,
"Matrix Recovery from Quantized and Corrupted Measurements,"
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4973–4977, May 2014
D. Vats, C. Studer, A. S. Lan, L. Carin, and R. G. Baraniuk,
"Test-size Reduction for Concept Estimation,"
International Conference on Educational Data Mining (EDM), pp. 292–295, July 2013
A. S. Lan, C. Studer, A. E. Waters, and R. G. Baraniuk,
"Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data,"
International Conference on Educational Data Mining (EDM), pp. 324–325, July 2013
A. S. Lan, C. Studer, A. E. Waters, and R. G. Baraniuk,
"Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics,"
International Conference on Educational Data Mining (EDM), pp. 90–97, July 2013
A. E. Waters, A. S. Lan, and C. Studer,
"Sparse Probit Factor Analysis for Learning Analytics,"
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8776–8780, July 2013 (invited paper)
Preprints
A. E. Waters, A. S. Lan, R. Ning, C. Studer, and R. G. Baraniuk,
"SPRITE: A Data-Driven Response Model For Multiple Choice Questions,"
Feb. 2016
D. Vats, C. Studer, A. S. Lan, L. Carin, and R. G. Baraniuk,
"Test-size Reduction via Sparse Factor Analysis,"
Apr. 2014
Patents
R. G. Baraniuk, A. S. Lan, C. Studer, and A. E. Waters,
"Sparse Factor Analysis for Learning Analytics and Content Analytics,"
US Patent 9,704,102, July 2017
A. S. Lan, D. Vats, A. E. Waters, and R. G. Baraniuk,
"Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions,"
US Patent App. No. 14/967,131, June 2016