Publications

Learning Code-Edit Embeddings to Model Student Debugging Behavior

Published in International Conference on Artificial Intelligence in Education, 2025

This work presents an encoder–decoder model that learns code-edit embeddings from consecutive student submissions, using test case outcomes to fine-tune large language models. The approach enables personalized code suggestions that preserve student style while improving correctness, and reveals common debugging patterns through clustering analysis.

Recommended citation: Hasnain Heickal and Andrew Lan. "Learning Code-Edit Embeddings to Model Student Debugging Behavior" International Conference on Artificial Intelligence in Education 2025, 91-98. https://arxiv.org/pdf/2502.19407?

Generating Feedback-Ladders for Logical Errors in Programming using Large Language Models

Published in Educational Data Mining, 2024

Using large language models (LLMs) to generate a “feedback-ladder,” providing multiple levels of feedback for programming assignments based on student submissions. The approach aims to offer progressively detailed feedback while considering the learning context of students, addressing limitations of existing methods that provide overly direct, one-size-fits-all feedback.

Recommended citation: Hasnain Heickal and Andrew Lan. "Generating Feedback-Ladders for Logical Errors in Programming using Large Language Models." Educational Data Mining 2024, 947-951. https://educationaldatamining.org/edm2024/proceedings/2024.EDM-posters.114/2024.EDM-posters.114.pdf

An Automatic Abstractive Text Summarization System

Published in Dhaka University Journal of Applied Science and Engineering, 2021

An abstractive text summarization system using pointer generator network and topical feature extraction.

Recommended citation: Barna, Nasid Habib, and Hasnain Heickal. "An Automatic Abstractive Text Summarization System." Dhaka University Journal of Applied Science and Engineering 6, no. 2 (2021): 39-48. https://www.banglajol.info/index.php/DUJASE/article/download/59217/41337

End-to-End Speech Synthesis for Bangla with Text Normalization

Published in 2018 5th International Conference on Computational Science/Intelligence and Applied Informatics (CSII), 2018

An end-to-end speech synthesis system in Bangla (or Bengali) using minimal training and zero language specific knowledge.

Recommended citation: Pial, Tanzir Islam, Shahreen Salim Aunti, Shabbir Ahmed, and Hasnain Heickal. "End-to-End Speech Synthesis for Bangla with Text Normalization." In 2018 5th International Conference on Computational Science/Intelligence and Applied Informatics (CSII), pp. 66-71. IEEE, 2018. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8457103

Deep Learning Based Bangla Speech-to-Text Conversion

Published in 2018 5th International Conference on Computational Science/Intelligence and Applied Informatics (CSII), 2018

A Bangla (or Bengali) Speech-to-Text conversion system using deep recurrent neural networks.

Recommended citation: Tausif, Md Tahsin, Sayontan Chowdhury, Md Shiplu Hawlader, Md Hasanuzzaman, and Hasnain Heickal. "Deep learning based bangla speech-to-text conversion." In 2018 5th International Conference on Computational Science/Intelligence and Applied Informatics (CSII), pp. 49-54. IEEE, 2018. https://ieeexplore.ieee.org/iel7/8454865/8457084/08457100.pdf