Publications, citations, h-index, i10-index: Google Scholar Citation Record

Research interests:

I am broadly interested in data science and artificial intelligence with a focus on data mining and machine learning. Specifically, my main thrust is in developing principled methodologies and practical tools for the transformation of heterogeneous, disparate, noisy bibliographic/clinical/genomic/molecular data into insightful, accessible, and reliable knowledge for supporting continued scientific advancement.

Joined College of Engineering: 2022

Lab: Data Mining and Machine Learning Laboratory

Selected recent publications:

Kishlay Jha and Aidong Zhang. Continual Knowledge Infusion into Pre-trained Biomedical Language Models. Bioinformatics, Oxford University Press, February 2022

Kishlay Jha, Guangxu Xun, Nan Du, and Aidong Zhang. Knowledge-guided Efficient Representation Learning for Biomedical Domain.  Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2021), Singapore, August 2021

Kishlay Jha, Guangxu Xun, and Aidong Zhang. Continual Representation Learning for Evolving Biomedical Bipartite Networks. Bioinformatics, Oxford University Press, February 2021.

Kishlay Jha, Guangxu Xun, Yaqing Wang, and Aidong Zhang. Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts.  Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August 2019.

Kishlay Jha, Guangxu Xun, Vishrawas Gopalakrishnan, and Aidong Zhang. DWE-Med: Dynamic Word Embeddings for Medical Domain. ACM Transactions on Knowledge Discovery from Data (TKDD), 2019

Xun, Guangxu, Kishlay Jha, Ye Yuan, Yaqing Wang, and Aidong Zhang. "MeSHProbeNet: a self-attentive probe net for MeSH indexing." Bioinformatics 35, no. 19 (2019): 3794-3802.

Kishlay Jha, Guangxu Xun, Yaqing Wang, Vishrawas Gopalakrishnan, and Aidong Zhang. Concepts-Bridges: Uncovering Conceptual Bridges Based on Biomedical Concept Evolution.  Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, United Kingdom, August 2018.

Research areas:

• Data Mining
• Machine Learning
• Natural Language Processing
• Bioinformatics
• Health Informatics