Research Interests

My research interest lies in data mining and machine learning, with a focus on dynamical processes (e.g. spread of misinformation, diseases, failures) on large networks (e.g. web, population contact networks, critical infrastructures). My recent work include AI for influenza forecasting, e-commerce search and fraud detection, outbreak detection in hospitals, network embedding, community detection, and network summarization.

As a member of the Computational Epidemiology Group, I primarily investigate problems motivated by public health such as propagation of diseases via contact network, forecasting outbreaks of infectious diseases, and designing optimal surveillance systems.

Research Interests (Keywords)

Computational Epidemiology, Data Mining, Machine Learning, AI for Social Good

Selected Publications

• Detecting Sources of Healthcare Associated Infections. Hangkyu Jang, Andrew Fu, Jiaming Cui, Methun Kamruzzaman, B. Aditya Prakash, Anil Vullikanti, Bijaya Adhikari and Sriram Pemmaraju. AAAI Conference on Artificial Intelligence. (AAAI 2023). Feb 2023, Washington, DC.

• EINNs: Epidemiologically-Informed Neural Networks. Alexander Rodriguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari and B. Aditya Prakash. AAAI Conference on Artificial Intelligence. (AAAI 2023). Feb 2023, Washington, DC.

• Near-Optimal Spectral Disease Mitigation in Healthcare Facilities. Masahiro Kiji, D.M. Hasibul Hasan, Alberto M. Segre, Sriram Pemmaraju, and Bijaya Adhikari. IEEE International Conference on Data Mining, 2022. (ICDM 2022), Nov 2022, Orlando, FL.

• Dynamic Healthcare Embeddings for Improving Patient Care. Hankyu Jang, Sulyun Lee, D. M. Hasibul Hasan, Philip M. Polgreen, Sriram V. Pemmaraju and Bijaya Adhikari. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. (ASONAM 2022), Nov 2022, Istanbul, Turkey.

• Risk-aware Temporal Cascade Reconstruction to Detect Asymptomatic Cases. Hankyu Jang, Shreyas Pai, Bijaya Adhikari, and Sriram V. Pemmaraju. IEEE International Conference on Data Mining. (ICDM 2021), Nov 2021, Virtual.