[1] L. AlKulaib, and C.T. Lu. (2023). Balancing the Scales: HyperSMOTE for Enhanced Hypergraph Classification. In 2023 IEEE International Conference on Big Data, Special Session: Machine Learning on Big Data (MLBD 2023).

[2] A. Alhamadani, K. Althubiti, S. Sarkar, J. He, L. AlKulaib, S. Behal, M. Khan, and C.T. Lu. (2023). From Guest to Family: An Innovative Framework for Enhancing Memorable Experiences in the Hotel Industry. In 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE.

[3] L. AlKulaib,A. AlHamadani, S. Sarkar, and C.T. Lu. (2023). Hypergraph Text Classification for Mental Health Misleading Advice. In 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE.

[4] A. AlHamadani, S. Sarkar, S. Behal, L. AlKulaib, and C.T. Lu. (2023). The Efficacy of PRISTINE: Revealing Concealed Opioid Crisis Trends via Reddit Examination. Innovation in Computing, Engineering Science & Technology organized by Advances in Science, Technology and Engineering Systems Journal (ASTESJ).

[5] S. Sarkar, A. AlHamadani, S. Behal, L. AlKulaib, and C.T. Lu. (2023). Analyzing Prediction of Depression and Anxiety on Reddit: a Multi-task Learning Approach through GMMTL. Innovation in Computing, Engineering Science & Technology organized by Advances in Science, Technology and Engineering Systems Journal (ASTESJ).

[6] L. AlKulaib,A. AlHamadani, S. Sarkar, and C.T. Lu. (2022). HyperTwitter: A Hypergraph-based Approach to Identify Influential Twitter Users and Tweets. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 693-700). IEEE.

[7] L. AlKulaib, L. Zhang, Y. Sun, and C.T. Lu. (2022). Twitter Bot Identification: An Anomaly Detection Approach. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 3577-3585). IEEE.

[8] A. AlHamadani, S. Sarkar, L. AlKulaib, and C.T. Lu. (2022). Dod-explainer: Explainable drug overdose deaths predictor from crime and socioeconomic data. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 5163-5172). IEEE.

[9] S. Sarkar, A. AlHamadani, L. AlKulaib, and C.T. Lu. (2022). Predicting Depression and Anxiety on Reddit: A Multi-task Learning Approach. In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 427-435). IEEE.

[10] A. AlHamadani, S. Sarkar, L. AlKulaib, and C.T. Lu. (2022). PRISTINE: Semi-supervised Deep Learning Opioid Crisis Detection on Reddit. In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 444-453). IEEE.

[11] A. AlHamadani, S. Sarkar, L. Zhang, L. AlKulaib, and C.T. Lu. (2021). Forecasting high-risk areas of covid-19 infection through socioeconomic and static spatial analysis. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 4313-4322). IEEE.

[12] L. AlKulaib, A. AlHamadani, T. Ji, and C.T. Lu. (2020). Collect Ethically: Reduce Bias in Twitter Datasets. In Information Management and Big Data: 6th International Conference, SIMBig 2019, Lima, Peru, August 21–23, 2019, Proceedings 6 (pp. 106-114). Springer International Publishing.

[13] L. AlKulaib (2018). Twitter Bots Multiclass Classification Using Bot-Like Behavior Features (Master's dissertation, The George Washington University).

[14] D. Broniatowski, A. Jamison, S. Qi, L. AlKulaib, T. Chen, A. Benton, S. Quinn, and M. Dredze. (2018). Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate. American journal of public health, 108(10), 1378-1384.

[15] S. Qi, L. AlKulaib, and D. Broniatowski. (2018). Detecting and characterizing bot-like behavior on Twitter. In Social, Cultural, and Behavioral Modeling: 11th International Conference, SBP-BRiMS 2018, Washington, DC, USA, July 10-13, 2018, Proceedings 11 (pp. 228-232). Springer International Publishing.

[16] R. Pless, R. Begtrup, L. AlKulaib, S. Counts, J. Harnett, J. Manning, H. Xuan, and D. Broniatowski. (2017). Recognizing images of eating disorders in social media. 2nd Social Media Mining for Health Applications Shared Task @ AMIA.