Biography
Lulwah AlKulaib is a Computer Science PhD candidate at Virginia Tech's National Capital Region campus, under the guidance of Professor Chang-Tien Lu. Her research develops innovative models that have practical applications in social media analytics, the study of low-resource languages, and public health initiatives. Lulwah's current research is a synthesis of her prior experience in various research roles and a interest in Natural Language Processing, Machine Learning, and Deep Learning. She is dedicated to advancing these fields by creating robust algorithms that can effectively navigate and interpret the complexities of human language and behavior.
Interests
- Artificial Intelligence
- Computational Linguistics
- Information Retrieval
- Social Network Analysis
- Behavioral Modeling
Education
-
PhD in Computer Science, 2024 (expected)
Virginia Tech
-
MSc in Computer Science, 2018
George Washington University
-
BSc in Computer Science, 2011
Gulf University for Science and Technology
Experience
Teaching Assistant
Kuwait University
Computer Science Teaching Assistant on a scholarship as a PhD candidate at Virginia Tech.
Research Intern
Stanford Muslim Mental Health and Islamic Psychology Lab
As a research intern on the Suicide Response Team, I play a role in performing data analysis for multiple research projects. My responsibilities are centered on extracting insights from complex datasets to support the team's objectives in developing evedince-based conclusions for our research.
Graduate Teaching Assistant
Virginia Tech
In the Fall semester of 2023, I served as a Graduate Teaching Assistant for a Web Application Development class, where I provided academic support through dedicated office hours for student inquiries. My responsibilities also included the grading of assignments, ensuring timely and constructive feedback.
Summer Intern
BEM Controls, Advanced Research Institute – Virginia Tech
During my MS at GWU, I completed a three-month internship at BEM Controls in Summer 2017, where I developed a cross-platform mobile application for energy management using React Native, compatible with both iOS and Android systems.
Programmer
Kuwait Institute for Scientific Research (KISR)
In my role as a programmer within the Technology Applications for Special Needs Section, I collaborated with a team to deliver technical support and develop tailored software solutions for individuals with disabilities, including creating Arabic interfaces and integrating specialized hardware. Our work involved thorough research and showcased our results in publications.
Trainee
Public Institution for Social Security (PIFSS)
As a recent graduate, I was selected for the Kuwaiti IBM Workforce Development Initiative at the Public Institution for Social Security, where I honed my skills in web and mobile development under the mentorship of IBM professionals and contributed to the development and deployment of the PIFSS mail and document tracking system.
Publications
(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).
(2023). UniMHe: Unified Multi Hyperedge Prediction A Case Study on Crime Dataset.
In 2023 2023 IEEE International Conference on Big Data, Special Session: Machine Learning on Big Data (MLBD 2023).
(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.
(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.
(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).
(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).
(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.
(2022). Twitter Bot Identification: An Anomaly Detection Approach.
In 2022 IEEE International Conference on Big Data (Big Data) (pp. 3577-3585). IEEE.
(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.
(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.
(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.
(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.
(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.
(2018). Twitter Bots Multiclass Classification Using Bot-Like Behavior Features (Master's dissertation, The George Washington University).
(2018). Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate.
American journal of public health, 108(10), 1378-1384.
(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.
