Multilingual NLP
Language technologies often fail beyond a handful of well-resourced languages, leaving billions of speakers vulnerable to disinformation and harmful content. This project develops multilingual approaches for detecting fake news, false claims, and machine-generated text across diverse linguistic landscapes—spanning 70+ languages. By building large-scale benchmarks and leveraging transfer learning techniques, this work directly addresses the Digital Language Divide, ensuring that information integrity tools are not limited to English or other high-resource languages but extend protection to the communities most susceptible to unchecked disinformation.
Related Publications:
- BLUFF (2026) — Benchmarking falsehoods/fake news in low-resource languages
- Beyond Speculation (2026, IEEE) — LLM-generated texts in multilingual disinformation
- MULTITuDE (2023, EMNLP) — Multilingual machine-generated text detection benchmark
- Fighting Fire with Fire (F3) (2023, EMNLP) — LLMs’ dual role in crafting/detecting disinformation
- Detecting False Claims in Low-Resource Regions (2022, ACL) — Caribbean false claim detection
I completed my Ph.D. in Informatics at Penn State University (defended May 2026; formal conferral August 2026), where I conducted research at the PIKE Research Lab under Dr. Dongwon Lee and the College of IST. Starting August 2026, I will join the Department of Information Science at the College of Media, Communication and Information (CMDI), University of Colorado Boulder, as a Tenure-Track Assistant Professor and founding Director of the Secure and Ethical AI Lab (SEAL). My research advances trustworthy and equitable AI for the world’s languages and communities — spanning multilingual NLP, low-resource and dialectal language technology, AI safety, and information integrity, with work extending across 70+ languages. I have authored 14+ peer-reviewed papers with 315+ citations in premier venues including ACL, EMNLP, NAACL, ICML, KDD, and IEEE.
My doctoral research focuses on bridging the digital language divide through transfer learning, classification (NLU), generation (NLG), adversarial attacks, and developing end-to-end AI pipelines using RAG and Agentic AI workflows for combating multilingual threats. Drawing from my Grenadian background and knowledge of local Creole languages, I bring a global perspective to AI challenges, working to democratize state-of-the-art AI capabilities for underserved linguistic communities worldwide. My mission is to develop robust multilingual multimodal systems and mitigate evolving security vulnerabilities while enhancing access to human language technology through cutting-edge solutions.
As an NSF LinDiv Fellow, I conduct transdisciplinary research advancing human-AI language interaction for social good. I actively mentor 5+ research interns and teach Applied Generative AI courses. Through industry experience at Lawrence Livermore National Lab, Interaction LLC, and Coalfire, I bridge academic research with practical applications in combating evolving security threats and enhancing global AI accessibility. I see multilingual advances and interdisciplinary collaboration as a competitive advantage, not a communication challenge. Beyond research, I stay active through dance, fitness, martial arts, and community service.