Jason Lucas

Jason Lucas

Ph.D. Candidate · Incoming Assistant Professor & Director, Secure and Ethical AI Lab (SEAL) — CU Boulder (Aug 2026)

I am a PhD candidate in Informatics in the College of IST at Penn State University, where I conduct research at the PIKE Research Lab under the guidance of Dr. Dongwon Lee. 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, 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.

Program Committee Member — DAGGenC Workshop (COLING 2025) featured image

Program Committee Member — DAGGenC Workshop (COLING 2025)

Program Committee Member for the Workshop on Detecting AI Generated Content, co-located with COLING 2025 in Abu Dhabi, UAE.

avatar
Jason Lucas
The Longtail Impact of Generative AI on Disinformation: Harmonizing Dichotomous Perspectives featured image

The Longtail Impact of Generative AI on Disinformation: Harmonizing Dichotomous Perspectives

This IEEE Intelligent Systems article examines the "longtail" impact of Generative AI on disinformation in high-impact events and resource-limited settings. We analyze four …

avatar
Jason Lucas
Graduate Student Bill of Rights Committee — College of IST featured image

Graduate Student Bill of Rights Committee — College of IST

Served on the College of IST Graduate Student Bill of Rights Committee at Penn State, developing student advocacy frameworks.

avatar
Jason Lucas
Lightening Talk for the CRA-WP Grad Cohort Workshop for IDEALS featured image

Lightening Talk for the CRA-WP Grad Cohort Workshop for IDEALS

The widespread use and disruptive effects of large language models (LLMs) have led to concerns about their potential misuse, such as generating harmful and misleading content on a …

avatar
Jason Lucas
Cohere For AI Invited Talk featured image

Cohere For AI Invited Talk

In this talk we present research that tackles the misuse of large language models (LLMs) by introducing the Fighting Fire with Fire (F3) strategy, which uses GPT-3.5-turbo to …

avatar
Jason Lucas

Conference Reviewer — ACL, EACL, EMNLP

Served as reviewer for top-tier NLP conferences including ACL, EACL, and EMNLP (2024–2025).

avatar
Jason Lucas
Authorship Obfuscation in Multilingual Machine-Generated Text Detection featured image

Authorship Obfuscation in Multilingual Machine-Generated Text Detection

This research from Penn State and KiNiT, benchmarks the effectiveness of 10 authorship obfuscation (AO) techniques against 37 machine-generated text (MGT) detection methods across …

dominik-macko
Presented at the EMNLP '23 Main Conference Proceedings featured image

Presented at the EMNLP '23 Main Conference Proceedings

Michiharu Yamashita and I co-present our latest research, Titled, Fighting Fire With Fire - The Dual Role of Large Language Models in Crafting and Detecting Elusive Disinformation. …

avatar
Jason Lucas
MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark featured image

MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark

This research from Penn State and KiNiT introduces MULTITuDE, a novel multilingual dataset for detecting machine-generated text. Comprised of over 74,000 authentic and …

dominik-macko
Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation featured image

Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation

This research project is a collaboration with Penn State and MIT Lincoln Lab. Our study demonstrates the dual capacity of LLMs for offensive misuse and defense detection against …

avatar
Jason Lucas