Marco Postiglione

Marco Postiglione

Postdoctoral Research Scholar
Department of Computer Science, Northwestern University
email google scholar dblp linkedin
I develop trustworthy AI systems for social good, with applications spanning security and healthcare. My work focuses on bridging the gap between theoretical advances and deployed systems that serve real-world users, from fact-checkers and journalists to clinicians and public safety organizations. I am part of the Northwestern Security & AI Lab, led by Prof. V.S. Subrahmanian.

News

Selected Projects

GODDS
Global deepfake detection for 70+ newsrooms incl. PolitiFact & USA Today
SMART
Social movement analysis with WSJ, AP & Washington Post journalists
DEWS
Drone threat prediction deployed with Netherlands Police
NTEWS
Terrorism early warning system for national security
MNW Benchmark
Deepfake detection dataset with Microsoft AI for Good & WITNESS
Countering AI Proliferation
Executive training on countering AI proliferation threats

Selected Publications

* equal contribution · Full list on Google Scholar

The Microsoft-Northwestern-WITNESS Benchmark for Deepfake Detection
T. Roca, M. Postiglione, C. Gao, I. Gortner, Z. Wojciak, P. Wang, M. Alimardani, S. Anlen, K. White, J. Lavista Ferres, S. Kraus, S. Gregory, V. S. Subrahmanian
IEEE Intelligent Systems, vol. 41, no. 2, 2026
paper dataset
SMART: A Social Movement Analysis & Reasoning Tool with Case Studies on #MeToo and #BlackLivesMatter
V. La Gatta*, M. Postiglione*, J. Gilbert, D. W. Linna Jr, M. M. Greenfield, A. Shaw, V. S. Subrahmanian
Proceedings of the ACM Web Conference 2026 (WWW '26), pp. 9634–9644
proceedings arxiv
AI-Generated Phishing: Combining Human Behavior with Post Content to Assess Susceptibility
D. Denisenko*, V. La Gatta*, M. Postiglione*, M. Sola*, Y. Chen, V. S. Subrahmanian
ACM Transactions on Internet Technology, 2026
paper
A Nonpartisan Study of Deepfake Activity and Engagement Around the 2024 US Presidential Election
M. Postiglione*, C. Gortner, B. Fosdick, S. Gao, S. Kraus, V. S. Subrahmanian
Proceedings of the International AAAI Conference on Web and Social Media (ICWSM '26)
DEEP: A Discourse Evolution Engine for Predictions about Social Movements
V. La Gatta*, M. Postiglione*, J. Gilbert, D. W. Linna Jr, M. M. Greenfield, A. Shaw, V. S. Subrahmanian
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI '26), IAAI Track
proceedings arxiv
SOLVE-Med: Specialized Orchestration for Leading Vertical Experts across Medical Specialties
R. Di Marino, G. Dioguardi, A. Romano, G. Riccio, M. Barone, M. Postiglione, F. Amato, V. Moscato
Proceedings of the 28th European Conference on Artificial Intelligence (ECAI 2025)
GODDS: The Global Online Deepfake Detection System
M. Postiglione*, C. Baldwin, D. Denisenko, B. Fosdick, S. Gao, C. Gortner, C. Pulice, S. Kraus, V. S. Subrahmanian
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI '25)
proceedings online system
Combining Evidence and Reasoning for Biomedical Fact-Checking
F. Barone*, A. Romano, A. Riccio, M. Postiglione, V. Moscato
Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
proceedings arxiv
Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification
M. Barone, A. Romano, G. Riccio, M. Postiglione, V. Moscato
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
A Drone Early Warning System for Predicting Threatening Trajectories
T. Deb, S. de Laaf, V. La Gatta, O. Lemmens, R. Lindelauf, M. van Meerten, H. Meerveld, A. Neeleman, M. Postiglione, V. S. Subrahmanian
IEEE Intelligent Systems, 2025
paper
PIE-Med: Predicting, Interpreting and Explaining Medical Recommendations
A. Romano, G. Riccio, M. Postiglione, V. Moscato
European Conference on Information Retrieval (ECIR 2025), Lecture Notes in Computer Science, vol. 15576, pp. 6–12
Predicting Future Disorders via Temporal Knowledge Graphs and Medical Ontologies
M. Postiglione*, D. Bean, Z. Kraljevic, R. Dobson, V. Moscato
IEEE Journal of Biomedical and Health Informatics, vol. 28, no. 7, 2024
paper
TaughtNet: Learning Multi-Task Biomedical NER from Single-Task Teachers
V. Moscato*, M. Postiglione*, C. Sansone*, G. Sperlì*
IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 5, 2023
paper
CASTLE: Cluster-Aided Space Transformation for Local Explanations
V. La Gatta*, V. Moscato*, M. Postiglione*, G. Sperlì*
Expert Systems with Applications, vol. 179, 2021
paper
An Epidemiological Neural Network Exploiting Dynamic Graph Structured Data Applied to COVID-19
V. La Gatta*, V. Moscato*, M. Postiglione*, G. Sperlì*
IEEE Transactions on Big Data, vol. 7, no. 1, 2020
paper

Experience & Education

Postdoctoral Research Scholar
Northwestern University · 2024–present
Northwestern Security & AI Lab (PI: V.S. Subrahmanian). Deepfake detection, disinformation, public safety AI.
Ph.D., Computer Science & Engineering
University of Naples Federico II · 2020–2024
Biomedical NLP, few-shot learning, temporal knowledge graphs. Advisor: Vincenzo Moscato.
Visiting Researcher
King's College London · 2023–2024
Dept. of Biostatistics & Health Informatics (PI: Richard Dobson).
M.S., Computer Science & Engineering
University of Naples Federico II · 2017–2020

Teaching & Mentorship

Lecturer — Advanced AI Methods and Applications in Healthcare
University of Naples Federico II · PhD Program in ICTH · 2025
Designed and delivered a 10-hour module covering state-of-the-art machine learning techniques, deep learning architectures, and practical applications of AI in clinical and biomedical contexts. flyer
Lecturer — Countering AI Proliferation
Northwestern University · Executive Course · 2025
Co-designed and delivered an executive course with Prof. V.S. Subrahmanian for government and industry stakeholders, covering AI-enabled cyberattacks, IP theft, and malicious use of generative models. link
Guest Lecturer — AI-Based Protein Synthesis: Benefits and Risks
Northwestern University · PHYSICS 101-8 (Prof. V. Kalogera) · 2025
Invited Talk — Demonstration of Generative Malware Models
Conference on AI & National Security, Northwestern University · 2024
Guest Lecturer — An Introduction to MongoDB
University of Naples Federico II · Big Data Engineering (Prof. V. Moscato) · 2024
Guest Lecturer — Overview of Few-Shot Named Entity Recognition
Harvard University · STAT E-100 (Prof. H. Okabe) · 2022
Teaching Assistant
University of Naples Federico II · 2018–2023
Machine Learning & Big Data for Health, Big Data Engineering, Information Systems, Electronic Calculators I, Elements of Physics I & II, Elements of Informatics.
M.S. Thesis Co-supervisor
University of Naples Federico II · 2020–present
Co-supervised 40+ M.S. theses in machine learning, deep learning, and big data engineering, covering biomedical NLP, explainable AI, knowledge graphs, and recommender systems.
Computational Advisor
Human-Augmented Analytics Group (HAAG), Georgia Tech · 2024–present
Methodological guidance on ML and NLP projects for an interdisciplinary virtual research laboratory.

Patents

Systems and Methods for Automatic Detection of Human Expression from Multimedia Content
U.S. Patent US20250148826A1 · 2025
A system for analyzing multimedia content featuring a role-matching module to identify participants of interest and a scoring module that evaluates statements based on extracted facial expressions, vocal traits, and textual elements.

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