Battista Biggio

PhD, Assistant Professor at PRA Lab, and Co-Founder of Pluribus One.

Twitter:   @biggiobattista

New personal webpage (updated):


Press: May 25, 2021. Interview on Communications of ACM: Deceiving AI. 

News: May 20, 2021. Lecture on "Trustworthy AI: Poisoning Attacks on AI" - AI for Good Trustworthy AI Seminar Series.

News: Invited speaker at CASA Distinguished Lecture Series on June 10, 2020. The video of my lecture "Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning" is available below.

News: Invited speaker at Avast's conference on CyberSec & AI, held in Prague, Czech Republic, on Oct. 25, 2019. The video of my lecture on Machine Learning Security: Adversarial Attacks and Defenses is available below.

Press: July 27, 2020. Short comment on Wired about AI/ML security testing in big companies and its automation in software development pipelines.

Press: May 11, 2020. Short comment on Wired about adversarial T-shirts against YOLO and R-CNN object detectors.

Press: Nov. 10, 2019. Short comment on NYT about Professor Dawn Song's work on adversarial stop signs.

Press: Aug. 30, 2019. Article on ZeroUnoWeb (in Italian) on AI security.

Press: Apr. 24, 2019. Interview on New Scientist about adversarial examples and AI.

Press: Mar 4, 2019. Interview on El Pais about deepfake videos (in Spanish).

Press: Feb 21, 2019, The Register features our recent article on transferability of adversarial attacks against machine learning here.

Press: Jan 03, 2019, Interview on Bloomberg about AI & hackers.

News: Invited speaker at the IBM workshop Nemesis '18, co-located with ECML-PKDD 2018 in Dublin. Slides available here.

News: Invited speaker at the "Winter School on Quantitative Systems Biology: Learning and AI", held in Trieste, Italy, on Nov. 15-16, 2018. The video of the first part of this lecture on Adversarial Machine Learning is available below (slides can be downloaded from the website of the school).

Press: April 29, 2018, Interview on WIRED "AI can help cybersecurity - if it can fight through the hype"

Press: March 9, 2018, Interview on WIRED "AI has a hallucination problem that's proving tough to fix"

Our ICCV 2017 Tutorial on Adversarial Pattern Recognition and Machine Learning is available on youtube. The associated review article "Wild Patterns: Ten Years after the Rise of Adversarial Machine Learning" is now on ArXiv: The tutorial webpage contains also slides from the follow-up editions at IJCAI-ECAI '18, EUSIPCO '18, ECCV '18, ACM CCS '18.

Short biography. Battista Biggio received the MSc degree in Electronic Engineering, with honors, and the PhD in Electronic Engineering and Computer Science, respectively in 2006 and 2010, from the University of Cagliari (Italy). Since 2007 he has been working for the Department of Electrical and Electronic Engineering of the same University, where he currently is an Assistant Professor. From May 12th, 2011 to November 12th, 2011, he visited the University of Tuebingen (Germany), and worked on the security of machine learning algorithms to contamination of training data.

Research interests. His research interests currently include:

  • secure / robust machine learning and pattern recognition methods (adversarial learning);
  • multiple classifier systems;
  • and kernel methods;

with applications in biometric recognition, spam filtering, malware detection, and intrusion detection in computer networks.

Italian National Scientific Qualification. Dr. Biggio obtained the Italian National Scientific Qualification for the role of Full Professor in Computer Engineering on July 30, 2020, and of Full Professor in Computer Science on April 29, 2021; and for the role of Associate Professor in Computer Engineering on April 04, 2017, and of Associate Professor in Computer Science on April 10, 2017.
Reviewer activity / memberships. Dr. Biggio serves as a reviewer for several international conferences and journals, including Pattern Recognition and Pattern Recognition Letters. He is a Senior Member of the IEEE Institute of Electrical and Electronics Engineers (Computer Society, and Systems, Man, and Cybernetics Society), and of the Italian Group of Italian Researchers in Pattern Recognition (GIRPR/CVPL), affiliated to the International Association for Pattern Recognition. Since January 2017, he has been nominated chair of the IAPR Technical Committee 1 on Statistical Pattern Recognition Techniques. He is Associate Editor of Elsevier Pattern Recognition, IEEE Trans. on Neural Networks and Learning Systems, and the IEEE Computational Intelligence Magazine.
He has co-chaired and organized DLS (2020, 2019), AISec (2019, 2018, 2017), and S+SSPR (2020, 2018, 2016). He has also served as PC member for several conferences, including (but not limited to):