What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His primary areas of investigation include Artificial intelligence, Machine learning, Pattern recognition, Classifier and Computer security. His Artificial intelligence study frequently links to adjacent areas such as Malware. His Malware research incorporates elements of Adversary, Adversarial machine learning and Evasion.
His Machine learning research incorporates themes from Training set, Data mining and Robustness. His study focuses on the intersection of Pattern recognition and fields such as Contextual image classification with connections in the field of Backpropagation, Sensor fusion, Remote sensing and Network architecture. His Biometrics study also includes fields such as
- Fingerprint which connect with Fingerprint recognition,
- Liveness which intersects with area such as Image texture and Facial recognition system.
His most cited work include:
- Multiple Classifier Systems (1064 citations)
- Evasion attacks against machine learning at test time (939 citations)
- Wild patterns: Ten years after the rise of adversarial machine learning (474 citations)
What are the main themes of his work throughout his whole career to date?
Fabio Roli spends much of his time researching Artificial intelligence, Machine learning, Pattern recognition, Biometrics and Data mining. His study explores the link between Artificial intelligence and topics such as Computer vision that cross with problems in Liveness. His Machine learning research focuses on subjects like Malware, which are linked to Evasion.
His Biometrics study combines topics from a wide range of disciplines, such as Fingerprint, Spoofing attack, Robustness and Fingerprint. His study in Fingerprint is interdisciplinary in nature, drawing from both Fingerprint Verification Competition and Fingerprint recognition. His studies deal with areas such as Image processing and Deep learning as well as Artificial neural network.
He most often published in these fields:
- Artificial intelligence (73.95%)
- Machine learning (39.47%)
- Pattern recognition (35.26%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (73.95%)
- Machine learning (39.47%)
- Malware (9.21%)
In recent papers he was focusing on the following fields of study:
Fabio Roli mostly deals with Artificial intelligence, Machine learning, Malware, Adversarial system and Pattern recognition. His research in Artificial intelligence tackles topics such as Computer vision which are related to areas like Matching. The concepts of his Machine learning study are interwoven with issues in Contextual image classification, Training set and Data mining.
Fabio Roli has included themes like Sandbox, Robustness and Evasion in his Malware study. His Adversarial system research includes elements of Computer security, Exploit and Pattern recognition. His Pattern recognition research includes themes of Fingerprint Verification Competition and Local binary patterns.
Between 2014 and 2021, his most popular works were:
- Wild patterns: Ten years after the rise of adversarial machine learning (474 citations)
- Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization (205 citations)
- Is Feature Selection Secure against Training Data Poisoning (201 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
His primary scientific interests are in Artificial intelligence, Machine learning, Malware, Adversarial system and Deep learning. His biological study spans a wide range of topics, including Data mining and Pattern recognition. His work carried out in the field of Machine learning brings together such families of science as Classifier, Algorithm design and Training set.
His Malware research is multidisciplinary, incorporating elements of Feature, Linear classifier, Robustness and Evasion. His research investigates the connection with Adversarial system and areas like Computer security which intersect with concerns in Leverage, Phishing and Web page. His Deep learning research incorporates elements of Artificial neural network and Convolutional neural network.
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