What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Artificial intelligence
Computer security, Social network, Artificial intelligence, Machine learning and Computer network are his primary areas of study.
His research in Computer security intersects with topics in Adversarial system and Internet privacy.
He combines subjects such as Network topology, Data mining and Data science with his study of Social network.
His Artificial intelligence research incorporates elements of Network science and Dynamic network analysis.
His research integrates issues of Evolving networks and Bridge in his study of Machine learning.
His Traffic analysis, Access control and IP forwarding study in the realm of Computer network interacts with subjects such as Attribute-based encryption.
His most cited work include:
- Advances and Open Problems in Federated Learning (571 citations)
- SybilInfer: Detecting Sybil Nodes using Social Networks. (398 citations)
- EASiER: encryption-based access control in social networks with efficient revocation (348 citations)
What are the main themes of his work throughout his whole career to date?
Prateek Mittal mainly investigates Computer security, Artificial intelligence, Adversary, Machine learning and Computer network.
His Computer security research incorporates themes from Denial-of-service attack, Internet privacy and Social network.
His Social network research is multidisciplinary, incorporating perspectives in Sybil attack and Data science.
His Adversary study combines topics from a wide range of disciplines, such as Network topology and Theoretical computer science.
His biological study spans a wide range of topics, including Inference and Data mining.
In general Computer network, his work in Guard is often linked to Relay linking many areas of study.
He most often published in these fields:
- Computer security (30.61%)
- Artificial intelligence (19.90%)
- Adversary (17.86%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (19.90%)
- Robustness (11.73%)
- Machine learning (15.82%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Robustness, Machine learning, Computer security and Computer network.
His Robustness research integrates issues from Adversarial system and Image.
His Machine learning research is multidisciplinary, relying on both Key, Traffic analysis and Identification.
His work in Computer security covers topics such as Differential privacy which are related to areas like Secure multi-party computation.
Prateek Mittal has included themes like Adversary and Obfuscation in his Computer network study.
His Adversary research includes themes of Routing, Software deployment, IP forwarding, Backdoor and Probabilistic logic.
Between 2019 and 2021, his most popular works were:
- Advances and Open Problems in Federated Learning (28 citations)
- HYDRA: Pruning Adversarially Robust Neural Networks (16 citations)
- RobustBench: a standardized adversarial robustness benchmark (15 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Artificial intelligence
His primary areas of investigation include Artificial intelligence, Machine learning, Deep learning, Robustness and Inference.
His Machine learning study frequently links to related topics such as Adversary.
His Adversary research is multidisciplinary, incorporating elements of Inference attack, Backdoor, Probabilistic logic, Entropy and Generalization error.
His research in Robustness focuses on subjects like Adversarial system, which are connected to Receptive field and Pattern recognition.
His study in Inference is interdisciplinary in nature, drawing from both Normalization, Computer network and Complex network.
Prateek Mittal has researched Computer network in several fields, including Information technology and Abort.
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