Dr. Sergio Maffeis

Associate Professor

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Biography

Sergio Maffeis is an Associate Professor in the Department of Computing at Imperial College London, focusing on web security, machine learning, and formal methods. He leads the Security and Machine Learning Lab, driving research in critical areas of cybersecurity. Dr. Maffeis has made significant contributions to the field through his publications and has served as a program committee member for leading cybersecurity conferences. His current research interests include advancing methodologies in detecting vulnerabilities, implementing machine learning techniques in intrusion detection, and exploring formal methods to enhance software security. Dr. Maffeis encourages collaboration and innovation, actively seeking outstanding PhD candidates with a solid background in formal methods, particularly those interested in security applications. He emphasizes the importance of peer-reviewed publications as a criterion for admission into PhD programs. With extensive experience in guiding students, he aims to cultivate a new generation of experts in cybersecurity.

Research Interests

Experience

Associate Professor

2016-01-01 — Present

Imperial College London • London, ENG, United Kingdom

Associate Professor in the Department of Computing, specializing in Web Security and Machine Learning.

Requirements for Imperial College London

Master Program
Requirements
GPA Requirement
Required:3.5
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:6.5
Speaking
Required:6.5
Overall
Required:7
TOEFL
Listening
Required:22
Reading
Required:22
Writing
Required:22
Speaking
Required:22
Total
Required:100
Duolingo
Overall Score
Required:125
Overall
Required:125
Prerequisites
Materials Science Mechanical Engineering Civil Engineering Chemical Engineering Physics Chemistry
Application Checklist
  • Personal statement
  • CV/resume
  • Official university transcripts
  • Two academic or professional references
  • Application fee (£90)
Specialization Notes

Specialisms available in Materials for the Energy Transition or Theory and Simulation of Materials.