Sepideh Ghanavati

Assistant Professor

School Computing and Information Science

University of Maine

Orono, ME

Phone: +1 (207) 581-3218

Email: sepideh[dot]ghanavati[at]

About Me

I am an assistant professor in Computer Science at the School of Computing and Information Science (SCIS) at the University of Maine and the director of Privacy Engineering - Regulatory Compliance Lab (PERC_Lab). My research interests are in the areas of information privacy and security, software  and requirements engineering and the Internet of Things (IoT). The interdisciplinary nature of this research requires me to employ a variety of research methods, including requirements and software engineering, natural language processing, machine learning, deep learning and empirical human studies.

We are thankful to Google for funding our project at PERC_Lab by Google Faculty Research Award.


Find my PGP public key here. a

Research Interests

  • Mobile and Software Privacy and Security

  • Privacy and Security for Internet of Things (IoT) 

  • Natural Language Processing - Neural Machine Translation

  • Machine Learning and Deep Learning for Privacy in Mobile Applications

  • Blockchain in Healthcare 

  • Regulatory Compliance Software Engineering

  • Usable Privacy

  • Privacy by Design and Privacy Requirements Analysis

  • (Goal-Oriented) Requirements Modeling and Requirements Engineering

Publication Index

[Google Scholar]     [DLBP]     [IEEE Xplore]

Master's and Undergraduate Students

I am now accepting BSc. and MSc. students from UMaine interested in privacy and security research in my research group, Privacy Engineering - Regulatory Compliance Lab (PERC). Please check the Projects page for information on the available projects.

Recent News


Our journal paper, RationalGRL: A Framework for Argumentation and Goal Modeling, has been accepted for publication in the Journal of Argument & Computation, 2020.


Our proposal, Advancing Legal-Technological Approaches for Protecting Privacy Rights and Civil Liberties in the Age of Big Data has been awarded as part of AI Initiative seed grant at UMaine.


Our paper, Towards Variability-Aware Legal-GRL Framework for Modeling Compliance Requirements has been accepted at the 7th International Workshop on Evolving Security & Privacy Requirements Engineering (ESPRE) at RE 2020.



Our journal paper, Populating Legal Ontologies using Semantic Role Labeling, has been published in the Springer Journal of Artificial Intelligence and Law, 2020.


We received $5,000 in Google Cloud Platform credits for our research proposal.



Our paper, Populating Legal Ontologies using Semantic Role Labeling, has been accepted at the 12th Language Resources & Evaluation Conference, 2020.


Our paper, Towards a heterogeneous IoT privacy architecture has been accepted at the 35th Annual ACM Symposium on Applied Computing, 2020.


More News.