Maria Gorlatova

Nortel Networks Assistant Professor of Electrical and Computer Engineering

Dr. Maria Gorlatova's research is focused on reaching the next level of adaptive intelligent behavior in Internet of Things systems and applications. This research involves the development of architectures, algorithms, and protocols for emerging pervasive systems. It crosses traditional discipline boundaries and requires thinking across multiple layers of system and protocol stacks. 

Dr. Gorlatova earned her Ph.D. in Electrical Engineering from Columbia University, and her M.Sc. and B.Sc. (Summa Cum Laude) degrees in Electrical Engineering from University of Ottawa, Canada. She has several years of industry experience, where she had been affiliated with Telcordia Technologies, IBM, and D. E. Shaw Research. She came to Duke from Princeton University, where she held the positions of an Associate Research Scholar in the Electrical Engineering Department and an Associate Director of the Princeton EDGE Lab. 

Dr. Gorlatova is a recipient of the Google Anita Borg USA Fellowship, Canadian Graduate Scholar CGS NSERC Fellowships, the Columbia University Presidential Fellowship, and the Columbia University Jury Award for Outstanding Achievement in Communications. She is a co-recipient of the ACM SenSys Best Student Demonstration Award, the IEEE Communications Society Young Author Best Paper Award, and the IEEE Communications Society Award for Advances in Communications.

Appointments and Affiliations

  • Nortel Networks Assistant Professor of Electrical and Computer Engineering
  • Assistant Professor of Electrical and Computer Engineering
  • Faculty Network Member of the Duke Institute for Brain Sciences

Contact Information

Education

  • B.S. University of Ottawa (Canada), 2004
  • M.S. University of Ottawa (Canada), 2007
  • Ph.D. Columbia University, 2013

Research Interests

Architectures, algorithms, and protocols for emerging mobile pervasive systems and the Internet of Things. Our work crosses traditional discipline boundaries and requires thinking across multiple layers of system and protocol stacks. We are focusing on breaking the barriers for technologies that enable fundamentally new deployments and experiences, such as energy harvesting, artificial intelligence adapted to the Internet of Things constraints, and augmented reality.

Awards, Honors, and Distinctions

  • Best Research Artifact Award. IEEE IPSN. 2020
  • N2 Women Rising Star. Networking Networking Women (N2Women). 2019
  • Young Author Best Paper Award. IEEE Communications Society. 2016
  • Jury Award for Outstanding Achievement in Communications. Columbia University Electrical Engineering Department. 2013
  • Anita Borg USA Fellowship. Google. 2012
  • Award for Advances in Communications. IEEE Communications Society. 2011
  • Best Student Demonstration Award. ACM SenSys. 2011
  • Presidential Fellowship. Columbia University. 2008
  • Alexander Graham Bell Canada Graduate CGS-D Scholarship. Natural Sciences and Engineering Research Council Canada. 2008

Courses Taught

  • COMPSCI 356: Computer Network Architecture
  • COMPSCI 391: Independent Study
  • COMPSCI 393: Research Independent Study
  • COMPSCI 394: Research Independent Study
  • COMPSCI 590: Advanced Topics in Computer Science
  • ECE 292: Projects in Electrical and Computer Engineering
  • ECE 356: Computer Network Architecture
  • ECE 391: Projects in Electrical and Computer Engineering
  • ECE 392: Projects in Electrical and Computer Engineering
  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 899: Special Readings in Electrical Engineering
  • EGR 393: Research Projects in Engineering
  • NEUROSCI 493: Research Independent Study 1

In the News

Representative Publications

  • Jiang, Y., W. Wang, T. Scargill, M. Rothman, J. Dunn, and M. Gorlatova. “Digital biomarkers reflect stress reduction after Augmented Reality guided meditation: A feasibility study.” In Digibiom 2022  Proceedings of the 2022 Emerging Devices for Digital Biomarkers, 29–34, 2022. https://doi.org/10.1145/3539494.3542754.
  • Manjarres, J., G. Lan, M. Gorlatova, M. Hassan, and M. Pardo. “Deep Learning for Detecting Human Activities from Piezoelectric-Based Kinetic Energy Signals.” Ieee Internet of Things Journal 9, no. 10 (May 15, 2022): 7545–58. https://doi.org/10.1109/JIOT.2021.3093245.
  • Zhang, Y., T. Scargill, A. Vaishnav, G. Premsankar, M. Di Francesco, and M. Gorlatova. “InDepth: Real-time Depth Inpainting for Mobile Augmented Reality.” Proceedings of the Acm on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, no. 1 (March 1, 2022). https://doi.org/10.1145/3517260.
  • Han, Y., Y. Chen, R. Wang, J. Wu, and M. Gorlatova. “Intelli-AR Preloading: A Learning Approach to Proactive Hologram Transmissions in Mobile AR.” Ieee Internet of Things Journal, January 1, 2022. https://doi.org/10.1109/JIOT.2022.3159554.
  • Zhang, X., S. Chen, Y. Zhang, Y. Im, M. Gorlatova, S. Ha, and C. Joe-Wong. “Optimal Network Protocol Selection for Competing Flows via Online Learning.” Ieee Transactions on Mobile Computing, January 1, 2022. https://doi.org/10.1109/TMC.2022.3162880.