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Maria Gorlatova

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
  • Assistant Professor of Computer Science
  • Faculty Network Member of the Duke Institute for Brain Sciences

Contact Information

Education

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

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 393: Research Independent Study
  • COMPSCI 394: Research Independent Study
  • COMPSCI 564: Edge Computing
  • COMPSCI 590: Advanced Topics in Computer Science
  • ECE 291: Projects in Electrical and Computer Engineering
  • 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 654: Edge Computing
  • ECE 891: Internship
  • ECE 899: Special Readings in Electrical Engineering
  • EGR 393: Research Projects in Engineering
  • NEUROSCI 493: Research Independent Study 1
  • NEUROSCI 494: Research Independent Study 2

In the News

Representative Publications

  • Zhang, X; Chen, S; Zhang, Y; Im, Y; Gorlatova, M; Ha, S; Joe-Wong, C, Optimal Network Protocol Selection for Competing Flows via Online Learning, Ieee Transactions on Mobile Computing, vol 22 no. 8 (2023), pp. 4822-4836 [10.1109/TMC.2022.3162880] [abs].
  • Wang, S; Hosseinalipour, S; Gorlatova, M; Brinton, CG; Chiang, M, UAV-Assisted Online Machine Learning Over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach, Ieee Transactions on Network and Service Management, vol 20 no. 2 (2023), pp. 1847-1865 [10.1109/TNSM.2022.3216326] [abs].
  • Eom, S; Janamsetty, R; Hadziahmetovic, M; Pajic, M; Gorlatova, M, Demo Abstract: Edge-based Augmented Reality Guidance System for Retinal Laser Therapy via Feature Matching, Ipsn 2023 Proceedings of the 2023 22nd International Conference on Information Processing in Sensor Networks (2023), pp. 366-367 [10.1145/3583120.3589814] [abs].
  • Jiang, X; Gorlatova, M; Hu, W, Message from General and Technical Program Chairs, Ipsn 2023 Proceedings of the 2023 22nd International Conference on Information Processing in Sensor Networks (2023) [10.1145/3583120] [abs].
  • Duan, L; Chen, Y; Gorlatova, M, Demo Abstract: BiGuide: A Bi-level Data Acquisition Guidance for Object Detection on Mobile Devices, Ipsn 2023 Proceedings of the 2023 22nd International Conference on Information Processing in Sensor Networks (2023), pp. 368-369 [10.1145/3583120.3589809] [abs].