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Dr Konstantinos Gatsis Departmental Lecturer

Dr

Konstantinos Gatsis PhD

Departmental Lecturer

Biography

Dr. Konstantinos Gatsis joined the Department of Engineering Science in 2019 as a Departmental Lecturer. Before joining Oxford, he was a Postdoctoral Researcher in the Department of Electrical and Systems Engineering at the University of Pennsylvania, Philadelphia, from 2016 to 2019.

Dr. Gatsis received the PhD degree in electrical and systems engineering from the University of Pennsylvania in 2016. He received the Joseph, D’16, and Rosaline Wolf Award for Best Doctoral Dissertation from the department of Electrical and Systems Engineering at the University of Pennsylvania. He also received the 2014 O. Hugo Schuck Best Paper Award, the Student Best Paper Award at the 2013 American Control Conference, and was a Best Paper Award Finalist at the 2014 ACM/IEEE International Conference on Cyber-Physical Systems.

His research aims to enable safe, secure, and networked autonomous systems by developing novel control, learning, and communication tools. Application domains of interest include the Industrial Internet-of-Things and Smart Cities.

Personal website

Research Interests

  • Control for Next Generation Wireless Networks and the Internet-of-Things (IoT)
  • Learning for Autonomous Systems
  • Security and Privacy
  • Control and Optimization

Research Groups

Recent Publications

Learning Robust State Observers using Neural ODEs (longer version)

Miao K & Gatsis K (2022)

BibTeX
@misc{learningrobusts-2022/12,
  title={Learning Robust State Observers using Neural ODEs (longer version)},
  author={Miao K & Gatsis K},
  year = "2022"
}

Model-Free design of control systems over wireless fading channels

Lima V, Eisen M, Gatsis K & Ribeiro A (2022), Signal Processing, 197, 108540-108540

BibTeX View PDF
@article{modelfreedesign-2022/8,
  title={Model-Free design of control systems over wireless fading channels},
  author={Lima V, Eisen M, Gatsis K & Ribeiro A},
  journal={Signal Processing},
  volume={197},
  number={108540},
  pages={108540-108540},
  publisher={Elsevier BV},
  year = "2022"
}

Age of Information in Random Access Channels

Chen X, Gatsis K, Hassani H & Bidokhti SS (2022), IEEE Transactions on Information Theory, 1-1

BibTeX View PDF
@article{ageofinformatio-2022/,
  title={Age of Information in Random Access Channels},
  author={Chen X, Gatsis K, Hassani H & Bidokhti SS},
  journal={IEEE Transactions on Information Theory},
  pages={1-1},
  publisher={Institute of Electrical and Electronics Engineers (IEEE)},
  year = "2022"
}

Federated Reinforcement Learning at the Edge

Gatsis K (2021)

BibTeX
@misc{federatedreinfo-2021/12,
  title={Federated Reinforcement Learning at the Edge},
  author={Gatsis K},
  year = "2021"
}

Adaptive scheduling for machine learning tasks over networks

Gatsis K (2021), Proceedings of the 2021 American Control Conference, 1224-1229

BibTeX View PDF
@inproceedings{adaptiveschedul-2021/7,
  title={Adaptive scheduling for machine learning tasks over networks},
  author={Gatsis K},
  booktitle={2021 American Control Conference},
  pages={1224-1229},
  year = "2021"
}

Linear regression over networks with communication guarantees

Gatsis K (2021), Proceedings of the Conference on Learning for Dynamics and Control, 144(2021), 1-12

BibTeX
@inproceedings{linearregressio-2021/6,
  title={Linear regression over networks with communication guarantees},
  author={Gatsis K},
  booktitle={3rd Annual Conference on Learning for Dynamics and Control Conference (L4DC 2021)},
  pages={1-12},
  year = "2021"
}

Adaptive Scheduling for Machine Learning Tasks over Networks

Gatsis K (2021), Proceedings of the American Control Conference, 2021-May, 1224-1229

BibTeX View PDF
@inproceedings{adaptiveschedul-2021/5,
  title={Adaptive Scheduling for Machine Learning Tasks over Networks},
  author={Gatsis K},
  booktitle={American Control Conference},
  pages={1224-1229},
  year = "2021"
}

Resource allocation in large-scale wireless control systems with graph neural networks

Lima V, Eisen M, Gatsis K & Ribeiro A (2021), IFAC-PapersOnLine, 53(2), 2634-2641

BibTeX View PDF
@inproceedings{resourceallocat-2021/4,
  title={Resource allocation in large-scale wireless control systems with graph neural networks},
  author={Lima V, Eisen M, Gatsis K & Ribeiro A},
  booktitle={21st IFAC World Congress (IFAC 2020)},
  pages={2634-2641},
  year = "2021"
}

Learning to control over unknown wireless channels

Gatsis K & Pappas GJ (2021), IFAC-PapersOnLine, 53(2), 2600-2605

BibTeX View PDF
@inproceedings{learningtocontr-2021/4,
  title={Learning to control over unknown wireless channels},
  author={Gatsis K & Pappas GJ},
  booktitle={21st IFAC World Congress (IFAC 2020)},
  pages={2600-2605},
  year = "2021"
}

Non-cooperative distributed MPC with iterative learning

Hu H, Gatsis K, Morari M & Pappas GJ (2021), IFAC-PapersOnLine, 53(2), 5225-5232

BibTeX View PDF
@inproceedings{noncooperatived-2021/4,
  title={Non-cooperative distributed MPC with iterative learning},
  author={Hu H, Gatsis K, Morari M & Pappas GJ},
  booktitle={21st IFAC World Congress},
  pages={5225-5232},
  year = "2021"
}
View all

DPhil Opportunities

If you are enthusiastic about research, feel comfortable working on new problems, and have a strong academic background, please consider applying to the DPhil program in our department and feel free to contact me about research opportunities.