***UPDATE***: I have completed my Ph.D. and joined Nokia Bell Labs as a Research Scientist – Networks Researcher, doing research on blockchains and federated learning. The content below reflects my time as a Ph.D. student at Yale. For my current website at Bell Labs, please visit https://www.bell-labs.com/about/researcher-profiles/nikos-papadis.


Welcome to my website!

My name is Nikolaos (“Nikos”) Papadis, and I am a final-year Ph.D. student in Electrical Engineering at Yale University. I am a member of the Yale Institute for Network Science (YINS) and I work under the guidance of Professor Leandros Tassiulas.

At Yale, I have got an M.Sc. and an M.Phil. in Electrical Engineering. I have also been awarded the 2019 IBM Ph.D. Fellowship.

Before coming to Yale, I did my undergraduate studies at the National Technical University of Athens (NTUA) in Greece, where I got a 5-year degree in Electrical and Computer Engineering, with specializations in Network Engineering and Computer Science, graduating 3rd in my class of about 350 students with a GPA of 9.50/10.

Over the summer of 2019, I was a Research Intern at IBM Research Ireland in Dublin, working on Blockchain and IoT.
From July to December of 2021, I was an Applied Science Intern at Amazon in Luxembourg, working on Operations Research problems in the Research Science team of Amazon Transportation Services.


The general theme of my research is building secure decentralized ecosystems for the sharing economy of the future. My interests include:

  • the tradeoffs between scalability, speed, security and decentralization of blockchain networks: how to properly model them and optimize the protocols accordingly
  • the effect of different consensus mechanisms on the blockchain’s performance (mathematical analysis, networking and design aspects), and their suitability for different applications
  • how layer-2 (off-chain) payment networks like Lightning can increase their performance and scalability while maintaining privacy

The tools I have been using include:

  • stochastic modeling
  • (network) optimization
  • queueing theory
  • control
  • discrete event simulation
  • reinforcement learning

Applications include:

  • blockchain as an enabler for decentralized business entities, acting as the substrate for the interaction of distinct islands of activity connected together into a virtual organization
  • fast, cheap and secure payments over any distance for all, especially for those currently without access to the financial and banking system
  • blockchain for securing Internet-of-Things networks, combined and intertwined with digital decentralized identity (DID) mechanisms
  • data ownership and monetization: the benefits blockchain can give to ordinary users by letting them be the owners of their own data and preventing privacy breaches and unauthorized data trading
  • Decentralized Finance (DeFi), leveraging the power of smart contracts

In the past, I also performed research in the sharing economy and exchange markets space, studying their sustainability, equilibria, and incentive-compatible resource allocation in them.
During my undergraduate thesis at NTUA I designed and developed a path-based algorithm for generating recommendations for online systems using data embedding in the hyperbolic space.


In conferences:

  • N. Papadis and L. Tassiulas, “Deep Reinforcement Learning-based Rebalancing Policies for Profit Maximization of Relay Nodes in Payment Channel Networks”, 4th International Conference on Mathematical Research for the Blockchain Economy (MARBLE), 2023, Best Paper Award (arXiv pdf, ePrint pdf)
  • N. Papadis and L. Tassiulas, “Payment Channel Networks: Single-Hop Scheduling for Throughput Maximization,” IEEE International Conference on Computer Communications (INFOCOM), 2022 (link)
  • H. Niavis, N. Papadis, V. Reddy, H. Rao, L. Tassiulas, “A Blockchain-based Decentralized Data Sharing Infrastructure for Off-grid Networking”, IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020 (link, arXiv pdf of more extensive version)
  • N. Papadis, S. Borst, A. Walid, M. Grissa, L. Tassiulas, “Stochastic Models and Wide-Area Network Measurements for Blockchain Design and Analysis”, IEEE International Conference on Computer Communications (INFOCOM), 2018 (link, pdf)
  • N. Papadis, E. Stai and V. Karyotis, “A path-based recommendations approach for online systems via hyperbolic network embedding”, 2017 IEEE Symposium on Computers and Communications (ISCC), 2017 (link, pdf)

In journals:

  • N. Papadis, L. Tassiulas, “Blockchain-based Payment Channel Networks: Challenges and Recent Advances”, IEEE Access, 2020 (open access pdf)


  • M. Darlin, N. Papadis, L. Tassiulas, “Optimal Bidding Strategy for Maker Auctions”, 2020 (arXiv pdf)


  • N. Papadis, PhD thesis, “Stochastic Modeling and Optimization of Blockchain Networks”, Yale, 2023 (link, pdf)
  • N. Papadis, undergraduate thesis (in Greek, with English abstract), “Efficient recommendation algorithms for online web systems using hyperbolic network embedding”, NTUA, 2016 (link with pdf)


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