Carnegie Mellon University

Giulia Fanti

Giulia Fanti

Assistant Professor, Electrical and Computer Engineering

5000 Forbes Avenue
Electrical and Computer Engineering Department
Pittsburgh, PA 15213


Fanti works on the algorithmic foundations of blockchains, specifically with regards to making them more efficient and scalable. She is interested in reducing the energy cost of Bitcoin and similar cryptocurrencies.




Blockchains are useful for storing data in distributed systems with limited trust. I am interested in designing scalable blockchains that account for resource constraints in the network and in individual devices. This work ranges from protecting users' privacy to building faster consensus algorithms. A common theme in this work relies on explicitly modeling device or network behavior, and using these models to design more efficient algorithms with theoretical guarantees.

Generative Adversarial Networks

Generative adversarial networks (GANs) are a technique for learning a generative model from data. They have been tremendously successful at producing high-quality, sharp images. However, they are not well-understood. I am interested in studying the dynamics of GANs themselves (e.g. improving diversity and interpretability), as well as using them for the release of privacy-preserving datasets.

Privacy-preserving communication

Recent years have brought increasing levels of surveillance. I am interested in designing privacy-preserving algorithms that enable people to communicate freely without sacrificing privacy. I have been working on a few main problems within this theme, related to anonymous social media (e.g., Yik Yak, Secret) and anonymous peer-to-peer networks (e.g., Bitcoin, cryptocurrencies). A common theme in this work is that we wish to provide statistical anonymity guarantees against computationally-unbounded adversaries.



  • Compounding of Wealth in Proof-of-Stake Cryptocurrencies
    G. Fanti, L. Kogan, S. Oh, K. Ruan, P. Viswanath, G. Wang 
  • Routing Cryptocurrency in the Spider Network (to appear in HotNets 2018)
    V. Sivaraman, S. B. Venkatakrishnan, M. Alizadeh G. Fanti, P. Viswanath
  • PacGAN: The Power of Two Samples in Generative Adversarial Networks (to appear in NIPS 2018)
    Z. Lin, A. Khetan, G. Fanti, S. Oh 
    [arXiv] [Code]
  • Dandelion++: Lightweight Cryptocurrency Networking with Formal Anonymity Guarantees 
    G. Fanti, S. B. Venkatakrishnan, S. Bakshi, B. Denby, S. Bhargava, A. Miller, P. Viswanath 
    [Sigmetrics 2018] [Simulation code] [Bitcoin Core reference implementation] [Bitcoin Magazine]



  • Rumor Source Obfuscation on Irregular Trees 
    G. Fanti, P. Kairouz, S. Oh, K. Ramchandran, P. Viswanath 
    [Sigmetrics 2016] [code] [slides]
  • Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries
    G. Fanti, V. Pihur, U. Erlingsson 
    [PETS 2016] [code]
  • Metadata-conscious anonymous messaging 
    G. Fanti, P. Kairouz, S. Oh, K. Ramchandran, P. Viswanath 
    [ICML 2016] [IEEE TSIPN 2016] [code]
  • Algorithmic Advances in Anonymous Communication over Networks 
    G. Fanti, P. Viswanath 
    [CISS 2016]




  • Multiresolution graph signal processing via circulant structures
    V. Ekambaram, G. Fanti, B. Ayazifar, and K. Ramchandran 
    [DSP/SPE 2013]
  • Critically-sampled perfect-reconstruction spline-wavelet filter banks for graph signals
    V. Ekambaram, G. Fanti, B. Ayazifar, and K. Ramchandran 
    [GLOBESIP 2013]
  • Circulant structures and graph signal processing 
    V. Ekambaram, G. Fanti, B. Ayazifar, and K. Ramchandran 
    [ICIP 2013]


  • Wireless power transfer using weakly coupled magnetostatic resonators
    J.O. Mur-Miranda, G. Fanti, Y. Feng, K. Omanakuttan, R. Ongie, A. Setjoadi, and N. Sharpe 
    [ECCE 2010]
  • Peak wireless power transfer using magnetically coupled series resonators
    J.O. Mur-Miranda and G. Fanti 
    [EnergyCon 2010]



CMU (Spring 2018)


U.C. Berkeley (2013-2014)
  • Served as head TA for a course of 190 students. Coordinated roles and managed content development, such as homeworks and discussion notes.
  • Designed new labs centered around real-world applications like digital cameras and music recognition.
  • Led a discussion and lab section.


U.C. Berkeley (Spring 2015)
  • Served as head TA for a course of 80 students.
  • Designed homeworks and discussion lesson plans. Led a weekly discussion section.