The promise of decentralized ledger-based technologies (DLTs), or blockchain,
the world and created an excitement for technology that was last seen in
the 1990s when the internet was entering mainstream. The core premise of
the technology is that DLT systems are secured by cryptography and economic
incentives, and that they are governed by decentralized consensus. As such,
it is critical that they are based on robust/sound economic and
technology principles that enable fair governance and societal progress.
My current research topics are cross-disciplinary with the objective to
define, research, and promote the technological, financial, privacy, security,
and regulatory frameworks of DLT-based systems. I also work in the area of
sentiment data analysis for fintech applications.
Central Bank Digital Currencies
Today's societal digitization continues to advance at exponential speeds
driven by technology trends. Billions of Internet of Things devices have made
their way into our daily lives,
but also into healthcare, manufacturing, and supplychains.
In contrast, the financial sector still largely operates on legacy infrastructures,
where merchants receive their payments long after they released the digital/physical
good to the consumer. In addition, the emergence of Decentralized Finance through
blockchain technology, and the accumulation of data in private silos, have demonstrated
a capacity to impact national sovereignty and monetary transmission channels.
Against this backdrop, many central banks have recently started to research and test
the issuance of digitally native fiat money or Central Bank Digital Currencies
(CBDCs)in an effort to redesign the essence and use of physical cash. CBDCs
present a broad variety of designs, which translate into manifold techno-legal and
standardization policy questions. In this context, our research
addresses the state-of-the-art of CBDCs
with a specific focus on retail CBDCs, with a focus on
of candidate architectures, techno-legal questions (more
notably privacy and AML/CFT) and regulatory compliance.
Smart Contract Automated Synthesis
The high cost and frequency of attacks against smart contract indicate that a
move towards rigorous R&D practices in this field is inevitable. Automated
synthesis techniques which take as input a specification and possibly a high-level
implementation and produce a low-level implementation of the target program are
mandatory for correct-by-construction smart contracts that run on blockchains.
To promote automated
synthesis techniques and close the research gap,
we work on the development of a template-based automated inductive synthesis framework
for smart contracts, tightly integrated with the underlying smart contract
language that is wrapped by a
novel verification environment.
Smart Contract Verification
As DLT systems grow and expand their reach across different applications,
new security questions emerge that go to the heart of the technology. There
are needs in improvements of software verification, formalism and standardization
for the underlying smart contracts. In this project we develop a formal
verification engine for smart contract programming languages such as Ethereum's
Solidity and Libra's Move.
Crypto-Economic Analysis of Blockchain Systems
Economic incentives are the foundation for DLT systems as a result
of their decentralized characteristic. As a centralized entity is
absent in a DLT system, the duty of verifying key attributes of
activities in the system relies on the system maintainers or the
miners. Therefore, economically incentivized consensus mechanisms
are critical to the security guarantee of a DLT system. We conduct
economic analysis on existing DLT systems to improve
their robustness against potential manipulations and aid design of
new incentive mechanisms that safeguard their fairness and
Decentralized Blockchain Oracles
As smart contracts cannot reach consensus on real world data outside
the ledger itself, specialized smart contracts called oracles record
such real world data in the ledger. Most oracles today do so without
the robust security guarantees of the underlying ledger itself. Our
group develops ASTRAEA, the first decentralized mechanism using
game-theoretical incentives to record real-life events in a DLT, and
continues to build improvements on it so to
provide further robust security guarantees
for data retrieval in permissionless or permissioned DLT systems.
Internet of Things (IoT)
The Internet of things is a system of interrelated (usually low-power) computing devices,
mechanical and digital machines connected through a network to perform
tasks without requiring control by a human. One of the limitations
in the growth of IoT is this of their privacy and security, where DLT
solutions present a transparent solution. The focus of this work is to
develop and integrate DLT solutions to enhance the
auditability, privacy, and security of modern IoT autonomous networks
with a focus on V2X (vehicle-to-vehicle) applications.
Machine Learning for Fintech Applications
In this topic we work along side with colleagues from Rotman School
of Management to develop machine learning applications for sentiment
analysis of financial instruments.