Selected Publications
Research
2026
On the Centralization of Governance Power in Decentralized Autonomous Organizations
IEEE International Conference on Blockchain and Cryptocurrency (ICBC). Brisbane,
Australia.
We study the designs and implementations of 48 public, actively used DAOs
deployed on Ethereum and identify how three key governance mechanisms — token registration, staking, and
delegation — systematically reinforce centralization of voting power, revealing inherent trade-offs
between decentralization, security, and usability.
2026
On Exercising Governance Power in Decentralized Autonomous Organizations
IEEE International Conference on Blockchain and Cryptocurrency (ICBC). Brisbane,
Australia.
We analyze 48 public Ethereum-based DAOs to uncover trust and transparency
trade-offs in governance design, discovering a new class of governance attacks that exploit fundamental
design choices in DAO governance mechanisms — even in bug-free implementations.
2026
Cross-Rollup MEV: Non-Atomic Arbitrage on Layer-2 Blockchains
5th International Workshop on Cryptoasset Analytics (CAAW). St. Kitts.
We identify 500,000+ previously untapped arbitrage opportunities across
Arbitrum, Base, Optimism, and ZKsync, demonstrating that non-atomic arbitrage on rollups is economically
meaningful and structurally distinct from L1 Ethereum — calling for new MEV extraction strategies.
2026
A Stochastic Petri Net Approach for Evaluating Resource Utilization and Costs in
Cloud-Hosted ZK-Rollups
IEEE International Systems Conference (SysCon). Halifax, Canada.
A formal modeling approach using Stochastic Petri Nets to assess operational
behavior of ZK-Rollups in cloud environments, calibrated using empirical data from zkSync Era. We show
that increasing L2 transaction volume can reduce daily operational costs by up to 25%, with a
significant cost-efficiency vs. responsiveness trade-off.
2025
The Express Lane to Spam and Centralization: An Empirical Analysis of Arbitrum's
Timeboost
Preprint. 2025.
The first large-scale empirical study of Timeboost, analyzing 11.5M+ express
lane transactions and 151K auctions. We find express lane control is highly centralized (two entities
win 90%+ of auctions), ~22% of transactions are reverted, and secondary markets have collapsed — showing
Timeboost fails to deliver on fairness, decentralization, and spam reduction.
2025
Fairness in Token Delegation: Mitigating Voting Power Concentration in DAOs
Preprint. 2025.
An empirical study combining on-chain data from five major protocols with
off-chain DAO forum discussions. Using LLMs to extract governance interests, we show delegations are
frequently misaligned with token holders' expressed priorities and that ranking-based interfaces
exacerbate power concentration.
2025
Airdrops: Giving Money Away Is Harder Than It Seems
Preprint. 2025.
The first comprehensive empirical study of nine major airdrops. Up to 66% of
tokens are rapidly sold, often in recipients' first post-claim transaction, driven by "airdrop farmers."
We identify common design pitfalls and propose actionable guidelines for more effective airdrop
strategies.
2025
A Stochastic Performance Model for Evaluating Ethereum Layer-2 Rollups
Future Generation Computer Systems. Elsevier. 2025.
Using Stochastic Petri Nets, we show that increased adoption of Layer-2
transactions can increase system throughput by up to 20%, while latency may increase by more than 100%
with larger batches — revealing a fundamental performance trade-off in ZK-Rollup design.
2025
Understanding Blockchain Governance: Analyzing Decentralized Voting to Amend DeFi
Smart Contracts
Preprint. 2025.
An in-depth empirical study of Compound and Uniswap governance protocols,
analyzing 370+ governance proposals from inception to August 2024. As few as 3–5 voters were sufficient
to sway the majority of proposals. The cost of voting disproportionately burdens smaller token holders,
and strategic voting behaviors further distort governance outcomes.
2025
Unrolling the Performance of ZK-Rollups through Stochastic Modeling
IEEE International Conference on Systems, Man, and Cybernetics (SMC). Vienna,
Austria.
A Stochastic Petri Net model to evaluate the feasibility of ZK-Rollups by
analyzing impact on throughput and latency. Increased adoption of Layer-2 transactions can enhance
throughput by up to 20%, while latency may rise by more than 100% with larger batches — revealing a
fundamental performance trade-off.
2025
2025
The Writing is on the Wall: Analyzing the Boom of Inscriptions and its Impact on
EVM-compatible Blockchains
4th International Workshop on Cryptoasset Analytics (CAAW). Miyakojima, Japan.
On certain days inscriptions accounted for nearly 90% of transactions on
Arbitrum and ZKsync Era, and 53% on Ethereum, with 99% involving meme coin minting. ZKsync and Arbitrum
saw lower median gas fees during these surges — ZKsync Era showed a greater fee reduction than
optimistic rollups.
2025
A Public Dataset For the ZKsync Rollup
4th International Workshop on Cryptoasset Analytics (CAAW). Miyakojima, Japan.
We curated a dataset from ~1 year of activity extracted from a ZKsync Era
archive node, made freely available to the research community. The paper details its creation, showcases
example analyses, and discusses future research directions for Layer-2 data-driven research.
2024
Liquid Staking Tokens in Automated Market Makers
Mathematical Research for Blockchain Economy (MARBLE). Malaga, Spain.
A theoretical and empirical study of LSTs on AMMs. While trading fees often
compensate for impermanent loss, fully staking is more profitable in many pools — raising questions
about the sustainability of current LST liquidity allocation to AMMs.
2024
Quantifying Arbitrage in Automated Market Makers: An Empirical Study of Ethereum ZK
Rollups
Mathematical Research for Blockchain Economy (MARBLE). Malaga, Spain.
We introduce a theoretical framework for Maximal Arbitrage Value (MAV) and
conduct an empirical study of arbitrage between SyncSwap (zkSync Era) and Binance. Total MAV from
July–September 2023 in the USDC-ETH pool: $104.96K (0.24% of trading volume).
2023
Dissecting Bitcoin and Ethereum Transactions: On the Lack of Transaction Contention
and Prioritization Transparency in Blockchains
Financial Cryptography and Data Security (FC). Bol, Brač, Croatia.
We characterize the lack of contention and prioritization transparency in
Bitcoin and Ethereum from private relay networks, showing private transactions are prevalent,
facilitating miner collusion and overcharging users — with critical implications for blockchain
stability.
2021
Selfish & Opaque Transaction Ordering in the Bitcoin Blockchain: The Case for
Chain Neutrality
ACM SIGCOMM Internet Measurement Conference (IMC). Virtual Event.
We audit the Bitcoin blockchain and present statistically significant evidence
of mining pools deviating from fee-per-byte norms to accelerate selfish transactions or those with
dark-fee payments — calling for urgent discussion on neutrality norms in blockchain transaction
ordering.
2021
Modeling Coordinated vs. P2P Mining: An Analysis of Inefficiency and Inequality in
Proof-of-Work Blockchains
ArXiv. 2021.
We study efficiency in proof-of-work blockchains with non-zero latencies,
proposing a model for both P2P and coordinated mining pool settings. We derive closed-form expressions
for efficiency and show that under a natural consistency condition, overall system efficiency in P2P is
higher than in coordinated settings.
2020
On Blockchain Commit Times: An analysis of how miners choose Bitcoin transactions
2nd International KDD Workshop on Smart Data for Blockchain and Distributed Ledger
(SDBD). August 2020.
In a month-long investigation of Bitcoin we reveal that congestion is typical
and commit times exhibit significant variance. Although fee-per-byte is the widely accepted "norm," we
show that miners significantly delay a fraction of transactions — deviations that undermine the utility
of blockchains for fair ordering.
2019
(Mis)Information Dissemination in WhatsApp: Gathering, Analyzing and
Countermeasures
The Web Conference (WWW). San Francisco, USA.
A large-scale analysis of misinformation dissemination in WhatsApp public
political groups during the 2018 Brazilian elections — identifying key sources of fake images,
propagation patterns across groups, and network structures that enable misinformation spread.
2019
On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns
on Facebook
ACM Conference on Fairness, Accountability, and Transparency (FAccT). Atlanta, USA.
We examine Russian IRA ad campaigns prior to the 2016 U.S. elections, showing
how Facebook's advertising infrastructure enabled efficient targeting of divisive political content at
vulnerable sub-populations — and calling for greater transparency in political ad targeting.
2017
Quantifying Search Bias: Investigating Sources of Bias for Political Searches in
Social Media
ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW).
Portland, USA.
We make the first attempt to quantify and explore demographic biases in
crowdsourced recommendations — finding that very different topics are popular among different
demographic groups and that there is a systematic bias toward particular demographics in trending topic
selection.
2019
WhatsApp Monitor: A Fact-Checking System for WhatsApp
13th International AAAI Conference on Web and Social Media (ICWSM). Munich,
Germany.
A web-based system that helps researchers and journalists explore content
shared on WhatsApp public groups in Brazil and India. The tool monitors images, videos, audio, and text,
displaying most-shared content per day. It was used to monitor content during the 2018 Brazilian general
election and was a major source for estimating misinformation spread.
2019
Search Bias Quantification: Investigating Political Bias in Social Media and Web
Search
Information Retrieval Journal. Springer. Volume 22, Issue 1–2. April 2019.
We propose a generalizable search bias quantification framework that measures
political bias in ranked search results and decouples bias from input data versus the ranking system.
Applied to 2016 U.S. Presidential primaries on Twitter, we find both input data and ranking system shape
final search output bias.
2017
White, Man, and Highly Followed: Gender and Race Inequalities in Twitter
IEEE/WIC/ACM International Conference on Web Intelligence (WI). Leipzig, Germany.
Using Face++ image processing algorithms to identify gender and race of U.S.
Twitter users, we show that users identified as White and male tend to attain higher positions in terms
of follower count — demonstrating that social media perpetuates offline demographic inequalities.
2017
Demographics of News Sharing in the U.S. Twittersphere
28th ACM Conference on Hypertext and Social Media (HT). Prague, Czech Republic.
The first in-depth characterization of news spreaders in social media. Males
and white users tend to be more active in sharing news, biasing the news audience toward the interests
of these demographic groups — with implications for personalized news digests.
2017
Linguistic Diversities of Demographic Groups in Twitter
28th ACM Conference on Hypertext and Social Media (HT). Prague, Czech Republic.
We characterize language usage across demographic groups in Twitter, extracting
linguistic features from 6 categories. Clear differences emerge in writing styles and topics of interest
across both gender and race lines among U.S. Twitter users.
2017
Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations
International AAAI Conference on Web and Social Media (ICWSM). Montreal, Canada.
The first attempt to quantify demographic biases in Twitter's crowdsourced
trending topics. A large fraction of trends are promoted by crowds whose demographics differ
significantly from the overall Twitter population, with certain groups systematically under-represented.
2017
Managing Longitudinal Exposure of Socially Shared Data on the Twitter Social Media
International Journal of Advances in Engineering Sciences and Applied Mathematics.
Springer, 2017.
A large-scale measurement study showing that more than 28% of 6-year old public
tweets are no longer accessible today. Even when users delete data, current mechanisms leave traces of
residual activity — and we show that significant information can be recovered from this residual data.
2017
An Evaluation of Sentiment Analysis for Mobile Devices
Springer Nature Social Network Analysis and Mining. Volume 7, Issue 1. 2017.
The first study comparing 14 sentence-level sentiment analysis methods adapted
for Android OS, measuring memory, CPU, and battery consumption. We identify methods that run efficiently
on mobile devices as well as those that cannot be deployed due to excessive memory use.
2017
Longitudinal Privacy Management in Social Media: The Need for Better Controls
IEEE Internet Computing (Special Issue on Usable Privacy & Security). Volume
21, Issue 3. 2017.
A large-scale measurement study of how Twitter users control longitudinal
exposure of their public tweets. Users face two fundamental problems: residual activity traces persist
even after deletion, and withdrawal mechanisms attract undesirable attention to deleted content.
2016
From Migration Corridors to Clusters: The Value of Google+ Data for Migration
Studies
IEEE/ACM International Conference on Advances in Social Networks Analysis and
Mining (ASONAM). San Francisco, USA.
Using "places lived" data from millions of Google+ users, we study migration
clusters — groups of countries individuals have lived in — going beyond bilateral flow models. Migration
clusters of country triads cannot be identified using bilateral flow data alone.
2016
Towards Sentiment Analysis for Mobile Devices
IEEE/ACM International Conference on Advances in Social Networks Analysis and
Mining (ASONAM). San Francisco, USA.
A comparative study of 17 sentence-level sentiment analysis methods adapted for
Android OS, measuring performance in terms of memory usage, CPU usage, and battery consumption —
providing a practical guide for developers building mobile NLP applications.
2016
Forgetting in Social Media: Understanding and Controlling Longitudinal Exposure of
Socially Shared Data
12th Symposium on Usable Privacy and Security (SOUPS). Denver, CO, USA.
More than 28% of 6-year-old public tweets on Twitter are no longer accessible
today. Even after deletion, residual activity traces remain — allowing significant recovery of deleted
content. We propose an exposure control mechanism that eliminates information leakage via residual
activities.
2013
You followed my bot! Transforming robots into influential users in Twitter
First Monday. Volume 18, Issue 7. July 2013.
Using Twitter bot accounts that interact with real users, we show it is
possible to become influential in systems like Klout and Twitalyzer through very simple strategies —
suggesting these influence measurement systems should be revised to avoid rewarding automatic activity.
Brazilian Venues
2025
Indo além da primeira camada: Modelagem e Avaliação de Desempenho de ZK-Rollups
na plataforma Ethereum
43rd Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC).
Natal, Brazil.
Proposta baseada em Redes de Petri Estocásticas para avaliar a viabilidade
dos ZK-Rollups no Ethereum, analisando vazão e latência. Maior adoção de transações na Layer-2 pode
aumentar a vazão do sistema em até 20%, enquanto a latência pode sofrer aumento superior a 100% com o
uso de batches maiores.
2018
A System for Monitoring Public Political Groups in WhatsApp
24th Brazilian Symposium on Multimedia and the Web (Webmedia). Salvador, Brazil.
A system for gathering, analyzing, and visualizing public WhatsApp groups in
Brazil. We provide a characterization of content shared in 127 Brazilian groups during the 2018
elections, helping journalists and researchers understand the repercussion of electoral events in
these groups.
2015
Brazil Around the World: Characterizing and Detecting Brazilian Emigrants Using
Google+
21st Brazilian Symposium on Multimedia and the Web (WebMedia). Manaus, Brazil.
Using Google+ data and SVM machine learning, we investigate which features of
Brazilian users are relevant to classify them as possible emigrants. Network features — reciprocity,
PageRank, in-degree, clustering coefficient, and ratio of incoming foreigners — showed the greatest
discriminative capacity.
2015
Algoritmos de Aprendizado de Máquina para Predição de Resultados das Lutas de MMA
30th Brazilian Symposium on Databases (SBBD). Petrópolis, Brazil.
Using machine learning algorithms to predict MMA fight outcomes based on
fighter characteristics and recent opponents, achieving 67% successful predictions — along with an
approach for creating datasets applicable to individual sports.
2015
Bazinga! Caracterizando e Detectando Sarcasmo e Ironia no Twitter
Brazilian Workshop on Social Network Analysis and Mining (BraSNAM). Recife,
Brazil.
Using automatically collected Twitter data tagged with #sarcasm and #irony,
we propose approaches for characterizing and detecting sarcasm and irony, achieving satisfactory
accuracy and Macro-F1 — with applications to sentiment analysis, text summarization, and review
ranking systems.
2015
Bots Sociais: Como robôs podem se tornar pessoas influentes no Twitter?
Revista Eletrônica de Sistemas de Informação (RESI). v. 14, n. 2, 2015.
2012
Sigam-me os bons! Transformando robôs em pessoas influentes no Twitter
Brazilian Workshop on Social Network Analysis and Mining (BraSNAM). Curitiba,
Brazil.
Experiments with simple Twitter bots on Klout and Twitalyzer show it is
possible to become influential through minimal strategies — suggesting that these influence ranking
systems do not have ideal metrics and are vulnerable to manipulation.
Theses & Technical Reports
2023
On Fairness Concerns in the Blockchain Ecosystem
Ph.D. Thesis. Max Planck Institute for Software Systems (MPI-SWS) & Saarland
University (UdS). 2023.
An audit of the Bitcoin and Ethereum blockchains to investigate norms
followed by miners in transaction prioritization, and an audit of decentralized governance protocols
(e.g., Compound) to evaluate whether voting power is fairly distributed. Findings have significant
implications for future developments of blockchains and decentralized applications.
2017
Characterizing Interconnections And Linguistic Patterns In Twitter
Master Thesis. Computer Science Department. Universidade Federal de Minas Gerais
(UFMG). 2017.
An investigation of gender and race inequalities in Twitter using Face++
image processing. White and male users attain higher positions in follower counts. Clear differences
emerge in writing styles across demographic groups in both gender and race domains, and in topics of
interest.
2014
Framework para Sistemas de Navegação de Veículos Aéreos não Tripulados
Bachelor Thesis. Computer Science Department. Universidade Federal de Ouro Preto
(UFOP). 2014.
A framework for autonomous flights on the AR.Drone 2.0 using Node.js, Arduino
sensors, and a remote control — enabling the user to create and execute custom autonomous flight
missions, verified through experiments on the physical drone.
For a complete list, see Google Scholar or DBLP.
Selected Talks
Presentations
2025
TUM Blockchain & Cybersecurity Salon · Munich, Germany
2025
TUM Blockchain Conference · Munich, Germany
2025
Ethereum Zürich · Zürich, Switzerland
2024
New York City, USA
2024
Fairness Concerns in the Blockchain Ecosystem
Indo-German Frontiers of Engineering (INDOGFOE) · Mumbai, India
2021
ACM IMC 2021 · Virtual Event
Teaching
Instruction
2026
Guest Lecture · Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU) ·
Kaiserslautern, Germany · January 14, 2026
2025
Guest Lecture · Universidade Federal do Piauí (UFPI) · Brazil · October 16, 2025
2023
Seminar · Universität des Saarlandes (UdS) · Saarbrücken, Germany · Summer Semester 2023
★
Busy Beaver Nominee
Press Coverage
Media
New York Times
I Flirt and Tweet. Follow Me at #Socialbot
MIT Tech Review
Twitter's Glass Ceiling Revealed for Women and Minority Races
Folha de S.P.
Robô Social
Awards & Recognition
Honors
2026
Selected participant, IC3 Winter Retreat 2026 — Engelberg,
Switzerland
2025
Invited by the Alexander von Humboldt Foundation to represent
Germany at the Brazilian-German Frontiers of Science & Technology (BRAGFOST) Symposium
2025
Selected participant, IC3 Winter Retreat 2025 — Engelberg,
Switzerland
2024
Invited by the President of the Alexander von Humboldt Foundation
to represent Germany at the Indo-German Frontiers of Engineering (INDOGFOE) Symposium — Mumbai, India
2024
Best Paper Award — Liquid Staking Tokens in Automated Market
Makers, MARBLE 2024
2024
Ph.D. completed with Magna Cum Laude distinction
2024
Selected participant, IC3 Winter Retreat 2024 — Les Diablerets,
Switzerland
2023
Seminar on Blockchains & DeFi nominated for the Busy Beaver
Award for outstanding lectures, Saarland University
2022
CISPA Summer School on Trustworthy Artificial Intelligence — one of
~100 students selected worldwide
2019
Project recognized as Brazil's most innovative health software by
IT Forum 365, promoted by PwC and ITMidia