I'm a MITACS Fellow under Dr. Michael Kouritzin at the Department of Mathematical and Statistical Sciences, University of Alberta, Canada. I was Chief Scientist at Antler-backed Chainrisk Labs back in the old days where I was leading innovation in preventing economic exploits and attacks in decentralized markets. After that I joined Pantera Capital's Hedge Fund TanX as Lead Risk Simulations to help traders make better decisions on the floor.
News
November 2025
Talk at DeFi Security Summit, Buenos Aires, Argentina
Even small market search frictions can create monopoly power and enable insurance-driven attack vectors in DeFi. Will speak at DSS about how Diamond's Paradox and coverage markets introduce systemic risks, with Lido as a case study.
October 2025
Open-Sourced Attack Simulation Toolkit for Ethereum PoS
Released simulation framework demonstrating unattributable faults (UF) in Ethereum's Proof-of-Stake consensus, attacks where everyone loses stake but no one can be blamed. The toolkit proves why traditional insurance mechanisms catastrophically fail under perfectly correlated losses. Full cryptoeconomic models included.
August 2025
Why Consensus Insurance Markets Are a Disaster Waiting to Happen
Published analysis revealing how attackers can weaponize insurance policies to slash their attack costs to near-zero while maximizing system-wide damage. Introduced the kamikaze attack model and proved fundamental impossibility results for naive insurance designs. Special thanks to collaborators from Stanford, Columbia, University of Toronto, and Othentic for their insights.
Experience
MITACS Fellow — University of Alberta
Advisor: Dr. Michael Kouritzin
Research in Mathematical Statistics for Financial Markets and Education Parameter Estimation under Dr. Michael Kouritzin at the Department of Mathematical and Statistical Sciences.
Risk Management Lead — Pantera Capital's TanX, YODL Exchange
Led risk simulation strategies for Pantera Capital's Hedge Fund TanX and devised CoW order routing algorithm for Dextr (now YODL) Exchange, helping traders make better decisions on the floor.
Chief Scientist — Chainrisk Labs
Led innovation in preventing economic exploits and attacks in decentralized markets at this Antler-backed startup. Developed governance attack prediction on Compound Finance using Multi-Agent Influence Diagrams (presented at ETH Tokyo & Coinfest Bali).
Protocol Economist — HyperspaceAI
Worked on incentive design on EigenLayer and optimal transaction dissemination protocols at this supercomputing L1 turned Distributed AI company.
Junior Data Scientist — Nethermind
Got cited in the Ethereum Yellow Paper (EIP-5133) for accurately predicting ETH's difficulty bomb delay. Conducted stress tests for TwinStake and MEV modeling with MEV-Boost.
Education
University of Alberta
BSc. in Statistics
Advisor: Prof. Arno Berger and Prof. Michael Kouritzin
Duke University
COMPSCI 584: Foundations of Blockchains
Advisor: Invited by Prof Kartik Nayak to audit the course as a guest professional student
Publications
New Preprint 2025
A Coincidence of Wants Mechanism for Swap Trade Execution in Decentralized Exchanges
Abhimanyu Nag, Madhur Prabhakar, Tanuj Behl
We propose a mathematically rigorous framework for identifying and completing Coincidence of Wants (CoW) cycles in decentralized exchange (DEX) aggregators. Unlike existing auction based systems such as CoWSwap, our approach introduces an asset matrix formulation that not only verifies feasibility using oracle prices and formal conservation laws but also completes partial CoW cycles of swap orders that are discovered using graph traversal and are settled using imbalance correction. We define bridging orders and show that the resulting execution is slippage free and capital preserving for LPs. Applied to real world Arbitrum swap data, our algorithm demonstrates efficient discovery of CoW cycles and supports the insertion of synthetic orders for atomic cycle closure. This work can be thought of as the detailing of a potential delta-neutral strategy by liquidity providing market makers: a structured CoW cycle execution.
Mathematical Research in Blockchain Economy (MARBLE) 2025
Seminal work in multiple restaking security protocols
Economic Security of Multiple Shared Security Protocols
Abhimanyu Nag, Dhruv Bodani, Abhishek Kumar
As restaking protocols gain adoption across blockchain ecosystems, there is a need for Actively Validated Services (AVSs) to span multiple Shared Security Providers (SSPs). This leads to stake fragmentation which introduces new complications where an adversary may compromise an AVS by targeting its weakest SSP. In this paper, we formalize the Multiple SSP Problem and analyze two architectures : an isolated fragmented model called Model M and a shared unified model called Model S, through a convex optimization and game-theoretic lens. We derive utility bounds, attack cost conditions, and market equilibrium that describes protocol security for both models. Our results show that while Model M offers deployment flexibility, it inherits lowest-cost attack vulnerabilities, whereas Model S achieves tighter security guarantees through single validator sets and aggregated slashing logic. We conclude with future directions of work including an incentive-compatible stake rebalancing allocation in restaking ecosystems.
Accepted to AI in Finance workshop, European Conference on Artificial Intelligence (ECAI) 2025
Multi Agent Influence Diagrams for DeFi Governance
Abhimanyu Nag, Samrat Gupta, Sudipan Sinha, Arka Datta
Decentralized Finance (DeFi) governance models have become increasingly complex due to the involvement of numerous independent agents, each with their own incentives and strategies. To effectively analyze these systems, we propose using Multi Agent Influence Diagrams (MAIDs) as a powerful tool for modeling and studying the strategic interactions within DeFi governance. MAIDs allow for a comprehensive representation of the decision-making processes of various agents, capturing the influence of their actions on one another and on the overall governance outcomes. In this paper, we study a simple governance game that approximates real governance protocols and compute the Nash equilibria using MAIDs. We further outline the structure of a MAID in MakerDAO.
Ethereum Yellow Paper 2022
Cited in Ethereum Yellow Paper
Ethereum Improvement Proposal 5133
Tomasz Stanczak, Eric Marti Haynes, Josh Klopfenstein, Abhimanyu Nag
Accurately predicted ETH's difficulty bomb delay, cited in the Ethereum Yellow Paper.
Portfolio
EIP-5133 Ethereum Difficulty Bomb Prediction
Code to predict block time after difficulty bomb was set off. This work was cited in the Ethereum Yellow Paper (EIP-5133) for accurately predicting ETH's difficulty bomb delay.
Attack Insurance Protocol Simulation
Simulation toolkit for analyzing unattributable faults (UF) in Ethereum PoS consensus and why naive insurance markets fail. Advanced security analysis for proof-of-stake protocols.
Healthcare Insurance Fraud Detection Using Markov Models
Undergraduate thesis (STAT-499) on predicting healthcare insurance fraud using Markov Observation Models. ScotiaBank-funded research project with Dr. Mike Kouritzin.
Statistical Models of Trading Strategies
A collection of statistical models for various trading strategies. Quantitative analysis frameworks for financial markets.
Citadel APAC 2022 Data Open Competition
Competition work for The Spring 2022 APAC Data Open conducted by Citadel and Correlation One.