# Arghya Mukherjee, PhD

> Arghya Mukherjee, PhD: Tulsa-based data scientist and AI engineer building VLMs, agentic AI, MCP servers, and fraud detection. Founder of ChainDiligence.

Website: https://arghyam.me. Last updated: 2026-10-26.
Role: Senior Data Scientist, AI Engineer & Founder of ChainDiligence. Location: Tulsa, Oklahoma. Email: arghyamukherjee1991@gmail.com.
Open to roles: Principal Data Scientist, Forward Deployed Engineer (FDE), Security Research.

## About
I’m a data scientist and AI engineer who builds systems that turn messy data into decisions. My work spans vision-language models, generative and agentic AI, fraud detection, ontology development, and MCP servers that connect language models to real tools and data.

As a Senior Data Scientist for the State of Oklahoma, I deliver machine learning and AI across state agencies. I also founded ChainDiligence, a blockchain intelligence company that turns my cryptocurrency crime research into products for screening, monitoring, and investigations.

I earned my PhD in Computer Science from the University of Tulsa in December 2025. My research measures scams, market manipulation, and security shocks in cryptocurrency ecosystems, and has been covered by Bloomberg and Bruce Schneier.

### Focus areas
- **Generative & agentic AI**: LLM applications, retrieval-augmented generation, multi-step agents, and MCP servers that give models safe access to tools and data.
- **Vision & multimodal models**: Vision-language models and deep learning for images and video, from training and evaluation to production deployment.
- **Fraud detection, anti-abuse & AML**: Models and data products that surface pump-and-dump schemes, scams, and illicit fund flows in financial and blockchain data.
- **Ontologies & data platforms**: Ontology and knowledge modeling, data pipelines, and analytics that let teams across an organization share one view of their data.

## Experience
### Founder, ChainDiligence
May 2026 – Present. Tulsa, OK. https://chaindiligence.com

- Founded a research-driven blockchain intelligence company that helps compliance, fraud, security, and investigation teams act on blockchain activity.
- Leading a suite of eight connected products in active development, covering wallet screening, transaction monitoring, fraud prevention, and crypto investigations.
- Turning peer-reviewed research on pump-and-dump schemes, exchange failure, and cryptocurrency scams into explainable risk signals.
- Designing risk scoring that shows its evidence: labels, fund-flow paths, confidence, and sources behind every decision.

Projects:
- **Address screening**: API that screens wallets for sanctions, scam, mixer, and darknet exposure, including indirect risk.
- **Transaction monitoring**: Continuous monitoring of deposits, withdrawals, and swaps with configurable alerts.
- **Investigation workspace**: Graph tool for following fund flows across hops and chains, saving case evidence, and exporting reports.
- **Market-integrity alerts**: Detection of token manipulation and abnormal trading, informed by pump-and-dump research.
- Tools: Blockchain analytics, Graph intelligence, Entity attribution, Risk scoring, APIs & webhooks

### Computer Vision Engineer, Chevron
Oct 2025 – Apr 2026. USA.

- Built a computer vision inspection system that detects damage to energy infrastructure from imagery.
- Replaced slow manual review with automated detection, so inspectors can focus on the assets that need attention.
- Took models from data collection and labeling through training, evaluation, and deployment into inspection workflows.
- Tools: Python, PyTorch, Computer vision, Deep learning, Object detection

### Data Scientist III, Office of Management and Enterprise Services, State of Oklahoma
Jan 2025 – Present. Oklahoma, USA.

- Design, build, and deploy machine learning and AI solutions for state agencies, from scoping with stakeholders to production and monitoring.
- Build vision-language models that interpret infrastructure imagery and answer questions about it in plain language.
- Led two generations of roadway asset detection, moving from a GIS-based first version to a computer vision system that cuts manual inspection time and cost.
- Built a custom image viewer so staff can review imagery and model detections side by side.
- Shape AI projects in digital twins and noise mitigation, from early design through delivery.

Projects:
- **Vision-language models**: Multimodal models that describe, classify, and answer questions about infrastructure imagery.
- **Digital twin design**: Project design for a digital twin that brings asset, imagery, and sensor data into one model of the network.
- **Noise mitigation AI**: Machine learning that helps assess and prioritize noise mitigation work.
- **Roadway assets v1**: First release built on ESRI, with dashboards to explore assets by county, road, and asset type.
- **Roadway assets v2**: Computer vision rebuild that detects and catalogs roadway assets directly from imagery.
- **Custom image viewer**: Purpose-built viewer for browsing imagery with detections overlaid, designed for reviewers.
- Tools: Python, PyTorch, VLMs, Computer vision, ESRI, Digital twins, Cloud ML

### Data Scientist, ML/AI Engineer, Workonward Inc
Apr 2024 – Dec 2024. Remote.

- Designed voice search and an AI chatbot that let customers reach key information hands-free, increasing user interaction by 200% within three months of launch.
- Designed and implemented the backend for ML features that score résumés against job descriptions.
- Built a custom recruiter and job-seeker chatbot on an LLM using retrieval-augmented generation.
- Worked with IT and DevOps to ensure quality assurance and data integrity.
- Tools: Python, LLMs, RAG, LangChain, Amazon Bedrock, NLP

### AI Software Engineer, Anti-Phishing Working Group
Apr 2024 – Present. Remote. https://apwg.org

- Develop ontologies that give APWG’s eCrime data a shared structure, linking scams, wallets, domains, and campaigns.
- Build MCP servers that let AI assistants query and reason over APWG data through controlled, auditable tools.
- Apply language models to classify, enrich, and connect incoming threat reports for fraud, anti-abuse, and AML use cases.

Projects:
- **eCrime ontology**: A common model of threat entities and their relationships across APWG datasets.
- **MCP servers**: Tool interfaces that connect AI agents to APWG data with access controls.
- Tools: Python, Ontologies, Knowledge graphs, MCP, LLMs, AWS

### Data Scientist, ML/AI Engineer, Robbie AI
May 2023 – Apr 2024. Remote.

- Developed computer vision models to identify body structures, and neural networks that detect pain level from FACS and PSPI scores.
- Raised accuracy of existing production models by at least 23%.
- Built a real-time video pipeline with Azure Blob Storage for live feeds and Apache Kafka streaming data to deep learning models.
- Tools: Python, Computer vision, Deep learning, Azure Blob Storage, Apache Kafka

### Software Engineer (DevOps), Anti-Phishing Working Group
Oct 2020 – Mar 2024. Remote. https://apwg.org

- Built and ran data services for APWG’s Cryptocurrency Working Group, used by members in academia, industry, and law enforcement-facing research.
- Maintained a curated database of roughly 1.2 million Bitcoin wallet addresses linked to scams and ransomware, used by members for fraud prevention, anti-abuse, and AML screening.
- Kept client-facing systems at 99.999% uptime through testing, monitoring, and CI/CD with Git, Jenkins, and Apache Airflow.

Projects:
- **Cryptocurrency scam address feed**: Collection, review, and enrichment of wallet addresses reported in scams and ransomware campaigns.
- **Member data APIs**: REST APIs that give working-group members programmatic access to eCrime data.
- **eCrime data lake**: Snowflake warehouse that turns raw reports into aggregated, query-ready datasets.
- **Workflow automation**: Scheduled ingestion and processing pipelines orchestrated with Airflow and deployed through CI/CD on AWS.
- Tools: Python, R, REST APIs, Snowflake, Elasticsearch, Apache Airflow, AWS, Jenkins

### Research Assistant & Data Scientist, The University of Tulsa
Jan 2018 – Dec 2024. Tulsa, OK.

- Built fraud detection research end to end: pump-and-dump schemes, scams, market manipulation, and the failure of coins and exchanges.
- Measured anti-abuse and anti-money-laundering signals in blockchain data, tracing how illicit funds move through exchanges and services.
- Developed ETL pipelines for Bitcoin, Ethereum, and Solana data with Python, Snowflake, and SQL, plus web crawlers and API clients for market and scam data.
- Combined econometric models with neural networks and NLP to detect manipulation and classify large volumes of text.
- Published peer-reviewed work at ACM CCS workshops, APWG eCrime, HICSS, and Information Processing and Management.

Projects:
- **Pump-and-dump detection**: Identifying coordinated manipulation campaigns and measuring their economic impact.
- **Exchange risk**: Survival analysis of why cryptocurrency exchanges close and what it costs their users.
- **Scam & fraud measurement**: Large-scale datasets of fraudulent projects, wallets, and campaigns for empirical study.
- **AML & anti-abuse**: Fund-flow analysis that links illicit activity to the services it passes through.
- Tools: Python, R, Stata, Snowflake, SQL, NLP, Web scraping, Statistics

### IT Risk Assurance Associate, PricewaterhouseCoopers
Jan 2015 – Dec 2016. Birmingham, UK.

- Delivered IT risk advisory work: risk assessments, security reviews, compliance assessments, and IT governance assessments.
- Evaluated client IT environments for risks and control gaps, and recommended remediation.
- Tools: Risk assessment, IT governance, Compliance, Security reviews

## Cybersecurity
Security has run through my career, from IT risk advisory at PwC to eCrime data at the Anti-Phishing Working Group, a PhD measuring cryptocurrency crime, and now building blockchain intelligence at ChainDiligence.

- **Cryptocurrency crime measurement**: Empirical studies of pump-and-dump schemes, scams, exchange closures, and the lifespan of coins, published at venues including ACM CCS workshops, APWG eCrime, and HICSS.
- **Blockchain intelligence & investigations**: Wallet screening, entity attribution, fund-flow tracing across chains, and explainable risk scoring for compliance and investigation teams.
- **Fraud, anti-abuse & AML**: Detection of pump-and-dump schemes, scams, and illicit fund flows across University of Tulsa research and APWG work, built on labeled data from research and industry feeds.
- **Phishing & eCrime data**: Collecting, enriching, and serving threat data on scam and ransomware wallets for APWG’s global membership.
- **Security economics**: Measuring the impact of breaches and security shocks on markets, and modeling how organizations should invest in security.
- **IT risk & governance**: Risk assessments, security reviews, compliance testing, and control-gap analysis for enterprise clients at PwC.

## Publications
233 citations on Google Scholar (h-index 4, i10-index 3): https://scholar.google.com/citations?user=wJBHR1QAAAAJ&hl=en
Citations per year: 2019: 9, 2020: 12, 2021: 23, 2022: 26, 2023: 40, 2024: 43, 2025: 33, 2026: 40.

- **Unicorns in the Wild West: Empirical Analysis of Cybercrime Facilitated by Cryptocurrencies**. Arghya Mukherjee, Tyler Moore. *APWG Symposium on Electronic Crime Research (eCrime)*, 2025. [Paper](https://ieeexplore.ieee.org/document/11327757/) · [PDF](https://tylermoore.utulsa.edu/ecrime25unicorn.pdf)
- **Beyond the Hype: Empirical Evaluation of Cryptocurrency Unicorn Success**. Arghya Mukherjee, Tyler Moore. *Hawaii International Conference on System Sciences (HICSS)*, 2025. [Paper](https://aisel.aisnet.org/hicss-58/os/blockchain/7/) · [PDF](https://tylermoore.utulsa.edu/hicss25.pdf) · [Audio summary](https://notebooklm.google.com/notebook/6d924345-92a2-4cc4-851b-53618e0c7eb5/audio)
- **Cryptocurrency Exchange Closure Revisited (Again)**. Arghya Mukherjee, Tyler Moore. *APWG Symposium on Electronic Crime Research (eCrime)*, 2022. [Paper](https://ieeexplore.ieee.org/abstract/document/10142141) · [PDF](https://tylermoore.utulsa.edu/ecrime22exchange.pdf)
- **An examination of the cryptocurrency pump-and-dump ecosystem**. JT Hamrick, Farhang Rouhi, Arghya Mukherjee, Amir Feder, Neil Gandal, Tyler Moore, Marie Vasek. *Information Processing and Management*, 2021. [Paper](https://www.sciencedirect.com/science/article/pii/S0306457321000169) · [PDF](https://tylermoore.utulsa.edu/ipm21.pdf) · [Audio summary](https://notebooklm.google.com/notebook/b715cb5d-b230-41bc-8747-b41cf90de67e/audio)
- **Analyzing Target-Based Cryptocurrency Pump and Dump Schemes**. JT Hamrick, Farhang Rouhi, Arghya Mukherjee, Amir Feder, Neil Gandal, Tyler Moore, Marie Vasek. *ACM CCS Workshop on Decentralized Finance and Security*, 2021. [Paper](https://dl.acm.org/doi/abs/10.1145/3464967.3488591)
- **The Economics of Cryptocurrency Pump and Dump Schemes**. JT Hamrick, Farhang Rouhi, Arghya Mukherjee, Amir Feder, Neil Gandal, Tyler Moore, Marie Vasek. *Workshop on the Economics of Information Security (WEIS)*, 2019. [PDF](https://weis2019.econinfosec.org/wp-content/uploads/sites/6/2019/05/WEIS_2019_paper_14.pdf)

Press coverage:
- [Bloomberg](https://www.bloomberg.com/news/articles/2018-12-19/crypto-market-rife-with-pump-and-dump-schemes-study-shows): Reported on our study of pump-and-dump schemes in cryptocurrency markets.
- [Schneier on Security](https://www.schneier.com/blog/archives/2020/06/cryptocurrency_.html): Security expert Bruce Schneier wrote about the same research on his blog.

## Presentations
- Nov 2025: "Unicorns in the Wild West: Empirical Analysis of Cybercrime Facilitated by Cryptocurrencies", APWG Symposium on Electronic Crime Research (eCrime 2025). [Paper](https://tylermoore.utulsa.edu/ecrime25unicorn.pdf)
- Jan 2025: "Beyond the Hype: Empirical Evaluation of Cryptocurrency Unicorn Success", Hawaii International Conference on System Sciences (HICSS-58). [Paper](https://tylermoore.utulsa.edu/hicss25.pdf)
- Nov 2022: "Cryptocurrency Exchange Closure Revisited (Again)", APWG Symposium on Electronic Crime Research (eCrime 2022). [Paper](https://tylermoore.utulsa.edu/ecrime22exchange.pdf)
- Jun 2019: "The Economics of Cryptocurrency Pump and Dump Schemes", Workshop on the Economics of Information Security (WEIS 2019). [Paper](https://weis2019.econinfosec.org/wp-content/uploads/sites/6/2019/05/WEIS_2019_paper_14.pdf)

## Writing
Essays on Substack: https://arghyam.substack.com

## Education
- **PhD, Computer Science**, The University of Tulsa, Tulsa, OK (2018 – Dec 2025). Control + Alt + Deceive: Empirical analysis of cryptocurrency ecosystem and cyber crime. Advisor: Dr. Tyler Moore.
- **MSc**, University of St Andrews, St Andrews, Scotland (2014). Measuring enterprise IEEE 802.11 (Wi-Fi) standards. Advisor: Dr. Colin Allison.
- **Bachelor of Computer Applications**, West Bengal University of Technology, Kolkata, India (2012). Computer applications and information technology.

## Skills
- **AI & machine learning**: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, Vision-language models, OpenCV
- **Generative & agentic AI**: LLMs, RAG, AI agents, MCP servers, LangChain, Amazon Bedrock, Fine-tuning
- **Knowledge & data modeling**: Ontology development, Knowledge graphs, Data modeling, SQL, GraphQL
- **Data & analytics**: Python, R, Pandas, PySpark, Stata, Power BI, Tableau, ESRI
- **Cloud & MLOps**: AWS, Azure, Google Cloud, Docker, Kubernetes, Apache Airflow, Snowflake, CI/CD
- **Security & blockchain**: Blockchain analysis, Fraud detection, AML, Anti-abuse, Threat intelligence, SIEM, Elasticsearch, IT risk assessment

## Contact
- Email: arghyamukherjee1991@gmail.com
- Book a call: https://calendar.app.google/Ee57QkDYqHeSt3b48
- LinkedIn: https://www.linkedin.com/in/arghyamukherjee/
- GitHub: https://github.com/amukherjee1991/
- CV (PDF): https://arghyam.me/resume/ArghyaMukherjee_Resume_DS_Nov4_24.pdf