Robert Henker
Researcher and Technology Manager focused on data-driven and automated decision systems and their role in the digital transformation of organizations.
Combining applied research with implementation experience in algorithmic automation & AI, data analytics, digital infrastructures and decentralized systems.
This website provides an overview of my research, projects and publications.
Check out the latest update of the XAI Agentic Analytics & Smart Procurement platform for carbon credits QAVCM: www.voluntarycarbon.org
Biography & Appointments
Connecting academics & deep tech
Robert Henker is a doctoral researcher at the University of Potsdam, co-founder of the research spin-off German Deep Tech Quantum and Advisor with XU Exponential University.
His work centers around data-driven analytics and algorithmic automation. As co-founder and CEO he built German Quantum, a low-latency analytics and algorithmic execution SaaS platform licensed by banks and exchanges. He initiated and led several research and industry–academia collaboration projects. Recent projects include QAVCM, a quantitative analytics & explainable AI (XAI) platform for the voluntary carbon market, RITS, a resilient technology suite for critical infrastructure in the federal state of Brandenburg and ImmoToken, a technology suite for the tokenization of real-world assets.
He holds a Diploma in Business Informatics, is a Certified Portfolio Manager (EBS University) and earned his MBA from ESCP Europe Paris. Currently he pursues a PhD in Computer Science at the Digital Engineering Faculty of the University of Potsdam.
Core Domains
Portfolio
Selected Projects
I initiated and co-initiated several industry–academia collaboration projects and transfer ventures. Recent projects include:
Selected Research
Recent Publications & Working Papers
Peer-reviewed research papers and academic contributions exploring data analytics, explainable AI, smart execution algorithms and decentralised physical infrastructures.
Hermes: An Autonomous Algorithmic Trading Agent for Cross-Exchange Spot Markets
R. Henker, D. Atzberger, J. O. Vollmer, W. Scheibel, J. Döllner
Capturing price discrepancies across different venues requires continuous market monitoring of massive data, automated decision making and low‐latency execution. In this work we present Hermes, an autonomous algorithmic trading agent built on a low‐latency execution infrastructure. It integrates a rule‐based decision cycle, low‐latency order execution and automated asset rebalancing within a continuous feedback loop. Thereby, Hermes evaluates and sizes trades based on depth, fees, profit targets, and constraints, automatically rebalancing assets and reassessing opportunities before further execution, enabling repeated exploitation of opportunities with significant volume without human intervention. The agent was deployed in a real‐world professional environment, executing more than 400,000 transactions.
Manuscript in preparation following an invitation to submit to the International Journal of Network Management (IJNM), Wiley.
QAVCM: A Quantitative Aggregation and Analytics Platform for the Fragmented Voluntary Carbon Market
R. Henker, R. Bin Tareaf, A. Holdschick, D. Puttyah, A. Sohotoo, B. Halecker
The integrated analytics and execution platform harmonises certificate data drawn from over 1.2 billion data points spanning 11,599 projects, representing 1,093,056,213 tCO₂e of tradable credits and 2,944,950,676 t/year of reduction capacity. Machine learning estimates fair values and explainable AI using SHAP makes model outputs inspectable. A smart order routing layer compares connected venues and splits orders to minimise execution costs.
Accepted for presentation at the 39th Annual Conference of the Working Group on Information Systems at Universities of Applied Sciences (AKWI) 2026, Berlin. Proceedings forthcoming.
Algorithmic Entrepreneurship: Evidence on Data-Driven Algorithmic Automation and Output-to-Employee Scaling in a Digital Asset Market Infrastructure Venture
R. Henker, B. Halecker
This study examines how Data-Driven Algorithmic Automation shapes Output-to-Employee Ratios and scalability in a Digital Asset Market Infrastructure Venture. It benchmarks publicly disclosed and blockchain-based data from large-scale algorithmic infrastructures (Tether, Sky Protocol, Hyperliquid) against an empirical analysis of a SaaS venture's client transactions, volumes, fees and staffing levels from 2021 to 2024, finding that Output-to-Employee ratios increased disproportionately over time. By emphasizing operational throughput over revenue-based metrics, the study contributes to debates in Automation Economics, Data-Driven Business Models and Labor Productivity.
TH Wildau Engineering and Natural Sciences Proceedings, 3 (2026). Wildauer Konferenz für Künstliche Intelligenz 2026 (WiKKI26)
DePIN for Enhancing the Resilience of EWF Infrastructures: Systematization and Potential for the Federal State of Brandenburg
B. Halecker, R. Henker
Critical infrastructures in the areas of energy, water and food (EWF) require new resilience concepts in the face of increasing global challenges. This article examines how decentralised physical infrastructure networks (DePIN) can contribute to increasing the resilience of EWF systems by combining blockchain, the Internet of Things and artificial intelligence, focusing on the Brandenburg region. The results show that DePIN approaches reduce single points of failure and enable a faster, autonomous response to disruptions, thereby sustainably improving regional security of supply.
TH Wildau Engineering and Natural Sciences Proceedings, 2. Wildauer Konferenz für Künstliche Intelligenz 2025 (WiKKI25)
Towards Infrastructure Digital Twins as Innovation Enablers in Rural Energy Systems: Early Developments for Renewable Transitions in Brandenburg
B. lemhényi Hankó, B. Hagedorn, C. Bachert, R. Henker, B. Halecker
Rural energy systems are central to renewable energy transitions but face persistent innovation challenges related to spatial dispersion, fragmented infrastructure ownership, and limited coordination capacity among actors. While rural regions often host substantial renewable generation potential, early-stage infrastructure innovation is constrained by heterogeneous data sources and a lack of shared situational awareness. This Research-in-Progress paper presents early developments from the Resilient Infrastructure Technology Suite (RITS) project in Brandenburg, examining how Infrastructure Digital Twins (IDTs) may function as innovation enablers in rural energy systems. The IDT is developed as a modular, GIS-based analytical and visualisation prototype supported by AI-assisted exploratory analytics.
TH Wildau Engineering and Natural Sciences Proceedings, 2 (2025). Wildauer Konferenz für Künstliche Intelligenz 2025 (WiKKI25)
Athena: Smart Order Routing on Centralized Crypto Exchanges Using a Unified Order Book
R. Henker, D. Atzberger, J. O. Vollmer, W. Scheibel, J. Döllner, M. Bick
In liquid markets based on order books, the price achieved for buying and selling deviates only slightly from the assumed reference price, meaning trading is associated with low implicit costs. This paper describes the design and implementation of Athena, a smart order routing algorithmic system that automatically splits orders across multiple exchanges to minimize implicit costs, collecting and merging order books from several centralized crypto exchanges into an internal unified order book.
International Journal of Network Management, 34(4), e2266
Conferences, Panels & Lectures
Regular presenter and moderator at international computer science conferences, innovation and venture summits. Active in academic teaching as guest lecturer and invited expert at several universities .
Initiate collaboration or research inquiries
Open to academia-industry partnerships and speaker invitations.