Adrianna Janik
LinkedInSenior AI Researcher · Executive MBA · Knowledge Graphs & Explainable AI
Senior AI Researcher at Accenture Labs (50% client‑facing) and Executive MBA from Trinity College Dublin — Ireland’s top business school. With 10+ years bridging industry and academia, I lead teams driving revenue and cost savings by de‑risking AI through knowledge graph explainability, IP‑driven sales, and lab optimisation. Background: B.E. Control Engineering, double M.S. Data Science (EIT Digital).
Publications • Experience • Education • Certifications • Volunteering • Talks
Areas of Expertise
Selected Projects
Customer Segmentation
Knowledge graph embeddings for segmenting customers, enabling targeted persona-based marketing campaigns.
Lung Cancer Recurrence
GraphML‑based prediction of early‑stage lung cancer relapse (CLARIFY consortium). Published at JCO CCI and others.
Regulatory Compliance
Rule‑based and knowledge graph system for compliance, benchmarked against pure agentic AI.
Gene-Disease-Associations
Biomedical knowledge graphs for detecting novel gene-disease associations, collaboration with geneticists.
Semantic Data Hub
Designing Knowledge Graph roll-out blueprint for a large enterprise.
Knowledge Graphs Workshops
Designing and running a series of workshop about knowledge graphs for a commercial client.
Selected Publications
Certifications & Professional Development
AI Leadership & Strategy
Reinvention with Agentic AI
Accenture Mar 2026Forward Program
McKinsey & Company Dec 2025Bloomberg Market Concepts
Bloomberg for Education Dec 2023Technical Expertise
Databricks Certified ML Associate
Databricks Jan 2025GraphDB Knowledge Graph Developer
Graphwise Jan 2026Knowledge Graph Builder Certificate
Bricks to Building KGs
The Knowledge Graph Conference Aug 2025Ontology and Taxonomy Modeling
The Knowledge Graph Conference Aug 2025Building KGs from Structured and Unstructured Data
The Knowledge Graph Conference Sep 2025Build Something Real
The Knowledge Graph Conference Sep 2025Professional Experience
Associate Innovation Manager
Designing and delivering hybrid search system for an automotive client's knowledge graph platform. Leading a series of 3 workshops for a Life Sciences client on knowledge graphs. Delivering knowledge graph-based regulatory compliance solution for a Life Science client replacing 23 FTEs with a hybrid agentic architecture. Co-leading Special Interest Group on Knowledge Graphs and LLMs in global Accenture Labs. Preparing Digital Twin for CHO-cells with optimization support. Managing hundreds of experiments with MLOps for predicting and evaluating gene disease association. Designing architecture for orchestration of LLMs. RAG with vector databases, contributing to open-source AmpliGraph GraphML library. Fluent in AI toolkit landscape: Langchain, GPT-3, GPT-4, Ollama, DeepSeek, etc.
Technology Research Specialist
Led CLARIFY project to Accenture's Greater than Award Finals in Inspiring Growth category. Managed tech transfer of internal demo, leading R&D stages for neuro-symbolic query answering system on biomedical knowledge graphs. Led development of tabular and graph-based systems, including explanations and inductive capabilities, for relapse prediction tool REST API. Completed TechStar 2023 leadership program. Developed prototype with REST API for open-source library AmpliGraph 2 reasoning functionality. Contributed to EU Commission's CLARIFY H2020 project, including delivering one client pilot, interacting with 11 partners, and authoring deliverables. Proposed 4 patent application ideas filed with patent office, 2 as lead author. Co-supervised PhD intern on interpretable Gene-Disease Prediction with GraphML. Presented at Sketching in Hardware 2022 Conference, ESSEC Business School, EIT Digital Alumni Annual Meeting. Hosted and co-presented COLING-22 Tutorial on Knowledge Graph Embeddings for NLP.
Technology Research Analyst
Conducted machine learning research on graph-based knowledge discovery tasks, focusing on explainable AI for knowledge graph embedding models in precision medicine applications in oncology. Developed ExamplE, novel post-hoc example-based explanation approach for link prediction resulting in patent application. Led Proof of Concept deployed at Hospital Puerta del Hierro for CLARIFY H2020 project, designing and implementing explanation subsystem for lung cancer relapse decision support system. Designed and conducted experiments for relapse prediction in lung cancer patients. Contributed to open-source AmpliGraph 1.4 development. Co-authored three deliverables to EU Commission, submitted three patent ideas, deployed internal tools. Contributed to consumer goods project by leading human-based evaluation protocol with 41 marketing professionals. Achieved runner-up position in Accenture Hackathon: AI4Insurance Industry Data + AI.
Strategic Consultant
Innovation strategy for Ireland's critical infrastructure provider. Developed strategic recommendations for digital transformation and technology adoption. Analyzed market trends and industry landscape for innovation best practices among international peers. Conducting interviews, applying frameworks (SWOT, BMC, PESTEL, VRIO, Ansoff's Matrix, Porter's Five Forces, etc...)
Doctoral Researcher & Teaching Assistant
Teaching assistant for Advanced Machine Learning (Master's level). Developed course materials and supported students in software development and data visualisation.
Visiting Researcher
Humanitarian AI for disaster mapping: computer vision and interpretability for satellite imagery. Built interactive demos (U‑Net Vis, Concept Vis) and published at EuroVis 2019.
R&D Embedded Software Engineer
Developed time synchronisation software for base stations; built web‑based log analysis tool with machine learning in Python. C++14/17, unit testing, and documentation.
Data Scientist (freelance) · Robotics Intern · R&D Intern
Freelance project on temporal expressions detection (CLARIN-PL). Robotics intern developing applications for Epson SCARA arms. Early R&D experience in embedded software.
Education
Executive MBA
Strategy, Innovation, Finance, Leadership.
M.Sc. in Data Science (double degree)
Specialisation: Distributed Systems & Big Data. Thesis on interpretability for semantic segmentation (remote sensing). Worked at Inria on deep learning for reading‑chart generation.
B.E. in Control Engineering and Robotics
Thesis on travel time prediction using neural networks (published as Springer book chapter). Erasmus+ at Cork Institute of Technology.
Volunteering & Community
Wappy
Volunteer as a Subject Matter Expert on Technology for designing mobile apps to support NGO projects for youth.
ODSC
Open Data Science Conference – community support. Serving as a Master of Ceremony during selected talks.
EVS
European Voluntary Service – sustainability projects. Supporting local NGOs in their initiatives.
Talks & Tutorials
Knowledge Graph Tutorial @ ECAI 2020
Explainable AI for Graphs