Martin Dlask, Ph.D.

Martin Dlask, Ph.D.

Principal AI Engineer with experience in pharma, finance and gaming. Expert in the field of deep learning, recommender systems, reinforcement learning and data science.

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Professional experience

I’ve been always changing Data Science and AI Engineering roles like socks. Almost like I couldn’t decide which one fits better.

I have 10+ years of experience developing AI/ML models and systems at scale across pharmaceutical, finance, and gaming industries. I also spent 2 years as an engineering manager leading a small team. I’ve published 10+ papers in statistics, computer science, and machine learning (h-index 6) and occasionally speak at major conferences on algorithms and technologies driving business impact.

Deep LearningReinforcement LearningRecommender systemsSelf-supervised LearningGenAIAI agents

Technical areas of expertise

Quite bold to call myself “expert”, right? Especially when anyone with ChatGPT can become an “expert”.

My main expertise lies in developing AI/ML systems end2end. From tracking and data collection, through data transformation, training pipelines and model deployment, to model monitoring and A/B testing. I usually work with the following tech stack:

PythonPythonAWSAWSGCPGCPTensorFlowTensorFlowPyTorchPyTorchAirflowAirflowKafkaKafkaDockerDockerKubernetesKubernetesTerraformTerraformLangChainLangChainLangGraphLangGraph

Published papers and articles

Great ideas get published. Profiting ideas stay put. But hey, I still managed to publish a few!

During my Ph.D. and my professional career I’ve published over 10 papers, about half of them in high impact journals. The papers are in the field of machine learning, optimization, pattern recognition from images and time series, and general statistics. Here are some examples of recently published papers. I also included selected published articles in Medium.

Conference • RecSys (Workshop)
Combining Bundle Economy and Relevancy through Content Recommendations in Candy Crush Saga
Recommender systemContinuous retrainingFeedback loopsUser preference
Read
Journal • Physica A: Statistical Mechanics and its Applications
Hurst exponent estimation of fractional surfaces for mammogram images analysis
Pattern recognitionImagingMaximum likelihood
Read
Journal • Methodology and Computing in Applied Probability
Bayesian approach to Hurst exponent estimation
Bayesian analysisTime seriesOptimization
Read
Article • Medium
An empirical approach to automatic data decomposition
Data engineeringMLOpsSQLData Warehouse
Read

Presentations and talks

Too much non-technical nonsense about AI recently on many conferences. Several times, I've taken a suit and stepped in.

Talks illustration
2025 • ML Prague
Attentive interpretable models for scalable content recommendation in mobile games
Event page
2024 • AI World Summit Amsterdam
Integrating predictions to client-server architecture in mobile games
Event page
2023 • Machine Learning Week Europe
Addressing challenges in iterative model development for recommender systems
Event page

AI/ML Workshops

Work hard, shop smart — that’s all about workshops!

I don’t always do workshops, but when I do, I do make sure that it is memorable for the participants. Combining fun and learning is the best way to introduce new topics to others. And would never miss to give a quiz to the participants in the end! Here are some examples of workshops in the AI space that I’ve led.

Workshop on language models: Language model classifier presented as wine tasting challenge
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Contact me

If the webpage didn’t intimidate you yet, I welcome you to contact me! Maybe I’ll solve your next big AI challenge.

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