With decades of experience in computer science, I have emerged as a Senior Data Scientist and MLOps Engineer with a strong foundation in programming. My diverse expertise ranges from legacy technologies to modern advancements, allowing me to excel in various roles such as data scientist, MLOps cloud architect, and classical statistician.

As a proven team player and leader, I have honed my collaborative skills while mentoring small groups, supervising students, and delivering lectures on AI, ML, and HCI. My dedication to knowledge sharing extends to my work as an associate chair for the leading CHI conference and program chair at the NordicCHI conference.

In addition to my extensive data science experience, I hold a Ph.D. in Computer Science and have published over 40 scientific articles on physiological and affective computing. My expertise in real-time adaptive systems, including emotionally adaptive games and VR movies, has allowed me to design and execute high-quality, scientifically valid HCI/UX experiments in various settings.

As a Lead Data Scientist, I am highly proficient in extracting, cleaning, and analyzing real-life, multimodal physiological datasets. My strong background in traditional statistical analyses, machine learning, and data mining approaches has resulted in numerous top-tier journal publications. I am committed to best practices in MLOps, which include implementing data lake houses, DevOps pipelines, secure and central storage, and easy deployment of real-time models to the cloud and IoT Edge devices.

Skills & Technologies:

Languages: Python, C/C++, Java
Analysis: R, SPSS, Python, Matlab
Machine Learning: Scikit-learn, PyTorch, TensorFlow, Keras, ONNX, Azure ML, Spark MLlib
MLOps: Azure, Databricks, MLflow, Kubernetes
As a forward-thinking Lead Data Scientist and MLOps Engineer, I continually strive to stay ahead of the curve and deliver exceptional results. My diverse experience and proven expertise make me the ideal candidate for any organization seeking a skilled Principal Data Scientist, Staff Engineer, or similar leadership role in data science and engineering.