Welcome!

I am a computer scientist working as a postdoctoral scholar at Globus Labs led by Prof. Ian Foster in the Department of Computer Science at the University of Chicago since November 2022. I am also the founder and elected chair of the SPEC RG Predictive Data Analytics Working Group.

In a nutshell, my research vision is to provide intuitive, efficient, and sustainable data science solutions across all disciplines and domains. Therefore, I focus on fusing Software Engineering, Performance Engineering, and Data Science. More precisely, my research vision encompasses the following three main pillars:

• Improvement of data science methods as well as their infrastructure (i.e., improve performance).
• Development of an automated framework to streamline the data science task (i.e., improve usability).
• Raise awareness and support for sustainable data science (i.e., improve energy efficiency).

In general, my research interest lies in, but is not limited to:

• Data management: The focus is on FAIR (findable, accessible, interoperable, and reusable) data management and the promotion of publicly available research data.
• Data privacy: The idea here is to exchange data with third parties, preserving the privacy of the data. I am interested in synthetic data generation and homomorphic encryption.
• Data science clouds: I am interested in the development, autonomous management (i.e., autonomous scaling of resources), benchmarking of various building blocks of such clouds, and runtime prediction and scheduling of data analytic tasks.
• Data science: My focus is on data analytics, clustering, and imputation. I am also interested in benchmarking and developing data analytics methods. In addition, I work on the application of such methods in interdisciplinary projects.
• Sustainable data science: Specifically, this involves the development of an energy efficiency benchmark for Deep and Machine Learning.