Besides teaching and research, investing time in projects and activities that further the science and community are rewarding.
Master thesis supervision
Sebastien Ollquist: Sequential Pattern Mining in Very Large Data Streams - done at Swisscom.
Youssef Saied: Distance-based anomaly detection - done at Oracle Zurich.
Ciprian Baetu: In-Memory Graph Query Runtime inside Relational Databases - done at Oracle Labs Zurich.
EPFL IC Ph.D. student organization (EPIC) committee member
Faculty and industry talk coordinator bringing together the faculty, alumni, industry, and student community to exchange ideas and experiences. This provides a doctoral-school level platform to get together and interact with distinguished faculty members more directly and informally and a forum for discussing challenges and opportunities in industry and organizations.
EU H2020 Project Sustainable Data Lakes for Extreme-Scale Analytics
Research and development on top of the in-house high-performance heterogeneous analytical engine Proteus to enable storage tiering, approximate query processing, and high-performance integration with project components of other participating partners, especially with the RAW labs and TU Eindhoven research and industrial partners. Presenting and discussing the progress, design, and research ideas with the project partners. Preparing, reviewing, and participating in project reporting and presentations, leading to successful project evaluation.
EU ERC 2017 PoC ViDaR: R-enabled large-scale data analytics in ViDa
Research and development for developing an R-based interface to enable faster analytics with low additional coding overhead for scientific users while keeping interoperability with existing tools and libraries on top of the high-performance in-house analytical engine Proteus. Explored the full system stack and low-level system primitives written in C++/LLVM, learned high-performance analytics, query optimization in Apache Calcite, and the language primitives of the R programming language, and developed and evaluated a successful system prototype.
Summer@EPFL hosted at DIAS Lab
Research and development to improve the usability of cutting-edge research prototypes of spatial indexes written in C++ by exposing the functionality to users in the Python ecosystem. Developed and benchmarked low-overhead code wrappers and demonstrated the interoperability of the existing high-performance codebase by simulating a scientific workflow fully in Jupyter Notebooks, showing how to improve the usability of system prototypes without having to reimplement the codebase on the platform and languages of the intended users