Qualcomm Technologies has just announced four winners of the Qualcomm Innovation Fellowship (QIF) for 2019. Among them are Mario Paulo Drumond and Kaicheng Yu, students at EPFL’s School of Computer and Communication Sciences (EDIC). They have been recognized by Qualcomm for their outstanding research proposals on emerging technologies.
Google AI has announced the list of winners for its Faculty Research Awards (2018), and among them is Professor Volkan Cevher from the LIONS’ lab at EPFL. He has earned the distinction under the category ‘Machine learning and data mining.” He is one of only two winners from Europe in that category.
In 2009, EPFL professors Anastasia Ailamaki and Babak Falsafi collaborated with their doctoral and postdoctoral students to present Shore-MT, a scalable storage manager for the multicore era. A decade later, Shore-MT continues to be a robust open-source database storage manager preferred by many users worldwide. In recognition of its continued relevance and usage, the original research paper has been honored with the 2019 EDBT Test-of-Time Award.
The impact of scientific research findings remains limited unless they are disseminated among the research community as a whole. However, sharing research openly is not easy because of many cultural and technological barriers. In a bid to remove those impediments in the way of open research, EPFL President Martin Vetterli launched the Open Science Fund in September 2018.
We are investigating new stochastic theories and analytics including statistical learning techniques, machine training and inference systems and their applications to IoT, social media and big data platforms.
We are investigating technologies to maximize efficiency with in-memory data services, in-situ query processing on streamed data, and on-demand query engine customization using multi-objective compiler optimization.
We are investigating a three-pronged approach to holistic data platforms and datacenter efficiency: vertical integration to minimize data-movement; specialization to optimize work per service; and approximation to tailor work for output quality.
We are investigating technologies spanning from decentralized trust and cryptography to robustness and resiliency of natural processes to strengthen security, privacy and trust in data platforms and systems.