Best thesis award for Nithish Sankaranarayanan

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Best thesis award for Nithish Sankaranarayanan

Best Thesis Award for Nithish Sankaranarayanan

BIFOLD student Nithish Sankaranarayanan received the “Best Systems Related Master’s Thesis Award” for his work “Efficient Operator Placement for Mutating Query Plans”. He won the award for outstanding scientific contribution and open source contribution in the Big Data Management and Analytics (BDMA) Master’s Programme.

To use resources efficiently in the Internet-of-Things environment, sharing common computation amongst concurrently executing queries is necessary.  However, such a sharing must not disrupt the execution of running queries.  This thesis proposes a novel approach to deploy queries after identifying sharing opportunities in a disruption-free manner.

Nithish Sankaranarayanan was scientifically supervised by Ankit Chaudhary, Dr. Steffen Zeuch and Prof. Dr. Volker Markl.

Best Poster Award for Kim Nicoli

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Best Poster Award for Kim Nicoli

Best Poster Award for Kim Nicoli

During the Summer School on Machine Learning for Quantum Physics and Chemistry, in September 2021 in Warsaw, BIFOLD PhD candidate Kim. A. Nicoli was awarded with the Best Poster Award. His poster was democratically selected by the participants and the scientific committee for being the best amongst more than 80 participants. The corresponding paper “Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models” is a joint international effort of several BIFOLD researchers: Kim Nicoli, Christopher Anders, Pan Kessel, Shinichi Nakajima, as well as a group of researchers affiliated with DESY (Zeuthen) and other institutions. The work is published in Physics Review Letters.

Kim A. Nicoli
(Copyright: Kim Nicoli)

“Modeling and understanding the interactions of quarks, fundamental subatomic, yet indivisible particles, which represent the smallest known units of matter, is the main goal of current ongoing research in the field of High Energy Physics. Deepening our understanding of such phenomena, leveraging on modern machine learning techniques, would have some important implications in many related fields of applied science and research, such as quantum computer devices, drug discoveries and many more.”

The summer school on Machine Learning for Quantum Physics and Chemistry was co-organized by the University of Warzaw and the Institute for Photonics Sciences, Barcelona.

More information: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.126.032001