The best paper co-winners for 2020 are
ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines Tarique Siddiqui, Paul Luh, Zesheng Wang, Karrie Karahalios, Aditya Parameswaran
Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects Clemens Lutz, Sebastian Breß, Steffen Zeuch , Tilmann Rabl, Volker Markl
Authors of ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines
Tarique Siddiqui recently completed his Ph.D. from the University of Illinois at Urbana-Champaign (UIUC), advised by Aditya Parameswaran, His research broadly lies in data management and analytics, with a focus on developing systems for interactive data exploration. He has also been working on learning-based techniques for query optimization in large scale big data warehouses. He is a recipient of the Siebel Scholars Award, and has previously worked at Goldman Sachs after doing his undergraduate at National Institute of Technology in India. Tarique will soon be joining Microsoft Research as a researcher.
Paul Luh recently graduated with a master’s degree from the University of Wisconsin-Madison, advised by Professor Theodoros Rekatsinas. He has been working on novel data extraction systems that combine ideas from both machine learning and program synthesis. Prior to his M.S., he completed his B.S. from the University of Illinois at Urbana-Champaign, where he worked with Professor Aditya Parameswaran on interactive data exploration systems. Starting July, Paul will join NVIDIA as a software engineer.
Zesheng Wang is a software engineer at Roblox Corporation. He received his M.S. in Computer Science from the University of Illinois at Urbana-Champaign, advised by Professor Aditya Parameswaran. During his M.S. study, he has been working on interactive data exploration systems with a focus on query execution and optimization. Prior to his M.S., he studied at Jilin University in China for two years before he joined and completed his B.S. in Mathematics at the University of Illinois at Urbana-Champaign.
Karrie Karahalios is a Professor in Computer Science and University Scholar at the University of Illinois (UIUC) where she heads the Social Spaces Group. Karahalios completed an S.B. in Electrical Engineering, an M.Eng. in Electrical Engineering and Computer Science, and an S.M. and Ph.D. in Media Arts and Sciences at MIT. Her work focuses on the interaction between people and the social cues they perceive and emit in networked electronic spaces. This is operationalized through the design and analysis of social media systems, the visualization of communication dynamics, The auditing of algorithmic systems, and the creation of assistive technologies for communication in non-lab environments.
Aditya Parameswaran is an Assistant Professor in the School of Information (I School) and Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. Until June 2019, Aditya was an Assistant Professor in Computer Science at the University of Illinois, Urbana-Champaign. He spent a year as a PostDoc at MIT CSAIL following his Ph.D. at Stanford University. He develops systems and algorithms for “human-in-the-loop” data analytics, synthesizing techniques from database systems, data mining, and human-computer interaction.
Authors of Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects
Clemens Lutz is a PhD candidate advised by Volker Markl at TU Berlin. Clemens’ research focuses on data management using modern hardware and distributed systems. He is currently investigating how we can apply fast, next-generation interconnects such as NVLink to scale data management on GPUs. Before beginning his PhD in 2015, Clemens received his MSc in Computer Science from ETH Zurich in collaboration with IBM Research, Zurich. He also holds an International Diploma in Computing from Imperial College London.
Sebastian Breß is a Software Engineer at Snowflake Computing and a Postdoctoral Researcher in the DIMA Group of Volker Markl at Technische Universität Berlin. He received his PhD in computer science in 2015 from University of Magdeburg under the supervision of Gunter Saake and Jens Teubner (TU Dortmund). His thesis focused on efficient query processing in co-processor-accelerated databases. In the course of his research, he developed two systems: 1) CoGaDB, a GPU-accelerated column store targeting OLAP workloads and 2) Hawk, a hardware-adaptive query compiler for heterogeneous processor environments (CPUs, GPUs, MICs). His research interests include data management on modern hardware, stream processing, query compilation, and optimizing database systems for heterogeneous processors.
Steffen Zeuch is a Senior Researcher at the DIMA group (TU Berlin) and IAM group (DFKI). He received his Ph.D. in Computer Science at Humboldt University Berlin in the research group of Prof. Freytag. Steffen is conducting research in data management, with an emphasis on topics related to modern hardware, distributed systems, and IoT environments. Currently, he is the project lead of the NebulaStream (www.nebula.stream) project at DIMA, which builds a new data management for the Internet of Things. He has published research papers on query optimization and execution as well as on novel system architectures in many top-tier conferences.
Tilmann Rabl holds the chair for Data Engineering Systems at the Hasso Plattner Institute and is Professor at the Digital Engineering Department of the University of Potsdam. He is also cofounder and scientific director of the startup bankmark. His research interest are in database systems, data processing on modern hardware, stream processing, and benchmarking. He received his PhD at the University of Passau in 2011 and was postdoc at the University of Toronto in the Middleware Systems Group. Before joining HPI, he was visiting professor at the Database Systems and Information Management (DIMA) group at Technische Universität Berlin and Vice Director of the Intelligent Analytics for Massive Data (IAM) Group at the German Research Center for Artificial Intelligence (DFKI).
Volker Markl is a Full Professor and Chair of the Database Systems and Information Management (DIMA) Group at the Technische Universität Berlin (TU Berlin). At the German Research Center for Artificial Intelligence (DFKI), he is Chief Scientist and Head of the Intelligent Analytics for Massive Data Research Group. In addition, he is Director of the Berlin Institute for the Foundations of Learnig and Data (BIFOLD), a merger of the Berlin Big Data Center (BBDC) and the Berlin Center for Machine Learning (BZML). Volker Markl is a computer science graduate from Technische Universität München, where he earned his Diplom in 1995 with a thesis on exception handling in programming languages. He earned his PhD in 1999 the area of multidimensional indexing under the supervision of Rudolf Bayer. Volker Markl has published numerous research papers on indexing, query optimization, lightweight information integration, and scalable data processing. He holds 18 patents, has transferred technology into several commercial products, and advises several companies and startups.