About Panagiotis Kalnis Panagiotis Kalnis Professor, Computer Science supercomputing infoclouds Professor Panos Kalnis is a leading researcher in big data, cloud computing, parallel and distributed systems and computing privacy for data mining and bioinformatics. Articles Related News June 2021 Algorithmic, Systems and Privacy Aspects of Split Learning 1 min read · Tue, Jun 1 2021 News Federated learning (FL) is a new machine learning setting introduced in 2016 in a sequence of papers resulting from a collaboration between a Google team led by Brendan McMahan and Peter Richtarik’s group. Key idea: Many clients (e.g., mobile phones, IoT devices or organizations) collaboratively train a machine learning model under the orchestration of a central trusted server, while keeping the training data stored on the client devices in a decentralized fashion in order to protect privacy. Split learning (SL) is a new federated learning tool specifically developed for training of deep April 2020 Peeling back the layers of deep machine learning 1 min read · Fri, Apr 17 2020 News machine learning artificial intelligence Computer science A layer-based approach raises the efficiency of training artificial intelligence models. September 2019 AI learns complex gene-disease patterns 1 min read · Sun, Sep 1 2019 News health artificial intelligence big data Computer science A deep learning model improves the ability to identify genes potentially involved in disease. June 2019 Querying big data just got universal 1 min read · Sun, Jun 23 2019 News big data algorithm Computer science A universal query engine for big data that works across computing platforms could accelerate analytics research. January 2017 New Data Mining approach makes recurring patterns easier to be spotted 1 min read · Wed, Jan 18 2017 News supercomputing infoclouds Frequent subgraph mining algorithm The ultimate answer is ScaleMine, cost-effective and agile scalable parallel frequent subgraph mining in a single large graph. Panagiotis Kalnis, Professor of Computer Science (CS), and the team from the KAUST Extreme Computing Research Center (ECRC), under the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division signed this novel approach. December 2016 Divide and conquer pattern searching 1 min read · Tue, Dec 27 2016 News Computer science computing Searching for recurring patterns in network systems has become a fundamental part of research and discovery in fields as diverse as biology and social media. KAUST researchers have developed a pattern or graph-mining framework that promises to significantly speed up searches on massive network data sets. “A graph is a data structure that models complex relationships among objects,” explained Panagiotis Kalnis, leader of the research team from the KAUST Extreme Computing Research Center. “Graphs are widely used in many modern applications, including social networks, biological networks like CEMSE Big Data Open Day shows off fascinating discoveries 4 min read · Thu, Dec 8 2016 News big data machine learning knowledge discovery supercomputing The fifth-anniversary event marked CEMSE's biggest successes and featured 20 KAUST discoveries, with more than 1,000 visitors from the community attending the event."Big data has many applications: to understand medicine better; to manage food supplies, and to connect objects. Data is at the center of everything," said Dean Mootaz Elnozahy of the University's Computer, Electrical, Mathematical Science and Engineering (CEMSE) Division at the CEMSE Big Data Open Day held on December 4, 2016. March 2016 InfoCloud celebrated the first 100 citations from an InfoCloud Student 1 min read · Tue, Mar 8 2016 News infoclouds InfoCloud celebrated the first 100 citations from an InfoCloud Student. February 2016 InfoCloud celebrated the year 2015 as the most productive year! 10 Full papers and 3 demos 1 min read · Mon, Feb 22 2016 News infocloud InfoCloud celebrated the year 2015 as the most productive year! 10 Full papers and 3 demos. January 2016 InfoCloud has published a paper "Accelerating SPARQL queries by exploiting hash-based locality and adaptive partitioning" in the VLDB Journal 2016 1 min read · Thu, Jan 7 2016 News infocloud InfoCloud has published a paper "Accelerating SPARQL queries by exploiting hash-based locality and adaptive partitioning" in the VLDB Journal 2016. December 2015 InfoCloud has published a paper "Progress and challenges in bioinformatics approaches for enhancer identification" in Briefings in Bioinformatics 2015 1 min read · Fri, Dec 4 2015 News machine learning bioinformatics Computer science InfoCloud has published a paper "Progress and challenges in bioinformatics approaches for enhancer identification" in Briefings in Bioinformatics 2015. November 2015 InfoCloud has published a paper "Karect: accurate correction of substitution, insertion and deletion errors for next-generation sequencing data" in Bioinformatics 1 min read · Tue, Nov 3 2015 News bioinformatics InfoCloud has published a paper "Karect: accurate correction of substitution, insertion and deletion errors for next-generation sequencing data" in Bioinformatics September 2015 In collaboration with QCRI, InfoCloud published a paper "Lightning fast and space efficient inequality joins" in VLDB 2015. 1 min read · Tue, Sep 1 2015 News algorithm In collaboration with QCRI, InfoCloud published a paper "Lightning fast and space-efficient inequality joins" in VLDB 2015. August 2015 InfoCloud is presenting three demo papers in VLDB 2015 1 min read · Sat, Aug 1 2015 News InfoCloud is presenting three demo papers in VLDB 2015. July 2015 In collaboration with the National University of Singapore, InfoCloud published a paper in Oxford University Press 1 min read · Wed, Jul 15 2015 News pathogens In collaboration with the National University of Singapore, InfoCloud published a paper in Oxford University Press on "Hi-Jack: a novel computational framework for pathway-based inference of host-pathogen interactions. May 2015 In collaboration with QCRI and MIT, InfoCloud published a paper in SIGMOD 2015 on "BigDansing: A System for Big Data Cleansing" 1 min read · Sun, May 31 2015 News big data In collaboration with QCRI and MIT, InfoCloud published a paper in SIGMOD 2015 on "BigDansing: A System for Big Data Cleansing." January 2015 InfoCloud published in Nucleic acids research paper "DEEP: a general computational framework for predicting enhancers." 1 min read · Thu, Jan 8 2015 News computational methods InfoCloud published in Nucleic acids research paper "DEEP: a general computational framework for predicting enhancers." December 2014 InfoCloud published in the VLDB Journal a paper "ACME: A scalable parallel system for extracting frequent patterns from a very long sequence" 1 min read · Mon, Dec 1 2014 News bioinformatics automatic tuning mechanism InfoCloud published in the VLDB Journal a paper "ACME: A scalable parallel system for extracting frequent patterns from a very long sequence." March 2014 InfoCloud published a paper in VLDB 2014 on "Grami: Frequent subgraph and pattern mining in a single large graph" 1 min read · Sat, Mar 1 2014 News Frequent subgraph mining InfoCloud published a paper in VLDB 2014 on "Grami: Frequent subgraph and pattern mining in a single large graph". August 2013 InfoCloud published a paper in VLDB 2014 on "RACE: a scalable and elastic parallel system for discovering repeats in very long sequences" 1 min read · Mon, Aug 26 2013 News RACE InfoCloud published a paper in VLDB 2014 on "RACE: a scalable and elastic parallel system for discovering repeats in very long sequences." February 2013 The Mizan paper got accepted to the 8th ACM European conference on Computer Systems-EuroSys 2013 1 min read · Wed, Feb 27 2013 News large-scale graph processing The Mizan paper got accepted to the 8th ACM European conference on Computer Systems-EuroSys 2013. January 2013 InfoCloud in collaboration with MIT is organizing the 2013 ACM-SIGMOD programming contest 1 min read · Wed, Jan 23 2013 News SIGMOD InfoCloud in collaboration with MIT is organizing the 2013 ACM-SIGMOD programming contest. December 2012 InfoCloud has openings for new members 1 min read · Fri, Dec 14 2012 News Infocloud has openings for faculty members, research scientists, postdoctoral fellows, Ph.D. and masters students, and internships. August 2012 Dr. Essam Mansour presented the paper entitled "ERA: Efficient Serial and Parallel Suffix Tree Construction for Very Long Strings" at VLDB 2012 1 min read · Wed, Aug 29 2012 News suffix tree Dr. Essam Mansour presented the paper entitled "ERA: Efficient Serial and Parallel Suffix Tree Construction for Very Long Strings" at VLDB 2012.
Algorithmic, Systems and Privacy Aspects of Split Learning 1 min read · Tue, Jun 1 2021 News Federated learning (FL) is a new machine learning setting introduced in 2016 in a sequence of papers resulting from a collaboration between a Google team led by Brendan McMahan and Peter Richtarik’s group. Key idea: Many clients (e.g., mobile phones, IoT devices or organizations) collaboratively train a machine learning model under the orchestration of a central trusted server, while keeping the training data stored on the client devices in a decentralized fashion in order to protect privacy. Split learning (SL) is a new federated learning tool specifically developed for training of deep
Peeling back the layers of deep machine learning 1 min read · Fri, Apr 17 2020 News machine learning artificial intelligence Computer science A layer-based approach raises the efficiency of training artificial intelligence models.
AI learns complex gene-disease patterns 1 min read · Sun, Sep 1 2019 News health artificial intelligence big data Computer science A deep learning model improves the ability to identify genes potentially involved in disease.
Querying big data just got universal 1 min read · Sun, Jun 23 2019 News big data algorithm Computer science A universal query engine for big data that works across computing platforms could accelerate analytics research.
New Data Mining approach makes recurring patterns easier to be spotted 1 min read · Wed, Jan 18 2017 News supercomputing infoclouds Frequent subgraph mining algorithm The ultimate answer is ScaleMine, cost-effective and agile scalable parallel frequent subgraph mining in a single large graph. Panagiotis Kalnis, Professor of Computer Science (CS), and the team from the KAUST Extreme Computing Research Center (ECRC), under the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division signed this novel approach.
Divide and conquer pattern searching 1 min read · Tue, Dec 27 2016 News Computer science computing Searching for recurring patterns in network systems has become a fundamental part of research and discovery in fields as diverse as biology and social media. KAUST researchers have developed a pattern or graph-mining framework that promises to significantly speed up searches on massive network data sets. “A graph is a data structure that models complex relationships among objects,” explained Panagiotis Kalnis, leader of the research team from the KAUST Extreme Computing Research Center. “Graphs are widely used in many modern applications, including social networks, biological networks like
CEMSE Big Data Open Day shows off fascinating discoveries 4 min read · Thu, Dec 8 2016 News big data machine learning knowledge discovery supercomputing The fifth-anniversary event marked CEMSE's biggest successes and featured 20 KAUST discoveries, with more than 1,000 visitors from the community attending the event."Big data has many applications: to understand medicine better; to manage food supplies, and to connect objects. Data is at the center of everything," said Dean Mootaz Elnozahy of the University's Computer, Electrical, Mathematical Science and Engineering (CEMSE) Division at the CEMSE Big Data Open Day held on December 4, 2016.
InfoCloud celebrated the first 100 citations from an InfoCloud Student 1 min read · Tue, Mar 8 2016 News infoclouds InfoCloud celebrated the first 100 citations from an InfoCloud Student.
InfoCloud celebrated the year 2015 as the most productive year! 10 Full papers and 3 demos 1 min read · Mon, Feb 22 2016 News infocloud InfoCloud celebrated the year 2015 as the most productive year! 10 Full papers and 3 demos.
InfoCloud has published a paper "Accelerating SPARQL queries by exploiting hash-based locality and adaptive partitioning" in the VLDB Journal 2016 1 min read · Thu, Jan 7 2016 News infocloud InfoCloud has published a paper "Accelerating SPARQL queries by exploiting hash-based locality and adaptive partitioning" in the VLDB Journal 2016.
InfoCloud has published a paper "Progress and challenges in bioinformatics approaches for enhancer identification" in Briefings in Bioinformatics 2015 1 min read · Fri, Dec 4 2015 News machine learning bioinformatics Computer science InfoCloud has published a paper "Progress and challenges in bioinformatics approaches for enhancer identification" in Briefings in Bioinformatics 2015.
InfoCloud has published a paper "Karect: accurate correction of substitution, insertion and deletion errors for next-generation sequencing data" in Bioinformatics 1 min read · Tue, Nov 3 2015 News bioinformatics InfoCloud has published a paper "Karect: accurate correction of substitution, insertion and deletion errors for next-generation sequencing data" in Bioinformatics
In collaboration with QCRI, InfoCloud published a paper "Lightning fast and space efficient inequality joins" in VLDB 2015. 1 min read · Tue, Sep 1 2015 News algorithm In collaboration with QCRI, InfoCloud published a paper "Lightning fast and space-efficient inequality joins" in VLDB 2015.
InfoCloud is presenting three demo papers in VLDB 2015 1 min read · Sat, Aug 1 2015 News InfoCloud is presenting three demo papers in VLDB 2015.
In collaboration with the National University of Singapore, InfoCloud published a paper in Oxford University Press 1 min read · Wed, Jul 15 2015 News pathogens In collaboration with the National University of Singapore, InfoCloud published a paper in Oxford University Press on "Hi-Jack: a novel computational framework for pathway-based inference of host-pathogen interactions.
In collaboration with QCRI and MIT, InfoCloud published a paper in SIGMOD 2015 on "BigDansing: A System for Big Data Cleansing" 1 min read · Sun, May 31 2015 News big data In collaboration with QCRI and MIT, InfoCloud published a paper in SIGMOD 2015 on "BigDansing: A System for Big Data Cleansing."
InfoCloud published in Nucleic acids research paper "DEEP: a general computational framework for predicting enhancers." 1 min read · Thu, Jan 8 2015 News computational methods InfoCloud published in Nucleic acids research paper "DEEP: a general computational framework for predicting enhancers."
InfoCloud published in the VLDB Journal a paper "ACME: A scalable parallel system for extracting frequent patterns from a very long sequence" 1 min read · Mon, Dec 1 2014 News bioinformatics automatic tuning mechanism InfoCloud published in the VLDB Journal a paper "ACME: A scalable parallel system for extracting frequent patterns from a very long sequence."
InfoCloud published a paper in VLDB 2014 on "Grami: Frequent subgraph and pattern mining in a single large graph" 1 min read · Sat, Mar 1 2014 News Frequent subgraph mining InfoCloud published a paper in VLDB 2014 on "Grami: Frequent subgraph and pattern mining in a single large graph".
InfoCloud published a paper in VLDB 2014 on "RACE: a scalable and elastic parallel system for discovering repeats in very long sequences" 1 min read · Mon, Aug 26 2013 News RACE InfoCloud published a paper in VLDB 2014 on "RACE: a scalable and elastic parallel system for discovering repeats in very long sequences."
The Mizan paper got accepted to the 8th ACM European conference on Computer Systems-EuroSys 2013 1 min read · Wed, Feb 27 2013 News large-scale graph processing The Mizan paper got accepted to the 8th ACM European conference on Computer Systems-EuroSys 2013.
InfoCloud in collaboration with MIT is organizing the 2013 ACM-SIGMOD programming contest 1 min read · Wed, Jan 23 2013 News SIGMOD InfoCloud in collaboration with MIT is organizing the 2013 ACM-SIGMOD programming contest.
InfoCloud has openings for new members 1 min read · Fri, Dec 14 2012 News Infocloud has openings for faculty members, research scientists, postdoctoral fellows, Ph.D. and masters students, and internships.
Dr. Essam Mansour presented the paper entitled "ERA: Efficient Serial and Parallel Suffix Tree Construction for Very Long Strings" at VLDB 2012 1 min read · Wed, Aug 29 2012 News suffix tree Dr. Essam Mansour presented the paper entitled "ERA: Efficient Serial and Parallel Suffix Tree Construction for Very Long Strings" at VLDB 2012.
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