Center for Ultra-scale Computing and Information Security (CUCIS) at Northwestern University

Time 2020-12-12 12:04:47

Web Name: Center for Ultra-scale Computing and Information Security (CUCIS) at Northwestern University

WebSite: http://cucis.ece.northwestern.edu

ID:131661

Keywords:

scale,Computing,and,

Description:

Welcome to the website for the Center for Ultra-scale Computing and Information Security at Northwestern University. The Center participants include faculty and researchers from the Department of Electrical Engineering and Computer Science, the Feinberg School of Medicine, and the Kellogg School of Management. CUCIS also has participants from various national labs such as Argonne National Laboratory (ANL), Sandia National Laboratory (SNL), Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and includes support from companies such as IBM, Intel, and Sun. Today's "connect anytime and anywhere" society based on the use of digital technologies is fueling tremendous data growth and transforming the way our business, science, and digital technology-based world functions. Data in the terabytes range are not uncommon today and are expected to reach petabytes for many application domains in science, engineering, business, bioinformatics, and medicine in the near future. Ultra-scale refers to the two to three orders of magnitude increase in data sizes, computing power, and complexity of data compared to what is considered today. As data becomes so pervasive, assurance, trust and security of information becomes of paramount importance. Secure computing, therefore, must be considered as an important parameter in any research dealing with ultra-scale computing. The goal of the Center for Ultra-scale Computing and Information Security (CUCIS) is to conduct highly innovative research in many synergistic areas of ultra-scale computing and information technologies. Furthermore, the goal of the center is to foster and enable inter-disciplinary research in computing technologies that scale to these levels. The CUCIS is directed by Prof. Alok Choudhary, and is presently supported by the NSF, DOE, Sandia National Labs, NASA, and Intel. To learn more, please use the navigation bar at the top of the page, or go directly to descriptions of our various research projects, a complete list of our publications, or more information about the group members. Software Developed by the Center: Data Mining NU-MineBench -- a collection of data mining algorithms and applications in sequential and parallel Parallel Data Clustering Algorithms -- a collection of massively parallel data clustering algorithms, including DBSCAN, OPTICS, and PINK Fast Max Clique Finder -- a sotfware suite to find the maximum cliques of large sparse graphs. See a use case in social network data. Parallel MEP -- a parallel community detection algorithm for graph data. The algorithm is based on the idea of maximizing equilibrium and purity of communities. The source codes are implemented in C and MPI to run on distributed-memory computer clusters. PrunedSearch -- A machine learning based meta-heuristic approach for constrained continuous optimization. Parallel netCDF -- a parallel I/O library for accessing netCDF files ElemNet -- Deep Learning the Chemistry of Materials From Only Elemental Composition and Enhancing Enhancing Materials Property Prediction by Leveraging Computational and Experimental Data using Deep Transfer Learning. IRNet -- A General Purpose Deep Residual Regression Framework for Materials Discovery. PADNet-XRD -- Peak Area Detection Network for Directly Learning Phase Regions from Raw X-ray Diffraction Patterns. EBSD-indexing -- Extracting Grain Orientations from EBSD Patterns of Polycrystalline Materials Using Convolutional Neural Networks. OPV_extratrees -- Machine Learning Framework for Estimating Efficiency of Organic Solar Cells using Extreme Random Forests microstructure-optimization-ml -- Microstructure optimization of constrained design objectives using machine learning based feedback aware data generation OPVPredictor -- Predictor for Highest Occupied Molecular Orbital (HOMO) Energy for Organic Photovoltaic Donor Molecules SINet -- A Transfer Learning Framework for Organic Solar Cell Prediction using Multi Input Single Output Neural Networks ml-iter-additive -- An iterative machine learning framework for predicting temperature profiles for an additive manufacturing process CheMixNet -- Mixed DNN Architectures for Predicting Properties using Multiple Molecular Representations microstructure-optimization-sampling -- Data Sampling Schemes for Galfenol Microstructure Optimization Deep_learning_homogenization -- A Deep Learning Model For Homogenization of Two-Phase High-Contrast Three-dimensional Materials ColonCancerOutcomeCalculator -- Colon Cancer Conditional Survival Outcome Calculator SIGRNN -- Synthetic Minority Instances Generation in Imbalanced Datasets Using a Recurrent Neural Network Approach Graduate Student Research Assistantship: We are looking for graduate students who are interested in pursuing a Ph.D. degree and study the following research areas: High-performance data mining. The research topics include design and development of algorithm in the field of data mining/ machine learning in general. The students will have opportunity to work with application domain scientists in materials, climatology, cosmology, medicine/bioinformatics and others. 2/12/2018Congratulations to Kathy Lee who earned her Ph.D. degree! She is now a Senior Scientist at the AI Lab of Acute Care Solutions in Philips Research. 1/24/2018Amar Krishna Raises $1 Million for New AI Cooking Assistant, Chefling Inc.,a news article published at Venture Beat. 2/5/2017 - PMEP, a parallel community detection software, is released. 9/14/2016 - Esteban Rangel presented the paper titled "Parallel DTFE Surface Density Field Reconstruction" in the 2016 IEEE International Conference on Cluster Computing, which is awarded the best paper of the conference. The paper is co-authored by Esteban Rangel, Nan Li, Salman Habib, Tom Peterka, Ankit Agrawal, Wei-Keng Liao, and Alok Choudhary. 8/23/2016 - The NSF features the expeditions project in an article titled: "Using data to better understand climate change" (Dr. Alok Choudhary is the project co-PI.) 10/7/2014 - Diana Palsetia was awarded a GHC Scholarship Grant to attend the 2014 Grace Hopper Celebration of Women in Computing. (scholar page) 4/7/2014 - Prof. Choudhary, has been quoted in a recent HPCWire article, titled, DOE Exascale Roadmap Highlights Big Data. As Choudhary observed of the report, titled, Big Data and Scientific Discovery, Very few large scale applications of practical importance are NOT data intensive. Read More 3/27/2014 - 4C, in partnership with Facebook has conducted a study to show the relationship between public Facebook behavioral data and television broadcast programming. By analyzing public Facebook data, 4C is helping networks make intelligent programming decisions and enabling brands to more strategically place relevant advertisements both on television and on Facebook. Read More 1/21/2014 - Prof. Alok Choudhary has received major funding for his big data startup, 4C. The amount of $5 million from Chicago-based venture fund Jump Capital was awarded to the Social Intelligence Company based on 4C's platforms application of algorithms. Based on decades of research by Prof. Choudhary, these algorithm mine social-media data around the globe to help advertisers target their campaigns on television, Twitter, Facebook and other media channels. Read More Prof. Alok Choudhary gave a plenary talk, "Big Data + Big Compute = An Extreme Scale Marriage for Smarter Science?" at the Supercomputing Conference on Thursday, Nov 21, 2013, at the Denver Convention Center. [slides] (25 MB) Read More 11/21/2013 - Parallel netCDF was used in petascale simulation of hurricane Sandy running on 437,760 computer cores of the Cray XE6 Blue Waters supercomputer at the National Center for Supercomputing Applications. 11/2013 - Md. Mostofa Ali Patwary, Diana Palsetia, Ankit Agrawal, Wei-keng Liao, Fredrik Manne, and Alok Choudhary. "Scalable Parallel OPTICS Data Clustering Using Graph Algorithmic Techniques" has been published in the proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November 17-22, 2013 in Denver, Colorado. 08/2013 - Zhengzhang Chen, Yusheng Xie, Yu Cheng, Kunpeng Zhang, Ankit Agrawal, Wei-keng Liao, Nagiza Samatova, Alok Choudhary, "Forecast Oriented Classification of Spatio-Temporal Extreme Events" has been published in the proceedings of the 23rd International Joint Conference on Artificial Intelligence to be held in Beijing, China, on August 3-9, 2013. - Yusheng Xie, Zhengzhang Chen, Kunpeng Zhang, Yu Cheng, Ankit Agrawal, Wei-keng Liao, Alok Choudhary, "Detecting and Tracking Disease Outbreaks in Real-time through Social Media" has been published in the proceedings of the 23rd International Joint Conference on Artificial Intelligence to be held in Beijing, China, on August 3-9, 2013. 07/2013 - Twitter API Partner Voxsup Applies Data Science to Social Media 05/2013 - Zhengzhang Chen, John Jenkins, Jinfeng Rao, Alok Choudhary, Fredrick Semazzi, Anatoli V Melechko, Vipin Kumar, and Nagiza F Samatova, "Automatic Detection and Correction of Multi-class Classification Errors Using System Whole-part Relationships" has been published in the proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013 in Austin, Texas. - Yusheng Xie, Zhengzhang Chen, Kunpeng Zhang, Md Mostofa Ali Patwary, Yu Cheng, Haotioan Liu, Ankit Agrawal, and Alok Choudhary, "Graphical Modeling of Macro Behavioral Targeting in Social Networks" has been published in the proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013 in Austin, Texas. 04/2013 - Jason Scott Mathias, Ankit Agrawal, Joe Feinglass, Andrew J Cooper, David William Baker, Alok Choudhary, "Development of a 5 year life expectancy index in older adults using predictive mining of electronic health record data" has been published in the Journal of the American Medical Informatics Association, (04/2013), (pdf), (supplement). 03/2013 - Daniel Honbo, Amit Pande, Alok Choudhary, "FPGA Architecture for Pairwise Statistical Significance Estimation", has been published in The International Journal of High Performance Systems Architecture. Link 02/2013 - Bharath Pattabiraman, Stefan Umbreit, Wei-keng Liao, Alok Choudhary, Vassiliki Kalogera, Gokhan Memik, Frederic A. Rasio, "A Parallel Monte Carlo Code for Simulating Collisional N-body Systems", has been published in The Astrophysical Journal Supplement, Volume 204, Issue 2, article id. 15, 16 pp. PDF 01/2013 - Tasty Trade, a real financial network interviews Alok Choudhary (Interview). - EECS Graduate Student Poster Fair -- Kathy Lee presented "Real-Time Flu Surveillance using Twitter Data". Diana Palsetia presented "User-Interest based Community Extraction in Social Networks". Professor William Hendrix was a judge. EECS Home | McCormick Home | Northwestern Home | Calendar: Plan-It Purple 2011 Robert R. McCormick School of Engineering and Applied Science, Northwestern University Tech : 2145 Sheridan Rd, Tech L359, Evanston IL 60208-3118 | Phone: (847) 491-5410 | Fax: (847) 491-4455 Ford : 2133 Sheridan Rd, Ford Building, Rm 3-320, Evanston, IL 60208 | Fax: (847) 491-5258 Email Director Last Updated:

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