Sreenivas R. Sukumar

Publication Activity (10 Years)

Years Active: 2003-2021
Publications (10 Years): 17

Top Topics

Diabetic Retinopathy

Knowledge Discovery

Top Venues

Publications

Sreenivas R. Sukumar, Jacob Balma, Cong Xu, Sergey Serebryakov
Survival of the Fittest Amidst the Cambrian Explosion of Processor Architectures for Artificial Intelligence : Invited Paper. PEHC@SC (2021)
Sreenivas R. Sukumar, Jacob A. Balma, Christopher D. Rickett, Kristyn J. Maschhoff, Joseph Landman, Charles R. Yates, Amar G. Chittiboyina, Yuri K. Peterson, Aaron Vose, Kendall G. Byler, Jérôme Baudry, Ikhlas A. Khan
The Convergence of HPC, AI and Big Data in Rapid-Response to the COVID-19 Pandemic. SMC (2021)
Christopher D. Rickett, Kristyn J. Maschhoff, Sreenivas R. Sukumar
Massively Parallel Processing Database for Sequence and Graph Data Structures Applied to Rapid-Response Drug Repurposing. IEEE BigData (2020)
Jacob Balma, Aaron D. Vose, Yuri K. Peterson, Amar G. Chittiboyina, Pankaj Pandey, Charles R. Yates, Ikhlas A. Khan, Sreenivas R. Sukumar
Deep Learning Predicts Protein-Ligand Interactions. IEEE BigData (2020)
Rina Singh, Jeffrey A. Graves, Valentine Anantharaj, Sreenivas R. Sukumar
Evaluating Scientific Workflow Engines for Data and Compute Intensive Discoveries. IEEE BigData (2019)
Md Mosharaf Hossain, Thomas M. Hines, Sheikh K. Ghafoor, Sheikh Rabiul Islam, Ramakrishnan Kannan, Sreenivas R. Sukumar
A Flexible-blocking Based Approach for Performance Tuning of Matrix Multiplication Routines for Large Matrices with Edge Cases. IEEE BigData (2018)
Seokyong Hong, Sangkeun Lee, Seung-Hwan Lim, Sreenivas R. Sukumar, Ranga Raju Vatsavai
Evaluation of Pattern Matching Workloads in Graph Analysis Systems. HPDC (2016)
Luna Xu, Seung-Hwan Lim, Ali Raza Butt, Sreenivas R. Sukumar, Ramakrishnan Kannan
FatMan vs. LittleBoy: Scaling Up Linear Algebraic Operations in Scale-Out Data Platforms. PDSW-DISCS@SC (2016)
Sangkeun Lee, Sreenivas R. Sukumar, Seokyong Hong, Seung-Hwan Lim
Enabling graph mining in RDF triplestores using SPARQL for holistic in-situ graph analysis. Expert Syst. Appl. 48 (2016)
Sreenivas R. Sukumar, Ramakrishnan Kannan, Seung-Hwan Lim, Michael A. Matheson
Kernels for scalable data analysis in science: Towards an architecture-portable future. IEEE BigData (2016)
Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim
Mini-apps for high performance data analysis. IEEE BigData (2016)
Sangkeun Lee, Sreenivas R. Sukumar, Seung-Hwan Lim
Graph mining meets the Semantic Web. ICDE Workshops (2015)
Li-Shiang Tsay, Sreenivas R. Sukumar, Larry W. Roberts
Scalable association rule mining with predication on semantic representations of data. TAAI (2015)
Sreenivas R. Sukumar
Open research challenges with Big Data - A data-scientist's perspective. IEEE BigData (2015)
Seung-Hwan Lim, Sangkeun Lee, Gautam Ganesh, Tyler C. Brown, Sreenivas R. Sukumar
Graph Processing Platforms at Scale: Practices and Experiences. ISPASS (2015)
Katherine Senter, Sreenivas R. Sukumar, Robert M. Patton, Edward Chaum
Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. IEEE BigData (2015)
Rina Singh, Jeffrey A. Graves, Sangkeun Lee, Sreenivas R. Sukumar, Mallikarjun Shankar
Enabling graph appliance for genome assembly. IEEE BigData (2015)
Sreenivas R. Sukumar, Regina K. Ferrell
'Big Data' collaboration: Exploring, recording and sharing enterprise knowledge. Inf. Serv. Use 33 (3-4) (2013)
Varun Chandola, Sreenivas R. Sukumar, Jack C. Schryver
Knowledge discovery from massive healthcare claims data. KDD (2013)
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L. Page, Andreas F. Koschan, Mongi A. Abidi
On handling uncertainty in the fundamental matrix for scene and motion adaptive pose recovery. CVPR (2008)
Sreenivas R. Sukumar, David L. Page, Andreas F. Koschan, Mongi A. Abidi
Towards understanding what makes 3D objects appear simple or complex. CVPR Workshops (2008)
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L. Page, Andreas F. Koschan, Mongi A. Abidi
Learning structurally discriminant features in 3D faces. ICIP (2008)
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L. Page, Andreas F. Koschan, Mongi A. Abidi
Uncertainty minimization in multi-sensor localization systems using model selection theory. ICPR (2008)
Yi Yao, Sreenivas R. Sukumar, Besma R. Abidi, David L. Page, Andreas F. Koschan, Mongi A. Abidi
Automated Scene-Specific Selection of Feature Detectors for 3D Face Reconstruction. ISVC (1) (2007)
Sreenivas R. Sukumar, David L. Page, Hamparsum Bozdogan, Andreas F. Koschan, Mongi A. Abidi
MuFeSaC: Learning When to Use Which Feature Detector. ICIP (6) (2007)
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L. Page, Andreas F. Koschan, Mongi A. Abidi
Sensor Selection Using Information Complexity for Multi-sensor Mobile Robot Localization. ICRA (2007)
Sreenivas R. Sukumar, David L. Page, Andrei V. Gribok, Andreas F. Koschan, Mongi A. Abidi
Shape Measure for Identifying Perceptually Informative Parts of 3D Objects. 3DPVT (2006)
Sreenivas R. Sukumar, David L. Page, Andrei V. Gribok, Andreas F. Koschan, Mongi A. Abidi, David J. Gorsich, Grant R. Gerhart
Robotic three-dimensional imaging system for under-vehicle inspection. J. Electronic Imaging 15 (3) (2006)
David L. Page, Andreas F. Koschan, Sreenivas R. Sukumar, Besma Roui-Abidi, Mongi A. Abidi
Shape analysis algorithm based on information theory. ICIP (1) (2003)