
Email
bremer5@llnl.gov 
Phone
(925) 4227365 
Organization
STE COMPSTE CASC DIVCENTER FOR APPLIED SCIENTIFIC COMPUTING DI
PeerTimo holds a shared appointment at Lawrence Livermore National Laboratory's (LLNL's) Center for Applied Scientific Computing (CASC), focusing on largescale data analysis and visualization, and at the University of Utah, serving as Associate Director for Research of the Center for Extreme Data Management Analysis and Visualization (CEDMAV). His research interests include largescale machine learning, data analysis, visualization, medical image analysis, topology, volume modeling, and virtual reality.
PeerTimo joined LLNL in December 2006. Prior to that, he was a postdoctoral research associate at the University of Illinois, UrbanaChampaign. He received a Ph.D. in computer science in 2004 from the University of California, Davis, and an M.S. and B.S. in mathematics/computer science from the Leipniz University, Hannover, Germany in 2000 and 1997, respectively.
PeerTimo is the coPrincipal Investigator (PI) of several projects, including a Department of Energy (DOE) project (ACTIVTBI) that seeks to apply DOE's high performance computing capabilities to accelerate new treatments for traumatic brain injury. He also is the coPI for LLNL initiatives in cognitive computing, applying advanced computing to biological research, highdimensional sampling, and variable precision computing, among others. PeerTimo sits on the Council of LLNL's Data Science Institute, whose mission is to enable excellence in data science research and applications across the Laboratory's core missions.
PROGRAM COMMITTEE LEADERSHIP AND PARTICIPATION
 CoChair Workshop on Visual Performance Analytics VPA 2014/2015/2016 conjuction with ACM/IEEE Supercomputing
 CoChair TopoInVis 2013 InternationalWorkshop on Topological Methods in Data Analysis and Visualization
 Organizer of the Foundations of Topological Analysis Workshop in affiliation with IEEE Vis 2010
 CEBDA 2018
 EGPGV 2018
 ISC High Performance Computing 2018
 Computer Graphics International 2013, 2014, 2015
 IEEE EuroVis 2012, 2013, 2014, 2017, 2018
 IEEE Visualization 2011, 2012, 2013, 2014
 ReVisE 2009 Refactoring Visualization from Experience
 TopoInVis 2009, 2011, 2013, 2015, 2017 International Workshop on Topological Methods in Data Analysis and Visualization
 NASAGEM New Advances in Shape Analysis and Geometric Modeling 2007
PROFESSIONAL MEMBERSHIPS
 Association for Computing Machinery (ACM)
 Institute of Electrical and Electronics Engineers (IEEE)
RECENT REFEREED PUBLICATIONS (BOOK CHAPTERS, JOURNAL ARTICLES, AND CONFERENCE PROCEEDINGS)
 B. Kailkhura, J. J. Thiagarajan, C. Rastogi, P. V. Varshney, and P.T. Bremer. A spectral approach for the design of experiments: Design, analysis and algorithms. Journal of Machine Learning Research, 2018.
 B. K. Spears, J. Brase, P.T. Bremer, B. Chen, J. Field, J. Gaffney, M. Kruse, S. Langer, K. Lewis, R. Nora, J. L. Peterson, J. J. Thiagarajan, B. Van Essen, and K. Humbird. Deep learning: A guide for practitioners in the physical sciences. Physics of Plasmas, 25(8):080901, 2018.
 D. Hoang, P. Klacansky, H. Bhatia, P.T. Bremer, P. Lindstrom, and V. Pascucci. A study of the tradeoff between reducing precision and reducing resolution for data analysis and visualization. IEEE Trans. Vis. Comp. Graph., 2018.
 A. Gyulassy, P.T. Bremer, and V. Pascucci. Sharedmemory parallel computation of morsesmale complexes with improved accuracy sharedmemory parallel computation of morsesmale complexes with improved accuracy. IEEE Trans. Vis. Comp. Graph., 2018.
 H. Bhatia, A. Gyulassy, V. Lordi, J. Pask, V. Pascucci, and P.T. Bremer. Topoms: Comprehensive topological exploration for molecular and condensedmatter systems. Journal of Comp. Chem., 2018.
 G. Kindlmann, C. Chiw, T. Huynh, A. Gyulassy, P.T. Bremer, and J. Reppy. Rendering and extracting extremal features in 3d fields. Comput. Graph. Forum, 2018.
 H. Bhatia, N. Jain, A. Bhatele, Y. Livnat, V. Pascucci, and P.T. Bremer. Interactive investigation of traffic congestion on fattree networks using treescope interactive investigation of traffic congestion on fattree networks using treescope. Comput. Graph. Forum, 2018.
 S. Liu, J. J. Thiagarajan, and P.T. Bremer. Exploring highdimensional structure via axisaligned decomposition of linear projections. Comput. Graph. Forum, 2018.
 R. Anirudh, H. Kim, J. J. Thiagarajan, K.A. Mohan, K. Champley, and P.T. Bremer. Lose the views: Limited angle CT reconstruction via implicit sinogram completion. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
 S. Petruzza, S. Treichler, V. Pascucci, and P.T. Bremer. Babelflow: An embedded domain specific language for parallel analysis and visualization. In Proc. IEEE International Parallel & Distributed Processing Symposium, 2018.
 H. I. Ingolfsson, T. S. Carpenter, H. Bhatia, P.T. Bremer, S. J. Marrink, and F. C. Lightstone. Computational lipidomics of the neuronal plasma membrane. Biophysical Journal, 113(10):2271–2280, 2017.
 S. Liu, D. Maljovec, B. Wang, P.T. Bremer, and V. Pascucci. Visualizing highdimensional data: Advances in the past decade. IEEE Trans. Vis. Comp. Graph., 2017.
 S. Liu, P.T. Bremer, J. Thiagarajan, V. Srikumar, B. Wang, Y. Livnat, and V. Pascucci. Visual exploration of semantic relationships in neural word embeddings. IEEE Trans. Vis. Comp. Graph., 2017.
 W. Usher, P. Klacansky, F. Federer, P.T. Bremer, A. Knoll, A. Angelucci, and V. Pascucci. A virtual reality visualization tool for neuron tracing. IEEE Trans. Vis. Comp. Graph., 2017.
 M. Ong, H. Bhatia, A. Gyulassy, E. Draeger, V. Pascucci, P.T. Bremer, V. Lordi, and J. Pask. Complex ion dynamics in carbonate lithiumion battery electrolytes. Physiccal Chemeisty C, 121(12), 2017.
 A. Gimenez, T. Gamblin, I. Jusufi, A. Bhatele, M. Schulz, P.T. Bremer, and B. Hamann. Memaxes: Visualization and analytics for characterizing complex memory performance behaviors. IEEE Trans. Vis. Comp. Graph., 2017.
 R. Anirudh, B. Kailkhura, J. Thiagarajan, and P.T. Bremer. Poisson disk sampling on the grassmannnian: Applications in subspace optimization. In Proc. IEEE Computer Vision and Pattern Recognition Workshops (CVPRW), 2017.
 J. Miller, J. Thiagarajan, P.T. Bremer, N. Honda, D. Stern, and R. Mifflin. Datadriven metric learning for history matching. In Proc. SPE Reservoir Simulation Conference, 2017.
 J. Miller, J. Thiagarajan, P.T. Bremer, N. Honda, D. Stern, and R. Mifflin. Datadriven metric learning for history matching. Nov 2016.
 A. Landge, P.T. Bremer, A. Gyulassy, and V. Pascucci. Notes on the distributed computation of merge trees on cwcomplexes. In Topological Methods in Data Analysis and Visualization IV. Springer International Publishing, 2016.
 A. Gyulassy, A. Knoll, C. Kah, B. Lau, Wang, M. E. Bremer, L. A. Papka, V. Curtiss, and V. Pascucci. Morsesmale analysis of ion diffusion in ab initio battery materials simulations. In Topological Methods in Data Analysis and Visualization IV. Springer International Publishing, 2016.
 P.T. Bremer. Adapt – adaptive thresholds for feature extraction. In Topological Methods in Data Analysis and Visualization IV, Mathematics and Visualization. Springer International Publishing, 2016.
 B. Kailkhura, J. Thiagarajan, and P.T. Bremer. Stair blue noise sampling. ACM Trans. on Graph., 2016.
 D. Niu, P.T. Bremer, P. Lindstrom, B. Hamann, Y. Zhou, and C.Zhang. Twodimensional shape retrieval using the distribution of extrema of laplacian eigenfunctions. The Visual Computer, pages 1–18, 2016.
 S. Liu, P.T. Bremer, J. Thiagarajan, B. Wang, B. Summa, and V. Pascucci. Grassmannian atlas: A general framework for exploring linear projections of highdimensional data. Comput. Graph. Forum, 2016.
 P.T. Bremer, A. Gruber, J. Bennett, A. Gyulassy, H. Kolla, J. Chen, and R.W. Grout. Identifying turbulent structures through topological segmentation. Com. in App. Math. and Comp. Sci., 11(1):37–53, 2016.
 K. E. Isaacs, T. Gamblin, A. Bhatele, M. Schulz, B. Hamann, and P.T. Bremer. Ordering traces logically to identify lateness in message passing programs. IEEE Transactions on Parallel and Distributed Systems (TPDS), 27(3):829–840, 2016.
 W. Widanagamaachchi, Y. Livnat, P.T. Bremer, S. Duvall, and V. Pascucci. Interactive visualization and exploration of patient progression in a hospital setting‘. In Proc. Workshop on Visual Analytics in Healthcare, 2016.
 H. Nguyen, L. Wei, A. Bhatele, T. Gamblin, D. Boehme, M. Schulz, K.L. Ma, and P.T. Bremer. Vipact: A visualization interface for analyzing calling context trees. In Proc. Third Workshop on Visual Performance Analysis (VPA), 2016.
 W. Widanagamaachchi, A. Jacques, B. Wang, E. Crosman, P.T. Bremer, V. Pascucci, and J Horel. Exploring the evolution of pressureperturbations to understand atmospheric phenomena. In IEEE Pacific Visualization Symposium (PacificVis), 2017.
 D. Bohme, T. Gamblin, P.T. Bremer, O. Pearce, and M. Schulz. Generalpurpose performance introspection for hpc software stacks. In Proc. ACM/IEEE Conference on Supercomputing (SC16), 2016.
 H. Bhatia, A. G. Gyulassy, V. Pascucci, M. Bremer, M. T. Ong, V. Lordi, E. W. Draeger, J. E. Pask, and P.T. Bremer. Interactive exploration of atomic trajectories through relativeangle
 distribution and associated uncertainties. In 2016 IEEE Pacific Visualization Symposium (PacificVis), pages 120–127, 2016.
 I. Rodero, M. Parashar, A. G. Landge, S. Kumar, V. Pascucci, and P.T. Bremer. Evaluation of insitu analysis strategies at scale for power efficiency and scalability. In 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pages 156–164, 2016.
 C. Christensen, S. Liu, G. Scorzelli, J.W. Lee, P.T. Bremer, and V. Pascucci. Embedded domainspecific language and runtime system for progressive spatiotemporal data analysis and visualization. In Proc. IEEE Symposium LargeScale Data Analysis and Visualization, 2016.
 A. Bhatele, N. Jain, Y. Livnat, V. Pascucci, and P.T. Bremer. Analyzing network health and congestion in dragonflybased supercomputers. In Proc. IEEE International Parallel & Distributed Processing Symposium, 2016.
 B. Kailkhura, J. Thiagarajan, P.T. Bremer, and P. K. Varshney. Theoretical guarantees for poisson disk sampling using pair correlation function. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.
 B. Kailkhura, J. Thiagarajan, P.T. Bremer, and P. K. Varshney. Impact of spectral sampling techniques on surrogate modeling. In Proc. SIAM Conf. on Uncertainty Quantification, 2016.
 Q. Sun, M. Romanus, T. Jin, H. Yu, P.T. Bremer, S. Petruzza, S. Klasky, and M. Parashar. Instaging data placement for asynchronous coupling of taskbased scientific workflows. In 2016 Second International Workshop on Extreme Scale Programming Models and Middlewar (ESPM2), pages 2–9, Nov 2016.
 M. Schulz, A. Bhatele, D. Bohme, P.T. Bremer, T. Gamblin, A. Gimenez, and K. Isaacs. A Flexible Data Model to Support Multidomain Performance Analysis, pages 211–229. Springer International Publishing, 2015.
 A. Gyulassy, H. Bhatia, P.T. Bremer, and V. Pascucci. Computing accurate morsesmale complexes from gradient vector fields. In Janine Bennett, Fabien Vivodtzev, and Valerio Pascucci, editors, Topological and Statistical Methods for Complex Data, Mathematics and Visualization, pages 205–218. Springer Berlin Heidelberg, 2015.
 D. Maljovec, S. Liu, B. Wang, D. Mandelli, P.T. Bremer, V. Pascucci, and C. Smith. Analyzing simulationbased PRA data through traditional and topological clustering: A BWR station blackout case study. Reliability Engineering & System Safety, 2015.
 A. Gyulassy, A. Knoll, K. Lau, B. Wang, P. Bremer, M. Papka, L. Curtiss, and V. Pascucci. Interstitial and interlayer ion diffusion geometry extraction in graphitic nanosphere battery materials. IEEE Trans. Vis. Comp. Graph., PP(99):1–1, 2015.
 S. Liu, B. Wang, J. Thiagarajan, P.T. Bremer, and V. Pascucci. Visual exploration of highdimensional data through subspace analysis and dynamic projections. Comput. Graph. Forum, 2015.
 H. Bhatia, B. Wang, G. Norgard, V. Pascucci, and P.T. Bremer. Local, smooth, and consistent Jacobi set simplification. Computational Geometry, 48(4):311–332, 2015.
 P.T. Bremer, D. Maljovec, A. Saha, B. Wang, J. Gaffney, B. Spears, and V. Pascucci. Nddav: Ndimensional data analysis and visualization. Computing and Visualization in Science, 17(1):1–18, 2015.
 A. Bhatele, A. R. Titus, J. J. Thiagarajan, N. Jain, T. Gamblin, P.T. Bremer, M. Schulz, and L. V. Kale. Identifying the culprits behind network congestion. In Parallel and Distributed Processing Symposium (IPDPS), 2015 IEEE International, pages 113–122, May 2015.
 B. Husain, A. Gimenez, J. A. Levine, T. Gamblin, and P.T. Bremer. Relating memory performance data to application domain data using an integration api. In Proceedings of the 2nd Workshop on Visual Performance Analysis, VPA ’15, pages 5:1–5:8, 2015.
 H. Kim, J. Thiagarajan, and P.T. Bremer. A randomized ensemble approach to industrial ct segmentation. In Proc. ICCV 2015, 2015.
 W. Widanagamaachchi, P. Klacansky, H. Kolla, J. Chen, A. Bhagatwala, V. Pascucci, and P.T. Bremer. Tracking features in embedded surfaces: Understanding extinction in turbulent combustion. In Proc. IEEE Symposium LargeScale Data Analysis and Visualization, 2015.
 S. Liu, D. Maljovec, B. Wang, P.T. Bremer, and V. Pascucci. Visualizing HighDimensional Data: Advances in the Past Decade. In Proc. Eurographics Conference on Visualization (EuroVis)  STARs, 2015.
 K. Isaacs, A. Bhatele, J. Lifflander, D. Bohme, T. Gamblin, M. Schulz, B. Hamann, and P.T. Bremer. Recovering logical structure from charm++ event traces. In Proc. ACM/IEEE Conference on Supercomputing (SC15), 2015.
 S. Liu, D. Maljovec, B. Wang, P.T. Bremer, and V. Pascucci. Visualizing highdimensional data: Advances in the past decade. In Proc. Eurographics Conference on Visualizatoin (EuroVis 15) State of the Art Report. 2015.
 A. Bhatele, A. Titus, J. Thiagarajan, N. Jain, T. Gamblin, P.T. Bremer, M. Schulz, and L. Kale. Identifying the culprits behind network congestion. In Proc. IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2015.
 2018 LLNL Early MidCareer Recognition Award
 2018 DDS&T Excellence in Publication Award
 2014 VGTC GTC Visualization Contest
 2012 IEEE Symposium on Large Data Analysis and Visualization: Best paper award
 2011 IEEE Pacific Visualization Conference: Best paper award
 DOE OASCR Visualization Award: Annual SciDac Conference 2008, Seattle
 2006 IEEE Visualization Conference 2006: Best application paper award
 2002 Accepted into the Student Employee Graduate Research Fellowship program of the Lawrence Livermore National Laboratory
 1998 Award for Outstanding Academic Achievement