Events

• Where: Arellano Theater, Levering Hall
• When: February 14, 2018, 16:00
• Paul Reed Smith
• An IDIES Bi-Monthly Seminar

Click here to view a recording of the event. Abstract: I will review the history of the Precision Measuring Matrix including my father’s involvement, real time demonstrations, discussion of FFT measurement anomalies, the discovered language of EEG harmonic brainwaves, watching the harmonics of an acoustic guitar in real time and newly discovered domains made possible … Continued

• Where: Hackerman Hall B-17
• When: December 05, 2017, 10:30
• Ian Foster

Abstract A growing disparity between supercomputer computation speeds and I/O rates makes it increasingly infeasible for applications to save all results for offline analysis. Instead, applications must analyze and reduce data online so as to output only those results needed to answer target scientific question(s). This change in focus complicates application and experiment design and … Continued

• Where: Mudd Hall Auditorium
• When: October 20, 2017, 08:00

The Institute for Data Intensive Engineering and Science will hold our 2017 Annual Symposium at Johns Hopkins University on Friday, October 20, 2017. This event will bring together experts in Big Data from all divisions of Johns Hopkins University, the government and industry to share their discoveries, practical ideas, and insights. The focus is on … Continued

• Where: Hodson Hall, Rm 210
• When: October 04, 2017, 16:00
• S. Muthukrishnan, PhD, Rutgers University
• An IDIES Bi-Monthly Seminar

Please join us at 4:00 pm on Wednesday, Oct 4, 2017 for “Heavy Hitters on Data Streams and Recent Variants” by Dr. S Muthukrishnan, Distinguished Professor of Computer Science and ACM Fellow at Rutgers University. The talk will take place on Wednesday, October 4th, 2017, from 4:00 pm to 5:00 pm in Hodson Hall, Room … Continued

• Where: Bloomberg Building, Room 462
• When: September 21, 2017 to September 21, 2017, 13:30
• Alex Smola, PhD, Director of Machine Learning and Deep Learning at AWS

Unfortunately, registration has reached capacity for the “Tutorial on Deep Learning with Apache MXNet Gluon” by Dr. Alex Smola, Director of Machine Learning and Deep Learning at AWS, Carnegie Mellon University, Marianas Labs, CEO. If you really want to attend, and are curious if any seats have become available, you can email one of our … Continued

• Where: BSPH E2030 (Feinstone)
• When: May 15, 2017, 13:30
• Christina Leslie
• A Genomics@JHU Seminar

Abstract: Dysregulated epigenetic developmental programs are a feature of many cancers, and the diverse differentiation states of immune cells as well as their dysfunctional states in tumors are in part epigenetically encoded. We developed an integrative computational strategy to exploit genome-wide data on chromatin accessibility (DNase-seq or ATAC-seq), histone modifications (ChIP-seq), and transcription (RNA-seq) in … Continued

• Where: BSPH E3609 (Genome Café)
• When: May 01, 2017, 13:30
• Benjamin Haibe-Kains
• A Genomics@JHU Seminar

Abstract: The success of precision medicine largely relies on comprehensive characterization of patient tumors and their derived model systems to select the best therapy for each individual patient. Recent initiatives generated massive amounts of molecular data for healthy (GTEx) and tumor (TCGA) tissues from patients, as well as patient-derived cancer cell lines (Cancer Cell Line … Continued

• Where: Arellano Theater, Levering Hall
• When: April 13, 2017, 16:30
• Dr. Dean Evasius
• An IDIES Bi-Monthly Seminar

Abstract: Data science has emerged as a distinct discipline that has also become a power enabler of science and engineering. In its deep interactions with other disciplines it is an example of the scientific convergence, which is one of the Ten Big Ideas for Future NSF Investments. The rapid growth of data science raises deep … Continued

• Where: BSPH E3609 (Genome Café)
• When: April 03, 2017, 13:30
• Joe Pickrell
• A Genomics@JHU Seminar

Abstract: A primary goal of human genetics is to understand the genetic causes of phenotypic variation. Recent successes in genome-wide association studies have shown that achieving this goal requires collecting and analyzing data at scale. I will discuss projects that center around this thesis. First, I will discuss analyses of the genetics of lifespan in … Continued

• Where: Hodson Hall Board Room
• When: March 27, 2017 to March 27, 2017, 13:30
• Stéphane Mallat PhD

Distinguished CIS Seminar Reception directly following seminar. Abstract: Classification and regression require to approximate functions in high dimensional spaces. Avoiding the dimensionality curse opens many questions in statistics, probability, harmonic analysis and geometry. Convolutional deep neural networks can obtain spectacular results for image analysis, speech understanding, natural languages and many other problems. We shall review … Continued