ePlus inc. announced that it will be hosting a panel and exhibiting at the Biological Data Science Meeting at Cold Spring Harbor Laboratory in Cold Spring Harbor, NY being held November 7-10, 2018. The meeting will focus on the infrastructure, software, and algorithms needed to analyze large data sets in biological research. Researchers in attendance will discuss topics covering genomics to imaging with attention to data mining techniques that address the exploding volumes of information being collected for their projects.
ePlus, along with partners NVIDIA and NetApp, will be hosting a panel discussion to explore Deep Learning in Biology on November 9th at 12:00 pm. During the panel, members from two organizations will discuss how they currently utilize Graphics Processing Units (GPUs) and Deep Learning in their research that provide content in a more accurate and faster method than via Central Processing Units (CPUs).
- Barbara Engelhardt of Princeton University and Anna Goldenberg of University of Toronto will be joining the lunchtime panel, and Michael Schatz of Johns Hopkins/CSHL will moderate.
- Zeki Yasar and Ken Puffer of ePlus will also bring their technical and business expertise and perspective around the importance of Deep Learning in the healthcare space.
- Some of the organizations that will be in attendance include Harvard, Stanford, UPenn, Johns Hopkins, and the National Institutes of Health. Most attendees will be professors, post-doctoral fellows, and graduate students.
“ePlus is excited to participate at this biological data science event as we explore groundbreaking technology in the Artificial Intelligence space,” said Zeki Yasar, emerging technology director at ePlus. “The application of Deep Learning algorithms is changing the way researchers tackle complicated problems and see structure in data that was once impossible for the human brain to comprehend. Applying this technology to the study of the human genome and biological science will improve outcomes related to precision medicine. Our team brings their experience and expertise in use-case development, data science consulting, and implementing relevant technologies to help our customers address their Deep Learning initiatives.”