Eugen Feller, PhD
Principal Software Engineer

Verizon Labs
499 Hamilton Ave, Palo Alto, CA-94301, USA

Email: eugen (dot) feller (at) verizon.com

http://www.linkedin.com/in/eugenfeller

News

  • Joined Verizon Labs Excited to be joining the team at Verizon Labs!
    Posted Apr 18, 2016, 6:33 PM by Eugen Feller
  • Area chair at IEEE CLOUD 2016 Consider submitting your papers to IEEE CLOUD 2016 (http://www.thecloudcomputing.org/2016/)
    Posted Mar 1, 2016, 4:30 PM by Eugen Feller
  • Paper accepted at IEEE CLOUD 2015 Joint work with my CMU and Ericsson colleagues on services rebalancing in clouds accepted at IEEE CLOUD 2015 applications track!
    Posted May 13, 2015, 11:21 AM by Eugen Feller
Showing posts 1 - 3 of 16. View more »

About

I am a Principal Software Engineer at Verizon Labs. Prior to that, I was a Senior Research Engineer at Ericsson Silicon Valley Lab. I did a postdoc in the Integrated Data Frameworks Group of the Data Science and Technology Department at the Lawrence Berkeley National Lab (LBNL). I received my PhD with highest honors in Computer Science from the University of Rennes 1, France (2012) under the supervision of Dr. Christine Morin. During the PhD I was a member of the Myriads INRIA project-team. I obtained Bachelor and Master of Science degrees in Computer Science from Heinrich Heine University Düsseldorf (HHU), Germany in 2008 (resp. 2009). I was a student research assistant at the HHU, interned in the Myriads INRIA project-team and was a summer intern at LBNL.

Interests

Currently, I focus on the design and implementation of big data management systems and algorithms. I am also interested in performance analysis and evaluation, automated storage provisioning, data placement strategies, and life-cycle management of applications in cloud computing environments. Overall my current research and development activities are centered around the following areas:
  • Large-scale dynamic distributed systems
  • Cloud computing, Real-time big data analytics
  • Virtualization, Energy-efficient resource management
  • Scalabiltiy, Fault tolerance, High availability
  • Performance analysis and evaluation