Bhuvan Urgaonkar, PhD
, has over 15 years of experience in the field of Software Engineering and Computers
. His work includes research in computer systems software, distributed computing (including systems such as Zookeeper, Redis, Memcached, Cassandra, Kafka), datacenters, cloud computing, storage systems, energy efficiency of computers and datacenters, big data (including systems such as Hadoop, Spark).
Dr. Urgaonkar has published over 80 research papers in competitive peer-reviewed conferences and journals on these topics with several best paper awards. He has procured research funding totaling more than $3 Million USD from federal agencies and industrial labs (Google, HP, IBM, Cisco, Microsoft, Amazon) to lead and train several Phd and MS students who now work in industry and academia. Dr. Urgaonkar has also delivered lectures on topics including Cloud Computing and Data Centers
to Faculty at Microsoft and numerous other technology companies and universities around the world.
Education / Training
: Ph.D. in Computer Science from the University of Massachusetts Amherst (2005) B.Tech (honors) in Computer Science and Engineering from the Indian Institute of Technology, Kharagpur, India
Awards / Honors
: Test of Time Award, ACM Sigmetrics 2016 National Science Foundation Career award, 2010 IBM Faculty Fellowships, 2016, 2014 Several best paper awards (see CV)
- Dr. Urgaonkar serves as an expert / technical consultant with multiple firms helping them (i) understand technical content related to state of the art products in areas such as content distribution, distributed computing, datacenter design, among others and (ii) interpret patents in these areas and connections between them and state of the art products and services. Services are available to law firms, government agencies, schools, firms / corporations, and hospitals. They include case review, deposition, and trial testimony as needed.
Areas of Expertise
- Software Design and Analysis
- Computer Systems
- Operating Systems
- File Systems
- Computer Security
- Distributed Computing
- Data Centers
- Cloud Computing
- Big Data Systems
|InternetContent Distribution NetworksSoftware Reliability and TestingFault ToleranceHadoopSparkKubernetesLinuxAWSAzureMachine LearningScheduling|