Alex Weaver

Georgetown University
aweaver@cs.georgetown.edu

Resume

Research Interests

The focus of my research is the study of distributed algorithms for peer-to-peer wireless networks. Assisted by my advisors, Cal Newport and Nitin Vaidya, I design and analyze algorithms for a variety of communication and computation problems. I'm particularly interested in smartphone peer-to-peer networks and bridging the gap between existing distributed systems theory and mobile wireless technologies.


Publications

Michael Dinitz, Magnus M. Halldorsson, Calvin Newport and Alex Weaver. "The Capacity of Smartphone Peer-to-Peer Networks." 2019 33rd International Symposium on Distributed Computing (DISC), 2019.

Calvin Newport and Alex Weaver. "Random Gossip Processes in Smartphone Peer-to-Peer Networks." 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), 2019.


Professional Experience

Data Analyst

GEICO
2016 - 2017

Conducting data source research, data cleaning, and data transformation to support the development of the GEICO Data and Decision Sciences Team's predictive models. Producing analytical reports, summaries, and metrics for the team and executive stakeholders using Python, R, SQL, SPSS, Hadoop, Hive, and Spark.

Programmer Analyst III

GEICO
2015 - 2016

Expanding the GEICO sales application through front and back end enhancements to the auto quote workflow user experience. Working as part of larger effort to reimplement legacy applications and features written in Java using the .NET framework.

Programmer Analyst II

GEICO
2014 - 2015

Worked with GEICO static team to support geico.com and careers.geico.com, main contribution was to the content management system application that was shared by these two properties that facilitated the creation, management, and publication of web content.

Assistant Programmer

University of Virginia Center for Diabetes Technology
2013

Contributed to the development of an Android application to intelligently predict insulin and glucagon levels based off current measurements of diabetic patients and provide appropriate treatment through personally-calculated insulin injections.

Programming Intern

Commonwealth Computer Research, Inc. (CCRi)
2012

Contributed to the development of an Android application to form a content-based network for the timely delivery of relevant information for military units conducting ground operations. Project involved machine learning and data mining techniques to prioritize incoming documents and pre-fetch content to increase network responsiveness and efficiency.