Anirudh Ramanathan

As an early engineer on the Kubernetes and Google container engine team, I donned several hats - adding core functionality to Kubernetes , helping scale open source development, improving both internal and external processes, onboarding the SRE organization and eventually leading development on Big Data and Machine Learning applications in Kubernetes.

• Critical role in graduating StatefulSets to beta - Statefulsets are an important Kubernetes construct that allow running stateful applications on containers.
• Started and grew Spark on Kubernetes to a multi-organization effort and and eventually graduated into the Apache Spark project.
• Led the SIG Big Data community to contributors from several organizations, helping create an ecosystem of Spark, Airflow, Tensorflow, Jupyter and HDFS on Kubernetes.
• Scaled the Kubernetes project to contributions from a host of other organizations, rewrote Github automation, CLA infrastructure, etc.
• Was instrumental in creating and improving processes and for testing and releases, and led releases in open source as well as internally.
• Onboarded, mentored and led a two-person focus group on various data science and ML projects.
• Invited speaker at several conferences & meetups.

Worked on Google Global Cache, the worldwide Content Delivery Network (CDN).

• Worked on the mapping optimizer, responsible for assignment of geo-distributed edge caches to incoming connections.
• Evaluated several SDN controlled content delivery algorithms against measures of latency and goodput on a global scale for Youtube.
• Implemented proposed improvements to realize tangible improvements to mean global latency for Youtube content.

Multiple Selections with Touchscreen Devices

• Carried out research on common UI interactions and their semantics with touch screen interfaces
• Developed an early prototype Android GUI library implementing the formalism, allowing a better and faster way to carry out multiple selections.
• Published work in NIK 2016.

• Course Grader for CSCE-222 Discrete Structures for Computing
• Led a Scrum team of students to develop a website and content management system for the political science department at Texas A&M University.
• Developed the frontend and web-backend for a supply chain simulation game intended for use in classrooms and later between different universities.

• Implemented automation and tooling for NVIDIA's compute clusters used for hardware design and simulations.
• Improved core scheduling and resource allocation algorithms.
• Developed and maintained metrics and monitoring pipelines for clusters.
• Created tools to track resource planning, forecasting and utilization metrics and scaled it across all GPU and Mobile SoC projects.

• Created a real-time GPS tracking system for law enforcement and an integrated communication system for the control room Developed the server application using ASP.NET/C#.
• Implemented an interactive web UI for tracking GPS devices using the Google Maps & Earth APIs.
• Built an NMEA sentence parser and a simulator to test our spatial error correction algorithms.
• Forked and modified an open source Java SIP client to build an integrated communication system over our own VOIP telephony system.

GPA: 4.0 

Graduated with First Class Honors

• Volunteer teacher as part of the TEALS program in association with Microsoft.
• Teaching basics of CS to middle school students.