Rajiv Nishtala

- Designed and implemented accurate power and performance models on multicore architectures using hardware counters. - Designed and implemented a hybrid reinforcement learning approach to maintain performance guarantees for latency-critical applications such as bank transactions or web requests. - Experience in working with large scale dataset such as Memcached and ElasticSearch with Faban. - Publish/Present relevant results in top-level journals and conferences in these research areas.

- Organised courses on C# - Delivered presentations at the Microsoft Student Technology Conference.

- I built scripts to process and analyze how long each cancer genome takes to process - Statistical calculation of various jobs and optimizing servers on Groovy and Grails.

Design and develop a Molcad server/client using NodeJS and AJAX. This approach is based on the Molcad server as the core of the interaction for the server. The interaction between client and server is done using XMLHttpRequest

Computer Architecture, Power modelling, Performance modelling, Reinforcement learning, data centers.

- Designed and implemented an energy efficient scheduler as a part of my masters studies in Germany. - Thesis: Energy-aware thread co-location in heterogeneous multicore processors - The work carried out the UPitt, gained me the best master thesis award

Thesis: Energy efficient Thread Co-Scheduling in Heterogeneous Multicore Systems (Master thesis award)

Cumulative GPA: 7.42/10.00; (Top grade: 10.00)