Aashaka Shah

Dept. of Computer Science [email protected] University of Texas at Austin https://aashaka.github.io Education

University of Texas at Austin 2018 (ongoing) Ph.D. in Computer Science Advisor: Prof. Vijay Chidambaram Indian Roorkee 2014-2018 B.Tech in Computer Science and Engineering CGPA: 9.337/10 Areas of Interest

Systems for machine learning, distributed systems, storage systems Research Experience

Jan - Sept 2019 Scalable and Efficient Data Authentication for Decentralized Systems On Arxiv UT Austin We design a distributed authenticated data structure which tackles bottlenecks due to random I/O operations, serialization, and hashing. Using this data structure, we build an Ethereum-like blockchain which achieves a high transaction throughput.

Aug - Oct 2018 Analyzing Impact of Data Regulation Compliance on Storage Systems HotStorage’19 UT Austin We analyze the properties a storage system should have to efficiently comply with the General Data Protection Regulation (GDPR). We modify and benchmark the Redis key-value store to incorporate major GDPR-compliant properties by adding strict monitoring, encryption, and deletion mechanisms.

Jan - May 2017 Empowering Light Nodes in Blockchains with Block Summarization NTMS’18 IIT Roorkee We introduce a hierarchical block summarization approach for transferable transactions in blockchain This allows resource-restricted light nodes to store a modified form of the blockchain, enabling them to validate transactions independently and reducing their dependence on full nodes. Ongoing Work

UT Austin Resource of GPUs in context of ML applications The aim is to efficiently use resources while improving performance of machine learning training and inference tasks. Work Experience

May - Aug 2019 Succinct verifiable computation and zk proofs Research Mentor: Satya Lokam Adapted the GKR zero knowledge protocol for multiple ephemeral sources and a resource-constraint verifier. Also augmented Hyrax, a popular verifiable computation framework, with support for exogenous compute instructions to enable a broader range of verifiable computation. Identified useful use-cases of these models in parameter servers and cryptographic signatures respectively.

May - July 2017 User-side noisy-neighbour handling for Apache Spark applications Adobe Research Mentor: Subrata Mitra India Detected and mitigated noisy-neighbour problem in shared environment with high accuracy. Cre- ated an ML model using select performance variables after understanding Spark internals.

May - June 2016 Model organization of die-stacked DRAM cache for Big Data applications IIT Madras Mentor: Prof. Madhu Mutyam Studied block prefetching techniques and used them to model a DRAM cache with non-uniform block sizes. Also attended a 10-day High Performance Computing Architecture Summer School. Publications

[1] Soujanya Ponnapalli, Aashaka Shah, Amy Tai, Souvik Banerjee, Vijay Chidambaram, Dahlia Malkhi, and Michael Wei. Scalable and efficient data authentication for decentralized systems, 2019. [2] Aashaka Shah, Vinay Banakar, Supreeth Shastri, Melissa Wasserman, and Vijay Chidambaram. Analyzing the impact of GDPR on storage systems. In 11th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 19), Renton, WA, 2019. USENIX Association. [3] Asutosh Palai, Meet Vora, and Aashaka Shah. Empowering light nodes in blockchains with block summarization. In 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), pages 1–5, Feb 2018. [4] Tenant-side detection, classification, and mitigation of noisy-neighbor-induced performance degradation. In USPTO, patent filed on behalf of Adobe Research, 2018. Teaching Experience

• CS378H: Concurrency: Honors Teaching Assistant (UT Austin, Fall 2018) • CSN-106: Discrete Structures Teaching Assistant (IIT Roorkee, Spring 2017) Scholarships and Awards

• Awarded a grant to attend SOSP 2019, CRA-W Grad Cohort 2019, GHCI 2016 • Overall best intern project award at Adobe Research, 2017, given to 2 out of 23 teams • Women Techmakers Scholarship, Asia Pacific Region, 2017 • Adobe India Women in Technology Scholarship, 2017 • IIT Roorkee Heritage Excellence Award, 2015, 2017, for outstanding academic, co-curricular and extra-curricular achievements • IIT Roorkee institute winner, Microsoft Code.Fun.Do 24hr hackathon, 2016 • JEE Advanced All India Rank 556 from more than 1.5lakh takers, 2014 Other Activities

• Co-organized LASR systems seminar at UT Austin for Fall 2018 • Participated in SRISTI UNICEF Summer School on Inclusive Innovation, 2018 • Editor-in-Chief, Geek Gazette, 2016-17: Headed discussions, ideas and writing for technical magazine with 4000+ readers • Convener, Inter Hostel Technical Trophy, 2017: Managed event planning, marketing, budget distribution and execution of 8 events spread over 3 weeks with 100+ participants • Team member, IIT Roorkee Badminton team: Won silver in Institute Colors Trophy, 2017 • Presented ”Empowering Light Nodes in Blockchain with Block Summarization” at the India-Japan Workshop on Cryptographic Techniques for Cyber Security, IIT Roorkee (February, 2017) • Attended a 10-day High Performance Computing Architecture Summer School at IIT Madras, 2016 • Gave introductory talks on HTML (1￿00student attendees) in 2015, Careers in CS (4￿0student attendees) in 2018 at IIT Roorkee