Amir Shaikhha

Amir Shaikhha

Assistant Professor

Short Bio

Amir is an Assistant Professor (Lecturer) in the School of Informatics at the University of Edinburgh. His research focuses on the design and implementation of data-analytics systems by using techniques from the databases, programming languages, compilers, and machine learning communities. Prior to that, he was a Departmental Lecturer at Oxford. He earned his Ph.D. from EPFL in 2018, for which he was awarded a Google Ph.D. Fellowship in structured data analysis, as well as a Ph.D. thesis distinction award. He has won the Best Paper Award at GPCE 2017 and the Most Reproducible Paper Award at SIGMOD 2017. He (co-)chaired the program committees of DBPL 2021, Scala 2022, and GPCE 2023.

Positions

If you are interested in a Ph.D. position at the intersection of compilers, databases, and machine learning, please contact me: firstname [dot] lastname [at] ed [another_dot] ac [yet_another_dot] uk

Recent News

  • June 2023. The demonstration for OpenDBML accepted to appear at VLDB 2023.
  • May 2023. I was selected for a Best Reviewer Award in SIGMOD 2023.
  • April 2023. The demonstration for SDQL.py accepted to appear at SIGMOD 2023.
  • March 2023. I will serve as the PC Chair of GPCE 2023; consider submitting a paper.
  • February 2023. Our work on combining prefetching with vectorization for hash tables accepted to appear at ECOOP 2023.
  • January 2023. I will be co-chairing DRAGSTERS’23. Consider submitting a paper.
  • December 2022. Two papers accepted in CC 2023: BayesTensor and SDQL.py.
  • November 2022. Our work on using machine learning for data structure selection accepted to appear at CGO 2023.
  • October 2022. Our work on Deep Loop Fusion accepted to appear at GPCE 2022.
  • August 2022. STOREL for tensor processing on flexible storage accepted to SIGMOD 2023.

Publications

  • Demonstration of OpenDBML, a Framework for Democratizing In-Database Machine Learning; M. Ghorbani, A. Shaikhha, to appear in VLDB’23 (demo).
  • Compiling Discrete Probabilistic Programs for Vectorized Exact Inference; J. Pan, A. Shaikhha, CC’23.
  • Building a Compiled Query Engine in Python; H. Shahrokhi, A. Shaikhha, CC’23.
  • An Efficient Vectorized Hash Table for Batch Computations; H. Shahrokhi, A. Shaikhha, ECOOP’23.
  • Fine-Tuning Data Structures for Query Processing; A. Shaikhha, M. Kelepeshis, M. Ghorbani, CGO’23.
  • Efficient Query Processing in Python Using Compilation; H. Shahrokhi, A. Shaikhha, SIGMOD’23 (demo).
  • Optimizing Tensor Programs on Flexible Storage; M. Schleich, A. Shaikhha, D. Suciu, SIGMOD’23.
  • Functional Collection Programming with Semi-ring Dictionaries; A. Shaikhha, M. Huot, J. Smith, D. Olteanu, OOPSLA’22.
  • Hinted Dictionaries: Efficient Functional Ordered Sets and Maps; A. Shaikhha, M. Ghorbani, H. Shahrokhi, ECOOP’22.
  • Deep Fusion for Efficient Nested Recursive Computations; A. Shaikhha, GPCE’22.
  • An Intermediate Representation for Hybrid Database and Machine Learning Workloads; A. Shaikhha, M. Schleich, D. Olteanu, VLDB’21 (Demo).
  • Scalable Querying of Nested Data; J. Smith, M. Benedikt, M. Nikolic, A. Shaikhha, VLDB’21.
  • Multi-Stage Programming in the Large with Staged Classes; L. Parreaux, A. Shaikhha, GPCE’20.
  • Synthesis of Incremental Linear Algebra Programs; A. Shaikhha, M. El Seidy, D. Espino, S. Mihaila, C. Koch, TODS’20.
  • Multi-Layer Optimizations for End-to-End Data Analytics; A. Shaikhha, M. Schleich, A. Ghita, D. Olteanu, CGO’20.
  • BayesCard: Revitilizing Bayesian Frameworks for Cardinality Estimation; Z. Wu, A. Shaikhha, Rong Zhu, Kai Zeng, Yuxing Han, Jingren Zhou, CoRR’20.
  • Compiler Generation for Performance-Oriented Embedded DSLs; A. Shaikhha, V. Jovanovic, C. Koch, GPCE’19 (Short Paper).
  • Polymorphic Extractors for Semantic and Portable Pattern Matching; A. Shaikhha, GPCE’19 (Short Paper).
  • Efficient Differentiable Programming in a Functional Array-Processing Language; A. Shaikhha, A. Fitzgibbon, S. Peyton-Jones, D. Vytiniotis, ICFP’19.
  • Finally, a Polymorphic Linear Algebra Language; A. Shaikhha, L. Parreaux, ECOOP’19.
  • Building Efficient Query Engines in a High-Level Language; A. Shaikhha, Y. Klonatos, C. Koch, TODS’18.
  • Push vs. Pull-Based Loop Fusion in Query Engines; A. Shaikhha, M. Dashti, C. Koch, JFP’18.
  • Unifying Analytic and Statically-Typed Quasiquotes; L. Parreaux, A. Voizard, A. Shaikhha, and C. Koch, POPL’18.
  • Quoted Staged Rewriting: a Practical Approach to Library-Defined Optimizations; L. Parreaux, A. Shaikhha, and C. Koch, GPCE’17 (Best Paper Award).
  • Repairing Transaction Conflicts in Optimistic Multi-Version Concurrency Control; M. Dashti, S. John, A. Shaikhha, C. Koch, SIGMOD’17 (Most Reproducible Paper Award).
  • How to Architect a Query Compiler; A. Shaikhha, Y. Klonatos, L. Parreaux, L. Brown, M. Dashti, C. Koch, SIGMOD’16.
  • Yin-Yang: Concealing the Deep Embedding of DSLs; V. Jovanovic, A. Shaikhha, S. Stucki, V. Nikolaev, C. Koch, M. Odersky, GPCE’14.
  • DBToaster: Higher-order Delta Processing for Dynamic, Frequently Fresh Views; C. Koch, Y. Ahmad, O. Kennedy, M. Nikolic, A. Noetzli, D. Lupei, A. Shaikhha, VLDBJ’14.

Awards

  • Best Reviewer Award, SIGMOD 2023.
  • Nominated for Best Supervisor of the Year, University of Edinburgh, 2022.
  • Ph.D. Thesis Distinction Award, EPFL, 2018.
  • Service Award, IC EPFL, 2018.
  • Best Paper Award, GPCE 2017.
  • Most Reproducible Paper Award, SIGMOD 2017.
  • Google Ph.D. Fellowship, 2017.
  • Teaching Assistant Award, IC EPFL, 2016.

Services

  • Chairing: GPCE’23 (PC Chair), DRAGSTERS’23 (Co-Chair), Scala’22 (PC Chair), DBPL’21 (Co-Chair).
  • Organization: CGO’24 (Finance Chair), VLDB’23 (PC), SIGMOD’23 (PC), GPCE’22 (PC), TFP’22 (PC), DBAI’21 (PC), BICOD’21 (PC), ASPLOS’20 (ERC), DBPL’19 (PC).
  • Reviewer: TODS 2023, TODS 2021, VLDBJ 2020, TODS 2018.
  • PhD Students’ Representative: IC EPFL, 2017-2018.
  • Member of EPIC PhD Student Association: IC EPFL, 2017.