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Alex Aiken

Alex Aiken has 4 papers in our library, in 2018–2025, most of them on Reasoning, GPU & parallel computing; often with Matei Zaharia, Oded Padon, Zhihao Jia.

4 papers in our library · 2018–2025

OpenAlex · ORCID · Wikidata · h-index 75 · 382 works · 20,331 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 364 times in our library · 7 more in our library without a page yet · ⭐ Paper Stars ranking: #4477

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Stanford UniversityStanford · United States2004–2026 · 265 papersEmployment · Professor, Computer Sciencecurrent🔬SLAC National Accelerator LaboratoryMenlo Park · United States2018–2026 · 7 paperscurrent🎓University of California, BerkeleyBerkeley · United States1994–2007 · 74 papers🔬IBM Research - AlmadenSan Jose · United States1990–2006 · 11 papers🎓Cornell UniversityIthaca · United States1986–1995 · 9 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksInformation Systems · 3 worksComputer Vision and Pattern Recognition · 1 workHardware and Architecture · 1 workComputer Science Applications · 1 workSoftware · 1 workArts and Humanities · 1 workArtificial Intelligence · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.GPU & parallel computing · 1 workReasoning · 1 work

 Works by year

2020s

20251 paper

2010s

20192 papers20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Beyond Data and Model Parallelism for Deep Neural Networks (2018 · 280 citations)
    Training large DNNs is now routinely spread across many GPUs, yet mainstream frameworks mostly rely on plain data parallelism or model parallelism.
  2. SPoC: Search-based Pseudocode to Code (2019 · 96 citations)
    SPoC addresses the generation of complete, multi-line C++ programs (roughly 10–20 lines) from line-by-line natural-language pseudocode.
  3. TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions (2019 · 72 citations)
    Deep learning frameworks such as TensorFlow, PyTorch, TensorRT and TVM speed up computation graphs by rewriting subgraphs into faster equivalent forms.
  4. EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking (2025 · 8 citations)
    EquiBench asks whether large language models actually grasp what code does or mostly react to how it looks.

All works

11 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Beyond Data and Model Parallelism for Deep Neural NetworksSysML 2019Zhihao Jia, Matei Zaharia, Alex Aiken2018 · 280 citations
  2. Automatic Generation of Peephole Superoptimizers ↗ASPLOS 2006 · no summary yetSorav Bansal, Alex Aiken2006 · 180 citations
  3. Statistical debugging ↗International Conference on Machine Learning · no summary yetAlice X. Zheng et al.2006 · 149 citations
  4. A Data Driven Approach for Algebraic Loop Invariants ↗Lecture notes in computer science · no summary yetRahul R. Sharma et al.2013 · 138 citations
  5. SPoC: Search-based Pseudocode to CodearXiv:1906.04908Sumith Kulal, Panupong Pasupat, Kartik Chandra, et al.2019 · 96 citations
  6. Data-Driven Equivalence Checking ↗OOPSLA 2013 · no summary yetRahul Sharma et al.2013 · 87 citations
  7. TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph SubstitutionsSOSP 2019Zhihao Jia, Oded Padon, James Thomas, et al.2019 · 72 citations
  8. Stochastic Superoptimization ↗arXiv:1211.0557 · no summary yetEric Schkufza, Rahul Sharma, Alex Aiken2012 · 31 citations
  9. Redundancy-Free Computation Graphs for Graph Neural Networks ↗arXiv (Cornell University) · no summary yetZhihao Jia et al.2019 · 9 citations
  10. EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence CheckingConference on Empirical Methods in Natural Language Processing (EMNLP)Anjiang Wei, Jiannan Cao, Ran Li, et al.2025 · 8 citations
  11. Synthesizing Program Input Grammars ↗arXiv:1608.01723 · no summary yetOsbert Bastani et al.2016 · 2 citations

 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 364 times (of the 149,439 papers whose bibliographies we read); 40 citing papers with a page here →.

Updated

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