• PandasBench: A Benchmark for the Pandas API
  Alex Broihier*, Stefanos Baziotis*, Daniel Kang, Charith Mendis
    Paper   Github   BibTex

  @misc{broihier2025pandasbenchbenchmarkpandasapi,
    title={PandasBench: A Benchmark for the Pandas API}, 
    author={Alex Broihier and Stefanos Baziotis and Daniel Kang and Charith Mendis},
    year={2025},
    eprint={2506.02345},
    archivePrefix={arXiv},
    primaryClass={cs.DB},
    url={https://arxiv.org/abs/2506.02345}, 
  }
  

  
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• PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees
  Yuxuan Zhu*, Tengjun Jin*, Stefanos Baziotis, Chengsong Zhang, Charith Mendis, Daniel Kang
  SIGMOD 2025
    Paper   Github   BibTex

  @article{10.1145/3725335,
    author = {Zhu, Yuxuan and Jin, Tengjun and Baziotis, Stefanos and Zhang, Chengsong and Mendis, Charith and Kang, Daniel},
    title = {PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees},
    year = {2025},
    issue_date = {June 2025},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    volume = {3},
    number = {3},
    url = {https://doi.org/10.1145/3725335},
    doi = {10.1145/3725335},
    abstract = {After decades of research in approximate query processing (AQP), its adoption in the industry remains limited. Existing methods struggle to simultaneously provide user-specified error guarantees, eliminate maintenance overheads, and avoid modifications to database management systems. To address these challenges, we introduce two novel techniques, TAQA and BSAP. TAQA is a two-stage online AQP algorithm that achieves all three properties for arbitrary queries. However, it can be slower than exact queries if we use standard row-level sampling. BSAP resolves this by enabling block-level sampling with statistical guarantees in TAQA. We implement TAQA and BSAP in a prototype middleware system, PilotDB, that is compatible with all DBMSs supporting efficient block-level sampling. We evaluate PilotDB on PostgreSQL, SQL Server, and DuckDB over real-world benchmarks, demonstrating up to 126X speedups when running with a 5\% guaranteed error.},
    journal = {Proc. ACM Manag. Data},
    month = jun,
    articleno = {198},
    numpages = {28},
    keywords = {approximate query processing, sampling}
    }
  

  
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• Dias: Dynamic Rewriting of Pandas Code
  Stefanos Baziotis, Daniel Kang, Charith Mendis
  SIGMOD 2024, Honorable Mention for Best Artifact Award
    Paper   Github   BibTex

  @article{dias,
    author = {Baziotis, Stefanos and Kang, Daniel and Mendis, Charith},
    title = {Dias: Dynamic Rewriting of Pandas Code},
    year = {2024},
    issue_date = {February 2024},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    volume = {2},
    number = {1},
    url = {https://doi.org/10.1145/3639313},
    doi = {10.1145/3639313},
    abstract = {In recent years, dataframe libraries, such as pandas have exploded in popularity. Due to their flexibility, they are increasingly used in ad-hoc exploratory data analysis (EDA) workloads. These workloads are diverse, including custom functions which can span libraries or be written in pure Python. The majority of systems available to accelerate EDA workloads focus on bulk-parallel workloads, which contain vastly different computational patterns, typically within a single library. As a result, they can introduce excessive overheads for ad-hoc EDA workloads due to their expensive optimization techniques. Instead, we identify source-to-source, external program rewriting as a lightweight technique which can optimize across representations, and offer substantial speedups while also avoiding slowdowns. We implemented Dias, which rewrites notebook cells to be more efficient for ad-hoc EDA workloads. We develop techniques for efficient rewrites in Dias, including checking the preconditions under which rewrites are correct, dynamically, at fine-grained program points. We show that Dias can rewrite individual cells to be 57\texttimes{} faster compared to pandas and 1909\texttimes{} faster compared to optimized systems such as modin. Furthermore, Dias can accelerate whole notebooks by up to 3.6\texttimes{} compared to pandas and 27.1\texttimes{} compared to modin.},
    journal = {Proc. ACM Manag. Data},
    month = {mar},
    articleno = {58},
    numpages = {27},
    keywords = {cross-representation, dynamic, pandas, rewriting}
    }
  

  
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• Hydride: A Retargetable and Extensible Synthesis-based Compiler for Modern Hardware Architectures
  Kothari, Akash, Abdul Rafae Noor, Muchen Xu, Hassam Uddin, Dhruv Baronia, Stefanos Baziotis, Vikram Adve, Charith Mendis, and Sudipta Sengupta.
  ASPLOS 2024
    Paper   BibTex

  @inproceedings{hydride,
    author = {Kothari, Akash and Noor, Abdul Rafae and Xu, Muchen and Uddin, Hassam and Baronia, Dhruv and Baziotis, Stefanos and Adve, Vikram and Mendis, Charith and Sengupta, Sudipta},
    title = {Hydride: A Retargetable and Extensible Synthesis-based Compiler for Modern Hardware Architectures},
    year = {2024},
    isbn = {9798400703850},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3620665.3640385},
    doi = {10.1145/3620665.3640385},
    abstract = {As modern hardware architectures evolve to support increasingly diverse, complex instruction sets for meeting the performance demands of modern workloads in image processing, deep learning, etc., it has become ever more crucial for compilers to provide robust support for evolution of their internal abstractions and retargetable code generation support to keep pace with emerging instruction sets. We propose Hydride, a novel approach to compiling for complex, emerging hardware architectures. Hydride uses vendor-defined pseudocode specifications of multiple hardware ISAs to automatically design retargetable instructions for AutoLLVM IR, an extensible compiler IR which consists of (formally defined) language-independent and target-independent LLVM IR instructions to compile to those ISAs, and automatically generated instruction selection passes to lower AutoLLVM IR to each of the specified hardware ISAs. Hydride also includes a code synthesizer that automatically generates code generation support for schedule-based languages, such as Halide, to optimally generate AutoLLVM IR. Our results show that Hydride is able to represent 3,557 instructions combined in x86, Hexagon, ARM architectures using only 397 AutoLLVM IR instructions, including (Intel) SSE2, SSE4, AVX, AVX2, AVX512, (Qualcomm) Hexagon HVX, and (ARM) NEON vector ISAs. We created a new Halide compiler with Hydride using only a formal semantics of Halide IR, leveraging the auto-generated AutoLLVM IR and back-ends for the three hardware architectures. Across kernels from deep learning and image processing, this compiler is able to perform just as well as the mature, production Halide compiler on Hexagon, and outperform on x86 by 8\% and ARM by 3\%. Hydride also outperforms the production Halide's LLVM back end by 12\% on x86, 100\% on HVX, and 26\% on ARM across the same kernels.},
    booktitle = {Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2},
    pages = {514–529},
    numpages = {16},
    location = {La Jolla, CA, USA},
    series = {ASPLOS '24}
    }
  

  
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• Designing Decoupled Compiler Transformation APIs
  B.Sc. Thesis
  National and Kapodistrian University of Athens, 2021
    PDF   BibTex

  @BACHELORSTHESIS{Moll:2011:BSc,
      author = { Stefanos Baziotis },
      title = { {D}esigning {D}ecoupled {C}ompiler {T}ransformation {API}s },
      school = {National and Kapodistrian University of Athens, Department of Informatics},
      year = { 2021 },
      month = { July },
      webpdf  = {https://pergamos.lib.uoa.gr/uoa/dl/frontend/file/lib/default/data/2958380/theFile},
  }
  

  
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I'm the host of the In the Midst of Philosophy podcast (also on Youtube), whose goal is to bring important figures from the fields of Philosophy, Technology, and Science, onto the foreground of public awareness.

• Episodes
  • /* Apr 02, 2025 */ #1 - William J. Rapaport: Philosophy of Computer Science
  • /* Jun 16, 2025 */ #2 - Federica Frabetti: The Deconstruction of Software Engineering
  • /* May 20, 2026 */ #3 - George Contogeorgis: Democracy as Freedom
  • /* Upcoming ... */ Sotiris Amarantos

• Compilers & Programming Languages
  • /* Nov 24, 2025 */ Having Fun with K&R C
  • /* Jul 19, 2025 */ metap: A Meta-Programming Layer for Python
  • /* May 07, 2025 */ What Happens If We Inline Everything?
  • /* Mar 13, 2025 */ Getting Started with Compilers
  • /* Dec 09, 2024 */ Common Misconceptions about Compilers
  • /* Dec 02, 2024 */ Defining All Undefined Behavior and Leveraging Compiler Transformation APIs
  • /* Nov 16, 2024 */ Compiler Optimization in a Language you Can Understand
  • /* Mar 28, 2023 */ Dias: Automatically Rewriting Pandas for 1000x Speedups
  • /* Mar 09, 2023 */ How Target-Independent is Your IR?
  • /* Apr 24, 2022 */ The Weird Type System of Golang
  • /* Jan 30, 2022 */ The Cryptic Proof of Semidominators in the Lengauer-Tarjan Algorithm
  • /* Nov 05, 2020 */ Juggling Knives or Adding Definedness to Combat Undefined Behavior
  • /* Aug 13, 2020 */ Tell The Compiler What You Know
  • /* May 21, 2020 */ Introduction to Scalar Evolution with Iteration-Based Intuition
  • /* May 08, 2020 */ Visualizing Dominators
  • /* May 03, 2020 */ Loop To Constant Computation

• Databases
  • /* Oct 15, 2025 */ “Serializability: multi-operation, multi-object”, but why?
  • /* Oct 08, 2025 */ Building and Debugging Postgres

• Performance
  • /* Feb 15, 2025 */ A Beginner's Guide to Vectorization By Hand: Part 4 - Convolution
  • /* Aug 28, 2021 */ A Beginner's Guide to Vectorization By Hand: Part 3
  • /* Sep 13, 2021 */ A Beginner's Guide to Vectorization By Hand: Part 2
  • /* Aug 31, 2020 */ A Beginner's Guide to Vectorization By Hand: Part 1

• Uncategorized
  • /* Nov 24, 2025 */ Simulating Unix v7 on PDP-11 with In-Depth Explanations
  • /* Nov 11, 2023 */ Inverting the Inverted: Revisiting Dismissed Ideas in Research
  • /* Dec 01, 2020 */ The New Free Ride in Computing
  • /* Aug 09, 2020 */ How 99% of C Tutorials Get it Wrong
  • /* May 23, 2020 */ GJK Algorithm: A Visual Derivation

• Non-Computer Science
  • /* Jul 20, 2026 */ Ἐπικαιρότης #2 - Ρητορική, Τέχνη καὶ Ἰδεολογία
  • /* Jul 13, 2026 */ La condensation du temps à travers la technique
  • /* Jul 12, 2026 */ Did Aristotle Talk About Freedom, Justice, and Equality?
  • /* Jun 29, 2026 */ Spontaneous Data and Sexually-Explicit AI Content: A Legal and Philosophical Perspective
  • /* Jun 28, 2026 */ A Rousseauian Analysis of Free Software
  • /* Jun 26, 2026 */ Πρὸς μία Φιλοσοφία Γλωσσικῆς Προόδου
  • /* Jun 25, 2026 */ L’amitié et l’amour
  • /* Jun 24, 2026 */ Γλῶσσα + Φλέρτ: Μήπως ἀποδίδουμε ὑπερβολικὴ βαρύτητα στὴν γλῶσσα;
  • /* Jun 22, 2026 */ The “You Can Do It Too” Narrative
  • /* Jun 20, 2026 */ Ἐξουσία καὶ Γλῶσσα
  • /* Jun 18, 2026 */ La dégénérescence de la fiabilité
  • /* Jun 11, 2026 */ Τὰ Ἀλαμπουρνέζικα τῶν Ἀγγλοπαθῶν
  • /* Jun 08, 2026 */ Wo zieht man da die Grenze?
  • /* Jun 05, 2026 */ Quotes: Showing Off, Credit, and the Construction of Authorship
  • /* Jun 01, 2026 */ Reddit: The Authoritarian Personality – 6+1 Sideways Reflections
  • /* May 31, 2026 */ De la personnalité, par opposition au sujet, en philosophie et dans les sciences exactes
  • /* May 27, 2026 */ Ἐπικαιρότης #1 - Τὸ Greekonomics καὶ οἱ πολιτικοί «μας»
  • /* May 12, 2026 */ The Banality of Formal Writing
  • /* Apr 22, 2026 */ L’état lugubre de l’hébergement des étudiants aux États-Unis
  • /* Mar 19, 2026 */ Rousseau, la raison et la conscience
  • /* Mar 16, 2026 */ Γιατί Μιλᾶμε Ἑλληνικά;
  • /* Feb 06, 2026 */ On Pronouns
  • /* Sep 20, 2025 */ On Reading Books
  • /* Aug 02, 2025 */ Les Mots Français en Grec – Partie 2
  • /* Jul 16, 2025 */ Πῶς οἱ Χατζηφραγκέτα μᾶς Ἔκαναν Διανοουμένους
  • /* Jul 08, 2025 */ Les Mots Français en Grec
  • /* May 17, 2025 */ The Curse of Microlearning
  • /* May 03, 2025 */ On Hypocritical Writing
  • /* Apr 04, 2025 */ Listening to Your Own Music - Short Essay
  • /* Mar 22, 2025 */ Σύντομος Ἔκθεσι: Ἡ παγκοσμίας κλάσης μετάφρασι τοῦ Στίγκλερ τῆς κ. Σινοπούλου
  • /* Mar 18, 2025 */ Γιατί χρησιμοποιῶ τὸ πολυτονικό
  • /* Mar 02, 2025 */ Tempi: Translating Greece's Indignation
  • /* Feb 22, 2025 */ Γλωσσάρι Μ. Καραγάτση
  • /* Feb 12, 2025 */ Short Essays - February 2025
    • ↳On the value of a non-thesis CS master's in a top school in the US
    • ↳Descartes' conception of infinity
    • ↳Unified theories as a type of compression
    • ↳Two interpretations of the rise of authoritarian regimes
  • /* Jul 16, 2023 */ Remembering and the Impact of Books