01 About

Charles Benello

I'm a software engineer and systems researcher at the University of Chicago. This fall I'm joining Amazon Web Services in Palo Alto as a Software Development Engineer Intern on the Redshift query optimization team. I'm currently interning at Alter Domus, building AI systems for financial asset management. My background spans database internals, high-performance computing, and full-stack development.

I design and implement large-scale systems - from parallel sorting algorithms in Rust to GPU-accelerated query processing in CUDA to production AI pipelines in Python. I've published in VLDB and CIDR, working with Professor Aaron Elmore at UChicago's ChiData Lab and Professor Anastasia Ailamaki at EPFL's DIAS Lab.

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Education

University of Chicago

Master's degree / Financial Mathematics

Jun 2025 - Dec 2026

University of Chicago

BS / Mathematics and Computer Science (Systems specialization); Minor in Korean

Sep 2021 - Jun 2025

Dean's List

St Paul's School

2015 - 2021

Mathematics: A*; Further Mathematics: A*; Computer Science: D1

Current Work

  • Incoming SDE intern at AWS Redshift (Palo Alto, fall 2026), working on query optimization
  • Research: adaptive sort configuration across disaggregated and cloud-native hardware
  • Research: GPU-accelerated compression for analytical databases
  • Evaluating policy compliance gaps in Rust LLM code generation benchmarks
  • CovTSP: near-optimal transit coverage solver using real GTFS network data

Experience

Software Development Engineer Intern (Incoming)

AWS — Amazon Redshift·Aug 2026 - Nov 2026

Joining the Amazon Redshift team in Palo Alto as a Software Development Engineer Intern, working on query optimization for AWS's flagship cloud data warehouse.

Skills

Query OptimizationDistributed SystemsCloud Data WarehousingC++

Research + Publications

Research Focus

  • Large-scale data processing
  • Database internals
  • High-performance systems
  • GPU-accelerated compression

Research Highlights

  • Predictive modelling for CrocSort configuration on disaggregated and cloud-native hardware - finding diminishing returns in thread counts and near-optimal config selection without brute-force sweeps
  • Resource-adaptive query execution with paged memory management
  • GPU-accelerated compression: decompression strategies, workload modelling, and cost-based trade-offs
  • Policy gap in Rust code generation benchmarks: showing that code passing SWE-bench tests can still violate project-defined safety and style policies
  • Exploring external sort on GPUs, disaggregated hardware, and cloud-native environments - understanding how storage/compute separation and elastic resources reshape sorting performance

Advisors + Labs

  • Professor Aaron Elmore (ChiData Lab, University of Chicago)
  • Professor Anastasia Ailamaki (DIAS Lab, EPFL)

Publications

CrocSort: Resource-Efficient, Skew-Resilient Parallel External Merge Sort

Riki Otaki*, Charles Benello*, Fuheng Zhao, Aaron J. Elmore, Goetz Graefe

VLDB 2026

* Equal contribution

Getting the Most Out of External Sorting in Cloud and Disaggregated Environments

Charles Benello

HPTS 2026

Resource-Adaptive Query Execution with Paged Memory Management

Riki Otaki, Jun Hyuk Chang, Charles Benello, Aaron J. Elmore, Goetz Graefe

CIDR 2025

Benchmarks Pass, Policies Fail: A Policy Gap in Rust Code Generation Evaluation

Matt Gaughan, Charles Benello, Keixin Pei

In preparation

WIP

Projects

covtsp
es
bofa_hqla

CovTSP

Covering TSP solver for transit coverage optimization. Formalizes the London Tube Challenge into a provably near-optimal solver for any GTFS city.

Classes

4 projects

Personal

8 projects

Research

4 projects

Side Projects

13 projects

Uncategorized

4 projects

More Projects

5 projects