[
  {
    "title": "Vesuvius Challenge Patch Aggregation Analysis",
    "description": "A report on patch aggregation methods in ink detection for the Vesuvius Challenge. Awarded August, 2024 Progress Prize.",
    "imgSrc": "assets/img/patch_agg.png",
    "imgAlt": "Vesuvius Challenge patch aggregation analysis",
    "link": "https://github.com/lschlessinger1/vesuvius-patch-agg-analysis",
    "linkText": "View on GitHub"
  },
  {
    "title": "Vesuvius Challenge Grand Prize (runner-up)",
    "description": "A method to detect ink in carbonized micro-CT scans of the Herculaneum Papyri. Awarded runner-up in the 2023 Grand Prize.",
    "imgSrc": "assets/img/scroll.png",
    "imgAlt": "Scroll ink prediction",
    "link": "https://github.com/lschlessinger1/vesuvius-grand-prize-submission",
    "linkText": "View on GitHub"
  },
  {
    "title": "Vesuvius topogeo",
    "description": "A topological and geometric analysis comparing and contrasting scrolls and fragments from the Vesuvius Challenge to better understand domain differences.",
    "imgSrc": "assets/img/curvature-preview.png",
    "imgAlt": "Scroll curvature",
    "link": "https://github.com/lschlessinger1/vesuvius-topogeo",
    "linkText": "View on GitHub"
  },
  {
    "title": "Automated Model Search Using Bayesian Optimization and Genetic Programming",
    "description": "Presented at the 3rd Workshop on Meta-Learning at NeurIPS 2019, Vancouver, Canada.",
    "imgSrc": "assets/img/kernel_encoding_example.png",
    "imgAlt": "Compositional kernel encoding",
    "link": "http://metalearning.ml/2019/papers/metalearn2019-schlessinger.pdf",
    "linkText": "View paper"
  },
  {
    "title": "Automated Kernel Search using Evolutionary Algorithms",
    "description": "Master's Project, Washington University in St. Louis, May 2019.",
    "imgSrc": "assets/img/kernel_tree.png",
    "imgAlt": "Kernel tree",
    "link": "https://github.com/lschlessinger1/MS-project/blob/master/reports/defense/report/project_report.pdf",
    "linkText": "View paper"
  }
]