{
  "schemaVersion": 2,
  "generatedAt": "2026-10-27T06:09:41.691Z",
  "canonicalUrl": "https://wtfashwin.github.io/Portfolio/",
  "identity": {
    "name": "Ashwin Upadhyay",
    "role": "AI Systems & Backend Engineer",
    "location": "Pune, India",
    "email": "ashwinupadhyay09@gmail.com",
    "bio": "I build AI applications and the backend systems behind them: retrieval, secure APIs, data models, and reliable workflows.",
    "links": {
      "github": "https://github.com/wtfashwin",
      "linkedin": "https://www.linkedin.com/in/upadhyayashwin/",
      "certifications": "https://www.linkedin.com/in/upadhyayashwin/details/certifications/",
      "leetcode": "https://leetcode.com/u/wtfashwin/",
      "kaggle": "https://www.kaggle.com/ashwinupadhyay",
      "geeksforgeeks": "https://www.geeksforgeeks.org/profile/wtfashwin",
      "credly": "https://www.credly.com/users/ashwin-upadhyay.d80bc5d2/badges/credly",
      "achievements": "https://github.com/wtfashwin/wtfashwin/blob/main/ACHIEVEMENTS.md",
      "oss": "https://github.com/wtfashwin/wtfashwin/blob/main/OPEN_SOURCE.md",
      "medium": "https://medium.com/@ashwinupadhyay",
      "hashnode": "https://hashnode.com/@wtfashwin",
      "paper": "https://www.tijer.org/paper/TIJER2505180"
    }
  },
  "evidenceNotes": {
    "generation": "Generated from the portfolio editorial source. Generation time is not an evidence verification time.",
    "professionalExperience": "Supplied professional summaries. Employer source code is private; public runtime or production outcomes are not asserted.",
    "publicProjects": "Linked source describes implementation; a liveUrl identifies a separately linked tool, prototype or synthetic example. Neither establishes production readiness or measured outcomes.",
    "interactiveExplanations": "Illustrative explanations of engineering concepts. The linked source records are the evidence.",
    "platformRecords": "Dated snapshots. Badge, competition, and profile records retain their separate check times; they are not live statistics.",
    "credentials": "Credential records and verification URLs supplied in the portfolio. These were not independently refreshed during this build."
  },
  "professionalExperience": [
    {
      "role": "Founding AI Engineer",
      "organization": "Sylox",
      "period": "Feb 2026 to Present",
      "focus": "Data privacy and AI backend platforms",
      "summary": [
        "Owned IRIS feature delivery across FastAPI, React/TypeScript, and PostgreSQL, from requirements through review and release.",
        "Rebuilt sensitive-data classification and repaired tests, migrations, and authentication failures.",
        "Built secure integrations and provider-agnostic AI verification services; proposed customer-hosted scanning architecture."
      ],
      "technologies": [
        "FastAPI",
        "PostgreSQL",
        "React",
        "Data privacy"
      ],
      "evidenceType": "supplied professional summary"
    },
    {
      "role": "AI Engineer · Contract",
      "organization": "LOPhils Inc.",
      "period": "Oct to Nov 2025",
      "focus": "Legal-document RAG assistant",
      "summary": [
        "Built ingestion, embeddings, metadata isolation, hybrid retrieval, reranking, and grounded answers.",
        "Developed asynchronous ingestion, search, and chat APIs with retries, caching, and retrieval checks."
      ],
      "technologies": [
        "FastAPI",
        "LangChain",
        "Pinecone",
        "RAG"
      ],
      "evidenceType": "supplied professional summary"
    }
  ],
  "runnableExamples": [
    {
      "id": "airflow-retry-policy",
      "problem": "Airflow retries and exception policy",
      "scope": "Local examples of a retry and an explicit exception policy. A retry alone does not make writes duplicate-safe.",
      "links": [
        {
          "label": "Run the retry example",
          "url": "https://gist.github.com/wtfashwin/1997b331f3a4a5dc17c621ee3bd97f3a"
        },
        {
          "label": "Inspect the exception policy",
          "url": "https://gist.github.com/wtfashwin/373319b939b76759dd97cf164b1965cb"
        }
      ]
    },
    {
      "id": "csv-meaning",
      "problem": "Keep meaning when reading a CSV",
      "scope": "A synthetic five-row batch preserves IDs, integer money units, missing values, and explicit timestamps. The notebook walks through the same boundaries.",
      "links": [
        {
          "label": "Run the CSV checks",
          "url": "https://gist.github.com/wtfashwin/aca8c85f3d6d3da1374c5f1e4945c075"
        },
        {
          "label": "Open the worked notebook",
          "url": "https://gist.github.com/wtfashwin/dce7ceedb2214464352997b427bff1fd"
        }
      ]
    },
    {
      "id": "api-body-boundary",
      "problem": "Check an API request-body boundary",
      "scope": "A local ASGI proof checks the body limit against a pinned source commit using fixed test doubles.",
      "links": [
        {
          "label": "Run the body-limit proof",
          "url": "https://gist.github.com/wtfashwin/864824eb480b0f01a13bb2d057447ea7"
        }
      ]
    },
    {
      "id": "csv-duplicate-audit",
      "problem": "Remove exact repeats without hiding conflicts",
      "scope": "Nine synthetic CSV records become seven retained records, with two exact repeats and two conflicting keys recorded in the audit.",
      "links": [
        {
          "label": "Run the duplicate audit",
          "url": "https://gist.github.com/wtfashwin/d4781a7504c871a5531d0403eeb40652"
        }
      ]
    },
    {
      "id": "classification-counts",
      "problem": "Read classification counts before the score",
      "scope": "Invented counts make precision, recall, and cutoff tradeoffs inspectable. This is arithmetic, not a model benchmark.",
      "links": [
        {
          "label": "Run the toy count example",
          "url": "https://gist.github.com/wtfashwin/a082d9456219a0e2ef22d26870361ca7"
        }
      ]
    }
  ],
  "publicProjects": [
    {
      "name": "Invoice Followup",
      "role": "Creator",
      "focus": "A free invoice queue and editable payment reminders",
      "summary": [
        "Review invoices, prepare a reminder draft and import or export a CSV in the browser.",
        "No account or automatic sending. Optional browser saving is unencrypted; the tool does not verify payments."
      ],
      "technologies": [
        "JavaScript",
        "CSV",
        "Browser storage"
      ],
      "sourceUrl": "https://github.com/wtfashwin/invoice-followup",
      "kind": "public-tool",
      "liveUrl": "https://invoice-followup.zany-hippo-3715.chatgpt.site/",
      "evidenceType": "public source and live validation prototype",
      "evidence": {
        "checkedAt": "2026-10-22",
        "sourceCommit": "3ac76427da6fd60fc2199a9b24f27f49a839b98b",
        "scope": "Public browser-local validation prototype. No paying users, collection improvement, traffic or rankings are established."
      }
    },
    {
      "name": "CSV Reporting Example",
      "role": "Creator",
      "focus": "A synthetic campaign report from two fictional CSV files",
      "summary": [
        "Inspect six illustrative metrics, their formulas and a JSON calculation receipt generated from fictional CSV inputs.",
        "No upload or live connector. This example does not establish customer results or a production reporting service."
      ],
      "technologies": [
        "Python",
        "CSV",
        "HTML",
        "Decimal"
      ],
      "sourceUrl": "https://github.com/wtfashwin/csv-report-pilot",
      "kind": "public-example",
      "liveUrl": "https://wtfashwin.github.io/Portfolio/reporting-example/",
      "evidenceType": "public source and synthetic reporting example",
      "evidence": {
        "checkedAt": "2026-10-23",
        "sourceCommit": "86065ea65e7b2e55453281e36b6fe06aa9c8fc04",
        "scope": "Synthetic reporting example using fictional CSV inputs. No upload, live connector, customer results or production reporting service is established."
      }
    },
    {
      "name": "Customer Support System",
      "role": "Creator",
      "focus": "AI support workflows and retrieval",
      "summary": [
        "FastAPI AI service with retrieval and LangGraph tool workflows, alongside a TypeScript application.",
        "Streaming responses, authorization forwarding, request correlation, and readiness checks.",
        "Public implementation and review history available on GitHub."
      ],
      "technologies": [
        "LangGraph",
        "FastAPI",
        "TypeScript"
      ],
      "sourceUrl": "https://github.com/wtfashwin/Customer-Support-System",
      "evidenceType": "public source implementation",
      "evidence": {
        "checkedAt": "2026-10-27",
        "sourceCommit": "60f711e7d2bec62a0fcc9bf48515027965f071ef",
        "sourceUrl": "https://github.com/wtfashwin/Customer-Support-System/tree/60f711e7d2bec62a0fcc9bf48515027965f071ef",
        "verificationLinks": [
          {
            "label": "Merged database setup fix",
            "url": "https://github.com/wtfashwin/Customer-Support-System/pull/12"
          },
          {
            "label": "CI: builds, API checks and fresh database setup",
            "url": "https://github.com/wtfashwin/Customer-Support-System/actions/runs/38647008014"
          },
          {
            "label": "Python tests and dry fixture evaluation",
            "url": "https://github.com/wtfashwin/Customer-Support-System/actions/runs/38647007939"
          }
        ],
        "scope": "GitHub Actions passed on 14 Oct 2026: web/API builds and checks, fresh and repeated PostgreSQL 16 setup, Python tests, and dry fixture evaluation. Deployment, external-provider, authentication and live RAG paths remain unverified."
      }
    },
    {
      "name": "Context Dock",
      "role": "Creator",
      "focus": "Native macOS developer tool",
      "summary": [
        "Swift, SwiftUI, and AppKit interface for capturing task ideas and matching project context.",
        "Local agent events, decision journaling, and atomic note writes.",
        "Public source and setup instructions available on GitHub."
      ],
      "technologies": [
        "Swift",
        "SwiftUI",
        "macOS"
      ],
      "sourceUrl": "https://github.com/wtfashwin/ContextDock",
      "evidenceType": "public source implementation",
      "evidence": {
        "checkedAt": "2026-10-27",
        "sourceCommit": "f20c8fb871f1a89685ffc6e3222dcc14a9eec061",
        "sourceUrl": "https://github.com/wtfashwin/ContextDock/tree/f20c8fb871f1a89685ffc6e3222dcc14a9eec061",
        "verificationLinks": [
          {
            "label": "Swift package build and tests",
            "url": "https://github.com/wtfashwin/ContextDock/actions/runs/38643769670"
          }
        ],
        "scope": "GitHub Actions passed shell checks, package build and tests on 14 Oct 2026 at this pull-request commit. These checks do not establish native UI behavior, external CLI compatibility or end-user runtime outcomes."
      }
    },
    {
      "name": "Fraud Detection",
      "role": "Creator",
      "focus": "Credit-card feature scoring and asynchronous explanations",
      "summary": [
        "FastAPI accepts 30 ordered features; Celery persists model explanations through Redis and PostgreSQL.",
        "Explicit pending, completed, failed, and duplicate-ID responses, plus readiness and bounded input-drift checks.",
        "Separate historical XGBoost benchmark reports ROC AUC 0.973709 on 56,962 held-out rows; the packaged demonstration model is a different artifact."
      ],
      "technologies": [
        "FastAPI",
        "Celery",
        "Redis",
        "PostgreSQL",
        "XGBoost"
      ],
      "sourceUrl": "https://github.com/wtfashwin/fraud-detection",
      "evidenceType": "public source implementation",
      "evidence": {
        "checkedAt": "2026-10-16",
        "sourceCommit": "4c7cd588c607bac7b47669ca51f711c4faec2417",
        "benchmarkUrl": "https://github.com/wtfashwin/fraud-detection/blob/4c7cd588c607bac7b47669ca51f711c4faec2417/docs/benchmark-results.md",
        "apiUrl": "https://github.com/wtfashwin/fraud-detection/blob/4c7cd588c607bac7b47669ca51f711c4faec2417/api/app.py",
        "scope": "Public implementation and a separate historical benchmark. Portfolio visualization is illustrative and makes no API requests."
      }
    }
  ],
  "upstreamContributions": {
    "checkedAt": "2026-10-12",
    "verifiedMergedTotal": 11,
    "verifiedRepositoryTotal": 7,
    "selectedCount": 7,
    "scope": "11 visible merged upstream PRs authored by wtfashwin across seven repositories were checked on this date. The selected records below are a subset, not the full inventory or a lifetime census. Accepted changes do not imply endorsement or measured production impact.",
    "fullRecordUrl": "https://github.com/wtfashwin/wtfashwin/blob/main/OPEN_SOURCE.md",
    "selected": [
      {
        "repository": "PrefectHQ/prefect",
        "pullRequest": "#22035",
        "title": "Fix Azure blob result storage to overwrite on rewrite (#19411)",
        "summary": "Allow cached task results in Azure Blob Storage to be overwritten on reruns.",
        "area": "Reliable storage",
        "url": "https://github.com/PrefectHQ/prefect/pull/22035",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      },
      {
        "repository": "dlt-hub/dlt",
        "pullRequest": "#3947",
        "title": "fix(mssql): ingest parquet row-groups individually to bound ADBC driver   memory",
        "summary": "Load Parquet row groups individually to limit SQL Server ingestion memory.",
        "area": "Bounded memory",
        "url": "https://github.com/dlt-hub/dlt/pull/3947",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      },
      {
        "repository": "VictoriaMetrics/VictoriaMetrics",
        "pullRequest": "#10974",
        "title": "app/vmselect/promql: stop integrate() from extrapolating past series end",
        "summary": "Stop integrate() from adding data beyond the end of a metric series.",
        "area": "Correct calculations",
        "url": "https://github.com/VictoriaMetrics/VictoriaMetrics/pull/10974",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      },
      {
        "repository": "unslothai/unsloth",
        "pullRequest": "#5551",
        "title": "studio/chat: release stuck IME flag when compositionend never fires",
        "summary": "Release a stuck IME typing state so users can send their messages.",
        "area": "Input handling",
        "url": "https://github.com/unslothai/unsloth/pull/5551",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      },
      {
        "repository": "langfuse/langfuse-python",
        "pullRequest": "#1664",
        "title": "fix(deps): support wrapt 2.x (closes #1561)",
        "summary": "Support installation with wrapt 2.x.",
        "area": "Compatibility",
        "url": "https://github.com/langfuse/langfuse-python/pull/1664",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      },
      {
        "repository": "TracecatHQ/tracecat",
        "pullRequest": "#2715",
        "title": "feat(elastic_security): add _source field filter to list_detection_signals",
        "summary": "Request only the Elastic alert fields a workflow needs.",
        "area": "Security workflows",
        "url": "https://github.com/TracecatHQ/tracecat/pull/2715",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      },
      {
        "repository": "ParisNeo/lollms-webui",
        "pullRequest": "#690",
        "title": "security: harden sanitize_path regex against #641 traversal class + regression tests",
        "summary": "Clarify path sanitization and add traversal regression tests.",
        "area": "Path safety",
        "url": "https://github.com/ParisNeo/lollms-webui/pull/690",
        "author": "wtfashwin",
        "status": "merged",
        "checkedAt": "2026-10-12"
      }
    ]
  },
  "skills": {
    "AI applications": [
      "RAG",
      "LangGraph",
      "LangChain",
      "Embeddings",
      "Reranking",
      "Retrieval evaluation"
    ],
    "Backend": [
      "Python",
      "FastAPI",
      "SQLAlchemy",
      "Celery",
      "Redis",
      "REST APIs"
    ],
    "Data": [
      "SQL",
      "PostgreSQL",
      "Alembic",
      "Parquet",
      "Data modeling"
    ],
    "Applications": [
      "React",
      "TypeScript",
      "Swift",
      "SwiftUI"
    ],
    "Delivery": [
      "Docker",
      "GitHub Actions",
      "pytest",
      "OpenTelemetry"
    ],
    "Security": [
      "RBAC",
      "OAuth / JWT",
      "Tenant isolation",
      "Credential encryption",
      "Mutation auditing"
    ]
  },
  "directory": {
    "schemaVersion": 1,
    "checkedAt": "2026-10-08T16:14:10.336314+00:00",
    "scope": "Public profiles from linked evidence and user-supplied accounts. Each record retains its verification status; this is not an exhaustive internet search.",
    "profiles": [
      {
        "platform": "GitHub",
        "kind": "Code & open source",
        "handle": "wtfashwin",
        "url": "https://github.com/wtfashwin",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://github.com/wtfashwin"
        ],
        "refresh": {
          "type": "github"
        }
      },
      {
        "platform": "LinkedIn",
        "kind": "Professional profile",
        "handle": "upadhyayashwin",
        "url": "https://www.linkedin.com/in/upadhyayashwin/",
        "status": "verified",
        "checkedAt": "2026-10-17T06:28:55.775Z",
        "evidenceUrls": [
          "https://www.linkedin.com/in/upadhyayashwin/"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "Kaggle",
        "kind": "ML experiments",
        "handle": "ashwinupadhyay",
        "url": "https://www.kaggle.com/ashwinupadhyay",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://www.kaggle.com/ashwinupadhyay"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "Medium",
        "kind": "Technical writing",
        "handle": "ashwinupadhyay",
        "url": "https://medium.com/@ashwinupadhyay",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://medium.com/feed/@ashwinupadhyay"
        ],
        "refresh": {
          "type": "rss",
          "url": "https://medium.com/feed/@ashwinupadhyay"
        }
      },
      {
        "platform": "Hashnode",
        "kind": "Technical writing",
        "handle": "wtfashwin",
        "url": "https://hashnode.com/@wtfashwin",
        "status": "user-supplied",
        "checkedAt": null,
        "suppliedAt": "2026-10-17",
        "ownershipMethod": "user-confirmed",
        "evidenceUrls": [],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "CodePen",
        "kind": "Frontend demos",
        "handle": "wtfashwin-",
        "url": "https://codepen.io/wtfashwin-",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://ashwinupadhyay.medium.com/stopwatch-project-using-frontend-technologies-6b1d091abec4"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "LeetCode",
        "kind": "Problem solving",
        "handle": "wtfashwin",
        "url": "https://leetcode.com/u/wtfashwin/",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://leetcode.com/u/wtfashwin/"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "GeeksforGeeks",
        "kind": "Problem solving",
        "handle": "wtfashwin",
        "url": "https://www.geeksforgeeks.org/profile/wtfashwin",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://github.com/wtfashwin"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "Codolio",
        "kind": "Coding activity",
        "handle": "wtfashwin",
        "url": "https://codolio.com/profile/wtfashwin",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://leetcode.com/u/wtfashwin/"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "Credly",
        "kind": "Verified credentials",
        "handle": "ashwin-upadhyay.d80bc5d2",
        "url": "https://www.credly.com/users/ashwin-upadhyay.d80bc5d2/badges/credly",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://www.credly.com/users/ashwin-upadhyay.d80bc5d2/badges/credly"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "TIJER",
        "kind": "Research publication",
        "handle": "TIJER2505180",
        "url": "https://tijer.org/tijer/viewpaperforall.php?paper=TIJER2505180",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://tijer.org/tijer/viewpaperforall.php?paper=TIJER2505180"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "Twine",
        "kind": "Freelance profile",
        "handle": "AshwinUpadhyay",
        "url": "https://www.twine.net/AshwinUpadhyay",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://www.twine.net/AshwinUpadhyay"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "Collective",
        "kind": "Freelance profile",
        "handle": "ashwin-upadhyay",
        "url": "https://www.collective.work/profile/ashwin-upadhyay",
        "status": "verified",
        "checkedAt": "2026-10-08T16:14:10.336314+00:00",
        "evidenceUrls": [
          "https://www.collective.work/profile/ashwin-upadhyay"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "PyPI",
        "kind": "Package profile",
        "handle": "wtfashwin",
        "url": "https://pypi.org/user/wtfashwin/",
        "status": "verified",
        "checkedAt": "2026-10-08T16:24:47.736792+00:00",
        "ownershipMethod": "user-confirmed",
        "evidenceUrls": [
          "https://pypi.org/user/wtfashwin/"
        ],
        "refresh": {
          "type": "manual"
        }
      },
      {
        "platform": "RemoteOK",
        "kind": "Professional profile",
        "handle": "wtfashwin",
        "url": "https://remoteok.com/@wtfashwin",
        "status": "verified",
        "checkedAt": "2026-10-08T16:24:47.736792+00:00",
        "ownershipMethod": "user-confirmed",
        "evidenceUrls": [
          "https://remoteok.com/@wtfashwin"
        ],
        "refresh": {
          "type": "manual"
        }
      }
    ],
    "writing": [
      {
        "title": "SHAR: Scalable Human Activity Recognition",
        "url": "https://tijer.org/TIJER/papers/TIJER2505180.pdf",
        "platform": "TIJER",
        "publishedAt": "2025-05",
        "role": "Co-author"
      },
      {
        "title": "Harnessing Future Insights: A Beginner’s Guide to Predictive Analytics",
        "url": "https://ashwinupadhyay.medium.com/harnessing-future-insights-a-beginners-guide-to-predictive-analytics-769254e74a8d",
        "platform": "Medium",
        "publishedAt": "2024-03-29T15:58:19+00:00"
      },
      {
        "title": "Stopwatch project using Frontend technologies",
        "url": "https://ashwinupadhyay.medium.com/stopwatch-project-using-frontend-technologies-6b1d091abec4",
        "platform": "Medium",
        "publishedAt": "2024-03-02T15:42:36+00:00"
      },
      {
        "title": "Building a Password Generator with HTML, CSS, and JavaScript",
        "url": "https://ashwinupadhyay.medium.com/building-a-password-generator-with-html-css-and-javascript-1549198fc5a3",
        "platform": "Medium",
        "publishedAt": "2024-03-02T15:17:02+00:00"
      },
      {
        "title": "From Code to Insights: Navigating the Journey from Web Development to Data Science",
        "url": "https://ashwinupadhyay.medium.com/from-code-to-insights-navigating-the-journey-from-web-development-to-data-science-452018749e8f",
        "platform": "Medium",
        "publishedAt": "2024-03-02T10:50:59+00:00"
      }
    ]
  },
  "writing": [
    {
      "title": "SHAR: Scalable Human Activity Recognition",
      "url": "https://tijer.org/TIJER/papers/TIJER2505180.pdf",
      "platform": "TIJER",
      "publishedAt": "2025-05",
      "role": "Co-author"
    },
    {
      "title": "Harnessing Future Insights: A Beginner’s Guide to Predictive Analytics",
      "url": "https://ashwinupadhyay.medium.com/harnessing-future-insights-a-beginners-guide-to-predictive-analytics-769254e74a8d",
      "platform": "Medium",
      "publishedAt": "2024-03-29T15:58:19+00:00"
    },
    {
      "title": "Stopwatch project using Frontend technologies",
      "url": "https://ashwinupadhyay.medium.com/stopwatch-project-using-frontend-technologies-6b1d091abec4",
      "platform": "Medium",
      "publishedAt": "2024-03-02T15:42:36+00:00"
    },
    {
      "title": "Building a Password Generator with HTML, CSS, and JavaScript",
      "url": "https://ashwinupadhyay.medium.com/building-a-password-generator-with-html-css-and-javascript-1549198fc5a3",
      "platform": "Medium",
      "publishedAt": "2024-03-02T15:17:02+00:00"
    },
    {
      "title": "From Code to Insights: Navigating the Journey from Web Development to Data Science",
      "url": "https://ashwinupadhyay.medium.com/from-code-to-insights-navigating-the-journey-from-web-development-to-data-science-452018749e8f",
      "platform": "Medium",
      "publishedAt": "2024-03-02T10:50:59+00:00"
    }
  ],
  "credentialRecords": [
    {
      "issuer": "Oracle",
      "title": "Fusion AI Agent Studio Certified Foundations Associate · Rel 1",
      "category": "professional",
      "period": "May 2026",
      "summary": "Foundations for building agents with Oracle Fusion AI Agent Studio.",
      "url": "https://catalog-education.oracle.com/pls/certview/sharebadge?id=32E3D22C92D717455374A138EDB6F9D13FD05BC72298FBA0430F7B64E25A92C1"
    },
    {
      "issuer": "Securiti AI",
      "title": "AI Security & Governance",
      "category": "professional",
      "period": "Feb 2026",
      "summary": "Generative AI risk, compliance, and responsible governance frameworks.",
      "url": "https://education.securiti.ai/verification/1451D2717-1451D2586-13EEB4DC5/"
    },
    {
      "issuer": "Saviynt",
      "title": "Identity Security for AI Age",
      "category": "professional",
      "period": "Dec 2025",
      "summary": "Identity security concepts for systems shaped by AI.",
      "url": "https://www.linkedin.com/in/upadhyayashwin/overlay/Certifications/1941196376/treasury/?profileId=ACoAACoEXhsBoRSy1GtJ2ZRN8QPPUEeXhcKrgNU"
    },
    {
      "issuer": "Oracle",
      "title": "Oracle Cloud Infrastructure 2025 Certified AI Foundations Associate",
      "category": "professional",
      "period": "Dec 2025",
      "summary": "Core artificial intelligence and machine learning concepts on OCI.",
      "url": "https://catalog-education.oracle.com/pls/certview/sharebadge?id=8A67E3A33AECF97AAEB719CB796CB04A057F8BDE066F19BF1C47CE965C9A6733"
    },
    {
      "issuer": "Calyptus",
      "title": "AI Fluent Tech Professional",
      "category": "professional",
      "period": "Nov 2025",
      "summary": "AI fluency credential issued by Calyptus.",
      "url": "https://certificate.calyptus.co/ai-fluency/14-ashwin-upadhyay"
    },
    {
      "issuer": "Oracle",
      "title": "Oracle Cloud Infrastructure 2025 Certified Developer Professional",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "Developing and deploying applications with Oracle Cloud Infrastructure.",
      "url": "https://catalog-education.oracle.com/pls/certview/sharebadge?id=00D3CEA936F13F2D2905235F947DED4EA6503F96C7E69973D265C93E05AD3DC5"
    },
    {
      "issuer": "Oracle",
      "title": "Oracle Cloud Infrastructure 2025 Certified Architect Associate",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "Oracle Cloud Infrastructure architecture and cloud design fundamentals.",
      "url": "https://catalog-education.oracle.com/ords/certview/sharebadge?id=B292D02B22DF5A1C895F880AA38DAE04CFECC912C094910A7609F4C7B8AD45CF"
    },
    {
      "issuer": "Oracle",
      "title": "Oracle AI Vector Search Certified Professional",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "Vector indexing and semantic search in Oracle Database 23ai.",
      "url": "https://catalog-education.oracle.com/ords/certview/sharebadge?id=3185B297B63CFB0C026C0932DC7862BD722B907FC3332D6BDA2A5D96C927D306"
    },
    {
      "issuer": "Oracle",
      "title": "Oracle Cloud Infrastructure 2025 Certified Data Science Professional",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "End-to-end cloud machine learning workflows and MLOps on OCI.",
      "url": "https://catalog-education.oracle.com/pls/certview/sharebadge?id=D9C78F28D89D65279F354EEE901A5B40788333EB0F3B9E5C2B36AE2DFF6599D1"
    },
    {
      "issuer": "Oracle",
      "title": "Oracle Cloud Infrastructure 2025 Certified Generative AI Professional",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "Generative AI workloads, fine-tuning, and OCI services.",
      "url": "https://catalog-education.oracle.com/ords/certview/sharebadge?id=3C89FBEBDA81EC0D06C13927A10CA75773E4117F437F99B4B06AF7356D24CC99"
    },
    {
      "issuer": "Astronomer",
      "title": "Astronomer Certification for Apache Airflow 3 Fundamentals",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "Core concepts for authoring and operating Apache Airflow workflows.",
      "url": "https://www.credly.com/badges/ef9a1b33-9899-46b7-b25e-5a2acb979e69/linked_in_profile"
    },
    {
      "issuer": "Astronomer",
      "title": "Astronomer Certification DAG Authoring for Apache Airflow 3",
      "category": "professional",
      "period": "Oct 2025",
      "summary": "Building and scheduling DAGs with Apache Airflow 3.",
      "url": "https://www.credly.com/badges/863162ef-ee67-4e23-b577-82a36d96ebfa/linked_in_profile"
    },
    {
      "issuer": "OpenAI Academy",
      "title": "AI Foundations",
      "category": "course",
      "period": "16 Oct 2026",
      "summary": "Course completion badge, earned with AI assistance. Expires 16 Apr 2027.",
      "url": "https://oaiacademy.credential.net/3bcda655-d5ca-418f-aac2-f17724f886ad"
    },
    {
      "issuer": "Claude Academy",
      "title": "Claude 101",
      "category": "course",
      "period": "16 Oct 2026",
      "summary": "Course completion badge, earned with AI assistance.",
      "url": "https://academy.claude.com/verify/be08d5b205c977103968365dbf95bbc6"
    },
    {
      "issuer": "Claude Academy",
      "title": "AI Fluency: Framework and foundations",
      "category": "course",
      "period": "16 Oct 2026",
      "summary": "Course completion badge, earned with AI assistance.",
      "url": "https://academy.claude.com/verify/fd3decdcc20f36553c9678198ae14dcf"
    },
    {
      "issuer": "Kaggle Learn",
      "title": "Intermediate Machine Learning",
      "category": "course",
      "period": "16 Oct 2026",
      "summary": "Course completion certificate, earned with AI assistance.",
      "url": "https://www.kaggle.com/learn/certification/ashwinupadhyay/intermediate-machine-learning"
    },
    {
      "issuer": "Databricks",
      "title": "Academy Accreditation - Generative AI Fundamentals",
      "category": "course",
      "period": "Oct 2025",
      "summary": "Generative AI concepts and workloads in the Databricks platform.",
      "url": "https://credentials.databricks.com/d0424f1c-b0e0-4b02-beef-5fbbb4c6d80e"
    },
    {
      "issuer": "Databricks",
      "title": "Academy Accreditation - AI Agent Fundamentals",
      "category": "course",
      "period": "Oct 2025",
      "summary": "Foundations for building AI agents with Databricks tools and patterns.",
      "url": "https://credentials.databricks.com/bd8fd17f-12f6-4f9b-8da0-4c68b628ed02"
    },
    {
      "issuer": "KodeKloud",
      "title": "Kubernetes for Absolute Beginners",
      "category": "course",
      "period": "Oct 2025",
      "summary": "Container orchestration, deployments, services, and cluster basics.",
      "url": "https://certificates.kodekloud.com/a22750a7-822e-449c-bcb9-6e048a98f5ca/2c52f2b1-b94a-467d-89da-a6317ba68b4f/fe7d88e3-8261-42c6-86ae-707143cda34f.pdf"
    },
    {
      "issuer": "KodeKloud",
      "title": "RAG Crash Course",
      "category": "course",
      "period": "Oct 2025",
      "summary": "Retrieval-augmented generation concepts and implementation basics.",
      "url": "https://certificates.kodekloud.com/81da9e5d-809c-466c-a3b0-614ce677b524/74039b22-3f2e-45bc-acc7-e2aefe8e63ba/89a6ef67-6aba-4d40-983d-67112d3ce2be.pdf"
    },
    {
      "issuer": "Udemy",
      "title": "JavaScript 2019: JavaScript ES6 Certification Course",
      "category": "course",
      "period": "Nov 2024",
      "summary": "JavaScript ES6 language features and modern JavaScript fundamentals.",
      "url": "https://udemy-certificate.s3.amazonaws.com/pdf/UC-b337ecb9-867b-48e8-b3b2-6800d07daf62.pdf"
    },
    {
      "issuer": "Forage",
      "title": "AWS - Solutions Architecture Job Simulation",
      "category": "simulation",
      "period": "Jul 2025",
      "summary": "Designed scalable Elastic Beanstalk hosting and explained its cost model.",
      "url": "https://forage-uploads-prod.s3.amazonaws.com/completion-certificates/pmnMSL4QiQ9JCgE3W/kkE9HyeNcw6rwCRGw_pmnMSL4QiQ9JCgE3W_GbrwZJ7GpEHHpCD3m_1752581762033_completion_certificate.pdf"
    },
    {
      "issuer": "Forage",
      "title": "Lloyds Banking Group - Technology Engineering Job Simulation",
      "category": "simulation",
      "period": "Jul 2025",
      "summary": "Designed and presented a customer-focused mortgage calculator.",
      "url": "https://forage-uploads-prod.s3.amazonaws.com/completion-certificates/Zbnc2o4ok6kD2NEXx/8AFfeg9k5udSCu6r5_Zbnc2o4ok6kD2NEXx_GbrwZJ7GpEHHpCD3m_1752586634915_completion_certificate.pdf"
    },
    {
      "issuer": "Forage",
      "title": "Deloitte Australia - Data Analytics Job Simulation",
      "category": "simulation",
      "period": "Jul 2025",
      "summary": "Analyzed data, built a Tableau dashboard, and used Excel to draw conclusions.",
      "url": "https://forage-uploads-prod.s3.amazonaws.com/completion-certificates/9PBTqmSxAf6zZTseP/io9DzWKe3PTsiS6GG_9PBTqmSxAf6zZTseP_GbrwZJ7GpEHHpCD3m_1752579647907_completion_certificate.pdf"
    }
  ],
  "platformRecords": {
    "kaggle": {
      "badges": [
        {
          "name": "1 Year on Kaggle",
          "awardedAt": "2024-09-13",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/49",
          "status": "awarded"
        },
        {
          "name": "2 Years on Kaggle",
          "awardedAt": "2025-06-01",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/50",
          "status": "awarded"
        },
        {
          "name": "Getting Started Competitor",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/6",
          "status": "awarded"
        },
        {
          "name": "Playground Competitor",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/9",
          "status": "awarded"
        },
        {
          "name": "Code Submitter",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/13",
          "status": "awarded"
        },
        {
          "name": "Python Coder",
          "awardedAt": "2024-09-13",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/30",
          "status": "awarded"
        },
        {
          "name": "R Coder",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/31",
          "status": "awarded"
        },
        {
          "name": "API Notebook Creator",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/34",
          "status": "awarded"
        },
        {
          "name": "Colab Coder",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/36",
          "status": "awarded"
        },
        {
          "name": "Code Tagger",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/37",
          "status": "awarded"
        },
        {
          "name": "Notebook Modeler",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/39",
          "status": "awarded"
        },
        {
          "name": "Dataset Creator",
          "awardedAt": "2024-09-25",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/17",
          "status": "awarded"
        },
        {
          "name": "API Dataset Creator",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/20",
          "status": "awarded"
        },
        {
          "name": "Dataset Tagger",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/22",
          "status": "awarded"
        },
        {
          "name": "Competition Modeler",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/29",
          "status": "awarded"
        },
        {
          "name": "Kaggle Community Member",
          "awardedAt": "2023-04-18",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/101",
          "status": "awarded"
        },
        {
          "name": "Collector",
          "awardedAt": "2025-01-21",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/42",
          "status": "awarded"
        },
        {
          "name": "Bookmarker",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/43",
          "status": "awarded"
        },
        {
          "name": "Vampire",
          "awardedAt": "2026-10-08",
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/44",
          "status": "awarded"
        },
        {
          "name": "Stylish",
          "awardedAt": null,
          "checkedAt": "2026-10-11T06:25:16.000Z",
          "evidenceUrl": "https://www.kaggle.com/certification/badges/ashwinupadhyay/41",
          "status": "awarded"
        }
      ],
      "competitions": [
        {
          "checkedAt": "2026-10-08T11:55:42.727668+00:00",
          "id": "llm-classification-finetuning",
          "notebookUrl": "https://www.kaggle.com/code/ashwinupadhyay/llm-preference-measured-cpu-baseline",
          "publicMetric": "Log loss",
          "publicScore": 1.04297,
          "scoreState": "scored",
          "status": "COMPLETE",
          "submissionRef": 56951809,
          "title": "LLM Classification Finetuning",
          "url": "https://www.kaggle.com/competitions/llm-classification-finetuning",
          "validationMetric": "Log loss",
          "validationScope": "Prompt-grouped development holdout (Kaggle execution; used for model selection)",
          "validationScore": 1.0525683147808185
        },
        {
          "checkedAt": "2026-10-08T11:36:58.861865+00:00",
          "id": "playground-series-s6e10",
          "notebookUrl": null,
          "publicMetric": "ROC AUC",
          "publicScore": 0.95843,
          "scoreState": "scored",
          "status": "COMPLETE",
          "submissionRef": 56951780,
          "title": "Predicting Airline Satisfaction",
          "url": "https://www.kaggle.com/competitions/playground-series-s6e10",
          "validationMetric": "ROC AUC",
          "validationScope": "Untouched holdout",
          "validationScore": 0.9593093506656138
        }
      ],
      "generatedAt": "2026-10-11T06:25:16.000Z",
      "profile": {
        "checkedAt": "2026-10-08T11:55:16.452000+00:00",
        "url": "https://www.kaggle.com/ashwinupadhyay",
        "username": "ashwinupadhyay",
        "verified": true
      },
      "schemaVersion": 1
    },
    "leetcode": {
      "checkedAt": "2026-10-08",
      "url": "https://leetcode.com/u/wtfashwin/",
      "summary": "923 problems",
      "detail": "LeetCode: 155 hard, contest rating 1,752, and 32 badges.",
      "evidenceType": "dated profile snapshot; not refreshed during this build"
    }
  }
}