{
  "schema_version": "1.0",
  "name": "Venkat Shreyas Krishnan",
  "description": "Engineer, researcher, explorer.",
  "canonical_url": "http://localhost:3000",
  "updated_at": "2026-09-22",
  "about": [
    "My work spans software systems, machine learning, and the physical world. At Johns Hopkins, that means research into simulation and surgical robotics, alongside work on agents and structured retrieval.",
    "I am also the founder and CTO of Univonest, an agentic marketplace. Building a product brings a different set of questions into view: how people find what they need, how negotiation works, and how software behaves beyond a prototype.",
    "Outside work, I make room for tennis, solving problems on Deep-ML, playing puzzles on Matiks, and reading. This archive has space for those parts of life, too."
  ],
  "education": [
    {
      "institution": "Johns Hopkins University",
      "degree": "MS, Information Systems and AI",
      "distinction": "Dean’s Scholar"
    },
    {
      "institution": "Vellore Institute of Technology",
      "degree": "B.Tech, Information Technology",
      "distinction": ""
    }
  ],
  "experience": [
    {
      "organization": "Stealth AI startup",
      "role": "AI engineer",
      "dates": null,
      "narrative": "Work on backend systems, agentic evals, mcp, custom harness, post training",
      "areas": [
        "backend",
        "post training",
        "Agents",
        "MCP",
        "math"
      ]
    },
    {
      "organization": "Johns Hopkins University · AI Agent Lab",
      "role": "Research Assistant",
      "dates": null,
      "narrative": "At Johns Hopkins, my work spans GPU-accelerated XPBD soft-body simulation using NVIDIA Warp, real-time skin deformation, and differentiable physics calibrated with real-world displacement information. Graph neural networks form another part of this surgical-robotics research. Alongside physical simulation, I work on AI agents, agentic retrieval, MCP, and structured grounding.",
      "areas": [
        "Differentiable physics",
        "Surgical robotics",
        "GPU simulation",
        "Graph neural networks",
        "AI agents",
        "Agentic RAG",
        "MCP"
      ]
    },
    {
      "organization": "Synergetics AI",
      "role": "AI Engineer",
      "dates": null,
      "narrative": "At Synergetics AI, I worked on production MCP servers and the infrastructure around AI agents. The engineering work included client integrations, backend performance, and cloud infrastructure across GCP and AWS, with Terraform for infrastructure configuration.",
      "areas": [
        "MCP",
        "Agent infrastructure",
        "GCP",
        "AWS",
        "Terraform",
        "Backend systems"
      ]
    },
    {
      "organization": "Reliance Jio",
      "role": "Software Intern",
      "dates": null,
      "narrative": "At Reliance Jio, I worked with React and Spring Boot on internal operational software. API integrations, notifications, and workflow software connected the interface to the systems behind it.",
      "areas": [
        "React",
        "Spring Boot",
        "API integrations",
        "Workflow software"
      ]
    },
    {
      "organization": "University of Auckland",
      "role": "Research Intern",
      "dates": null,
      "narrative": "My research internship at the University of Auckland focused on natural-language processing: extracting and classifying entities with CLAVIN and Stanford NER.",
      "areas": [
        "NLP",
        "Entity extraction",
        "Entity classification",
        "CLAVIN",
        "Stanford NER"
      ]
    }
  ],
  "research": [
    {
      "slug": "soft-body-simulation",
      "title": "Simulation for surgical robotics",
      "year": null,
      "status": "in-progress",
      "summary": "GPU-accelerated soft-body mechanics, differentiable physics, and graph-based models for surgical-robotics research at Johns Hopkins.",
      "question": "How can simulation connect models of soft tissue with observations of the physical world?",
      "areas": [
        "XPBD",
        "NVIDIA Warp",
        "Soft-body mechanics",
        "Differentiable physics",
        "GNNs",
        "Real-world calibration"
      ],
      "canonical_url": "http://localhost:3000/research/soft-body-simulation"
    },
    {
      "slug": "entity-extraction",
      "title": "Finding entities in language",
      "year": null,
      "status": "archived",
      "summary": "Entity extraction and classification research at the University of Auckland, using CLAVIN and Stanford NER.",
      "areas": [
        "NLP",
        "Entity extraction",
        "Classification"
      ],
      "canonical_url": "http://localhost:3000/research/entity-extraction"
    },
    {
      "slug": "skin-disease-detection",
      "title": "Skin-disease detection",
      "year": null,
      "status": "published",
      "summary": "Published research in skin-disease detection. This is a topic label; the exact publication title and citation have not yet been added.",
      "areas": [
        "Machine learning",
        "Skin-disease detection"
      ],
      "canonical_url": "http://localhost:3000/research/skin-disease-detection"
    },
    {
      "slug": "advertisement-generation",
      "title": "AI advertisement generation",
      "year": null,
      "status": "published",
      "summary": "Published research involving advertisement generation and Kolmogorov-Arnold Networks. This is a topic label pending the exact title and citation.",
      "areas": [
        "Generative systems",
        "Kolmogorov-Arnold Networks"
      ],
      "canonical_url": "http://localhost:3000/research/advertisement-generation"
    }
  ],
  "research_interests": [
    "Autonomous surgical robotics",
    "Simulation",
    "Differentiable physics",
    "Robot learning",
    "Sim-to-real",
    "Agents",
    "Agent reliability",
    "Post-training",
    "Evaluation"
  ],
  "companies": [
    {
      "slug": "univonest",
      "title": "Univonest",
      "subtitle": "An agentic marketplace",
      "summary": "A bilingual marketplace connecting cross-category procurement, negotiation, and real-time workflows. Selected for the Fuel Accelerator at the Johns Hopkins Pava Center; approximately 700 users.",
      "kind": "company",
      "role": "Founder & CTO",
      "areas": [
        "AI negotiation",
        "Deterministic guardrails",
        "Fine-tuning",
        "Real-time chat",
        "Seller verification",
        "Spatial discovery"
      ],
      "status": "Current operating status not yet recorded.",
      "canonical_url": "http://localhost:3000/building/univonest"
    }
  ],
  "projects": [
    {
      "slug": "bridgefill",
      "title": "BridgeFill",
      "subtitle": "Schema Registry & LLM Codegen",
      "summary": "A developer-time schema registry and integration generator. API providers publish OpenAPI contracts and code examples; consumers receive contract-checked integration files through MCP, REST, or a CLI.",
      "kind": "project",
      "areas": [
        "MCP",
        "OpenAPI",
        "TypeScript",
        "PostgreSQL",
        "API-key authentication",
        "Encryption"
      ],
      "status": "Public source and local setup instructions are available. Current hosted operating status is not verified.",
      "codeUrl": "https://github.com/Krishnan9074/Bridgefill",
      "canonical_url": "http://localhost:3000/building/bridgefill"
    },
    {
      "slug": "neuroassist",
      "title": "NeuroAssist",
      "subtitle": "Neurological screening research project",
      "summary": "A neurological assessment and support prototype combining symptom-based AI guidance, disorder-focused machine-learning models, a chatbot, and educational resources. Clinical validation is not documented.",
      "kind": "project",
      "areas": [
        "XGBoost",
        "Gemini AI",
        "React",
        "Clerk",
        "Educational resources"
      ],
      "status": "Research project; clinical validation has not been supplied.",
      "codeUrl": "https://github.com/Krishnan9074/NeuroAssist",
      "canonical_url": "http://localhost:3000/building/neuroassist"
    },
    {
      "slug": "adenstien",
      "title": "Adenstien",
      "subtitle": "A generative advertisement system",
      "summary": "A shopping and advertising prototype pairing personalized product recommendations with AI-generated scripts, speech, and short video ads. Built for the Walmart Sparkathon.",
      "kind": "project",
      "areas": [
        "Recommendation",
        "Conservative Q-learning",
        "Jaccard similarity",
        "LLMs",
        "TTS",
        "Video composition",
        "Kolmogorov-Arnold Networks"
      ],
      "status": "Public project source and a demo video are available. Production deployment is not verified.",
      "codeUrl": "https://github.com/Krishnan9074/Adeinstien",
      "canonical_url": "http://localhost:3000/building/adenstien"
    }
  ],
  "skills": [
    "AI agents",
    "Agent evaluation",
    "Model evaluation",
    "LLM evaluation",
    "Post-training",
    "Backend systems",
    "Production AI systems",
    "AI reliability",
    "Agent infrastructure",
    "Tool-using agents",
    "Model pipelines",
    "Structured retrieval",
    "Observability",
    "MCP",
    "LLM infrastructure",
    "PyTorch",
    "Differentiable simulation",
    "Graph neural networks",
    "Python",
    "TypeScript",
    "C++",
    "Java",
    "Next.js",
    "Node.js",
    "Spring Boot",
    "PostgreSQL",
    "Docker",
    "Terraform",
    "GCP",
    "AWS",
    "Azure",
    "Unix/Linux"
  ],
  "writing": [
    {
      "title": "Contracts before generation",
      "date": "2026-09-22",
      "updated": "2026-09-22",
      "description": "An introductory technical note on the boundary between generated code and the systems that accept it.",
      "category": "Technical",
      "tags": [
        "Contracts",
        "Integration",
        "AI systems"
      ],
      "language": "en",
      "canonical_url": "http://localhost:3000/writing/contracts-before-generation",
      "markdown_url": "http://localhost:3000/agent/writing/contracts-before-generation.md"
    },
    {
      "title": "Evaluation needs a denominator",
      "date": "2026-09-22",
      "updated": "2026-09-22",
      "description": "A short worked example about interpreting an agent success rate.",
      "category": "Research Notes",
      "tags": [
        "Evaluation",
        "Agents"
      ],
      "language": "en",
      "canonical_url": "http://localhost:3000/writing/evaluation-needs-a-denominator",
      "markdown_url": "http://localhost:3000/agent/writing/evaluation-needs-a-denominator.md"
    }
  ],
  "external_writing": [
    {
      "title": "Part 1 : Language-model mechanics for post-training",
      "platform": "Substack",
      "canonical_url": "https://vskrishnan.substack.com/p/language-model-mechanics-for-post"
    },
    {
      "title": "Two Ways to Build an Eye: Subretinal Photovoltaics and Cortical Stimulation",
      "platform": "Substack",
      "canonical_url": "https://vskrishnan.substack.com/p/two-ways-to-build-an-eye-subretinal"
    },
    {
      "title": "Beyond Naive RAG: A Step-by-Step Guide to Building Agentic RAG in 2026",
      "platform": "Medium",
      "canonical_url": "https://medium.com/@vkrishnan9074/beyond-naive-rag-a-step-by-step-guide-to-building-agentic-rag-in-2026-fceddd989c74"
    },
    {
      "title": "MCP Clients: Stdio vs SSE",
      "platform": "Medium",
      "canonical_url": "https://medium.com/@vkrishnan9074/mcp-clients-stdio-vs-sse-a53843d9aabb"
    }
  ],
  "booking_url": "https://cal.com/krishnan-v-s",
  "interests": [
    {
      "slug": "tennis",
      "title": "Tennis",
      "description": "One part of life away from the screen. A place for photographs, memories, and notes from the court as this archive grows.",
      "images": []
    },
    {
      "slug": "problems-and-puzzles",
      "title": "Problems and puzzles",
      "description": "I solve problems on Deep-ML and play puzzles on Matiks.",
      "images": []
    },
    {
      "slug": "reading",
      "title": "Reading",
      "description": "A personal reading list, with room for the ideas that linger. No books have been added yet.",
      "images": []
    }
  ],
  "books": [],
  "now": {
    "updated_at": "2026-09-22",
    "text": "My current interests include intelligent systems, simulation, and the questions that emerge when software meets the physical world. This page is a small, editable record of what has my attention."
  },
  "public_links": {
    "github": "https://github.com/krishnan9074",
    "linkedin": "https://www.linkedin.com/in/krishnan-v-s/",
    "x": "https://x.com/Krishnan9074"
  }
}