# Vedaant Jain > SWE @ Kumo.AI | Mathematics & Computer Science at UIUC Location: San Francisco, California, United States Profile: https://flows.cv/vedaantjain ## Work Experience ### Software Engineer @ Kumo Jan 2026 – Present | United States Creating the future Kumo infrastructure with Rust and using some really fun algorithms to do it. Establishing a scalable explanation system for gnns too. ### Machine Learning/Systems Researcher @ University of Illinois Urbana-Champaign Jan 2023 – Jan 2025 | Urbana, Illinois, United States Publications: 1. Jain V, Alves Feitosa F, Kreiman G (2024). Is AI fun? HumorDB: a curated dataset and benchmark to investigate graphical humor. ICCV 2025 arXiv: 2406.13564. 2. Chaudhary I, Jain V, Singh G (2024). Decoding Intelligence: A Framework for Certifying Knowledge Comprehension in LLMs. AISTATS 2026, SeT LLM@ICLR 2024, arXiv: 2402.15929 [cs.AI]. 3. I Chaudhary, V Jain, A Singh, K Sachdeva, S Ranu, G Singh (2025). Lumos: Let there be Language Model System Certification. arXiv preprint arXiv:2512.02966 **Focal Lab** Implemented probabilistic certification framework for LLM knowledge comprehension via Knowledge Graphs using PyTorch/Huggingface, evaluating 8 models on few-shot medical QA via distributed inference on supercomputing clusters. Identified adversarial input distributions that cause up to a 15% performance drop in models (e.g., Gemini-1.5-Pro) under natural prompt noise, informing robust model design. **Ge Lab** Improved Sampling of discrete diffusion based Graph Neural Networks (GNNs) models for inverse protein folding with information theory and entropy. ### Software Engineer Intern @ Kumo Jan 2025 – Jan 2025 | Mountain View, California, United States Scoped and built a deterministic end-to-end, full-stack code generation system using compiler principles to automatically translate Kumo UI entities into Python SDK code reducing manual authoring time by over 90%. Designed and executed 120+ experiments and reduced search space by 75% for 10 hyperparameters for Graph Transformers (GT). Developed synthetic datasets and trained custom GNN models outperforming baselines by an average of 10% for pre-sales engagements with about 5 enterprise clients. Enabled large file upload feature supporting > 1GB local uploads, resolving critical pain points for multiple enterprise customers. Delivered customer-facing tutorial notebooks for Kumo-RFM product release. ### Software Engineer Intern @ Metaphor Data Jan 2024 – Jan 2024 Developed CI/CD integrated comprehensive testing framework with synthetic test-data generation for LLM and RAG pipelines, improved performance by 20%. Pioneered CLI tool and 4 API endpoints for batch transactions across 4 data asset types. Implemented automatic GraphQL query generation to accelerate development. Worked with Azure OpenAI, TypeScript, Jest, CI/CD, Python, PyTest, MongoDB, GraphQL. ### Undergraduate Student Researcher - Kreiman Lab @ Harvard Medical School Jan 2023 – Jan 2024 | Boston Introduced Novel Dataset on humor detection for Vision and Vision-Language models. arXiv: 2406.13564 Worked with PyTorch, DeepSpeed, Huggingface for model training and evaluation. For human data collection, designed web psychophysics experimets with JavaScript, AWS Lambda, HTML/CSS, and Amazon S3. ### Software Developer @ UIUC TheorieLearn Jan 2024 – Jan 2024 | Urbana, Illinois, United States Full stack development of 12 new resources to aid learning the Algorithms class at UIUC: https://theorielearn.github.io/ ### SPIN Intern @ National Center for Supercomputing Applications Jan 2023 – Jan 2024 | Urbana-Champaign Area Developed and presented a poster at the NCSA student conference on using Diffusion Models and Inpainting for Parkinson’s Disease simulation on facial features achieving performance 6% above previous baseline. ### Head of AI/ML @ Disruption Lab at Gies Jan 2023 – Jan 2024 | Urbana-Champaign Area Led 10 AI project teams totaling 100+ students, achieving 91% client success rate, including AMD. Projects spanned LLM-guided web crawling, virtual classrooms, and malware detection. Developed 5 training modules on LLMs, orchestration frameworks, and Computer Vision, for members with varying familiarity ### Technical Team Lead @ Disruption Lab at Gies Jan 2023 – Jan 2023 | Urbana-Champaign Area ### SWE @ Disruption Lab at Gies Jan 2022 – Jan 2023 | Urbana-Champaign Area Working on a research project about detecting malware using hardware data and ML. Affiliated with AMD ### Co-Lead Software; Robot Construction Member @ FIRST Jan 2021 – Jan 2022 | India Our team was the Runner-s Up Alliance Captain(2nd place) at First Tech Challenge India, a competition in robotics. We also won the Connect Award for our team's efforts regarding community outreach. Additionally, we were also nominated for the Control Award for software innovation with our robot. ### Intern @ AirV Labs Jan 2021 – Jan 2021 Worked with Unity to develop AR applications. Trained deep learning models(CNNs) with PyTorch and integrated it into the Unity app. ## Education ### Bachelor's degree in Mathematics and Computer Science University of Illinois Urbana-Champaign ### High School Diploma in Mathematics and Computer Science UWC Mahindra College ## Contact & Social - LinkedIn: https://linkedin.com/in/vedaant-jain - GitHub: https://github.com/ethvedbitdesjan --- Source: https://flows.cv/vedaantjain JSON Resume: https://flows.cv/vedaantjain/resume.json Last updated: 2026-04-10