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finding pebbles
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finding pebbles

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@MozillaIndia @webcompat @fossasia @pClub-gu @asq-ai @NIU-DATA-Lab

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akhilpandey95/README.md

About Me

I am Research Scientist at the Center for Science of Science and Innovation working for Dashun Wang at the Kellogg School of Management, Northwestern University. As a Research Scientist, I oversee the lab's overall AI efforts, data analytics, and data management. I work closely with other team members to ensure these initiatives align with the lab's goals and contribute to its broader research objectives. My research interests lie in the intersection of Large Language models, Science of Science, Representational Learning, and Uncertainty Quantification.

Previously, I was a Ph.D student advised by Dr. Hamed Alhoori, and my dissertation fully funded by the NSF grant. focussed on building a predictive modeling framework to investigate the Reproducibility crisis in AI. Previously, I was a Givens Research Associate and an Argonne Leadership Computing Facility Graduate Student researcher.

My most recent project involves using symbolic programming to build Neural Architecture Search pipelines for Graph Neural Networks.

  • πŸ”­ I’m currently working on fine-tuning large language models, implementing LLM agents, LLM's + Graphs.
  • 🌱 I’m currently exploring Ways bring GraphRAG to the larger scholarly ecosystem, and Science of Science data
  • πŸ‘― I’m looking to collaborate on Building microservices for LLMs; Agentic LLM tooling as a service layer
  • πŸ€” I’m always looking for help with Building Knowledge Graphs within Citation Networks
  • πŸ’¬ Ask me about Large Language models, Graph Learning, Uncertainty Quantification, Neural Architecture Search.
  • πŸ“« How to reach me: @akhilpandey95
  • πŸ˜„ Pronouns: (he/him)
  • ⚑ Fun fact: Haskell has type inference, meaning it can automatically determine the type of a data by looking at how it is created.

Active projects:


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  1. gnnNAS gnnNAS Public

    Work as part of ANL summer 2022 research with emphasis on utilizing symbolic programming to perform NAS on graph neural networks

    Python 2

  2. uncertainty uncertainty Public

    Work as part of ANL summer 2020 research on uncertainity quanitification methods in graph neural networks

    Python 1

  3. numgo numgo Public

    Numerical Calculations and Operations in Go

    Go 6

  4. FAT12 FAT12 Public

    An implementation of a FAT 12 system simulation in C

    C 3 1

  5. reproducibilityproject/effortly reproducibilityproject/effortly Public

    A preliminary analysis into the effort required for reproducing computational science scholarly articles.

    Jupyter Notebook 1

  6. reproducibilityproject/scholarlyreprograph reproducibilityproject/scholarlyreprograph Public

    Exploiting Graph Structures for Reproducibility Badge Prediction in Academic Papers

    1