akhilpandey95 Goto Github PK

followers: 84.0 following: 9.0 repos: 45.0 gists: 1.0

Name: Akhil Pandey

Type: User

Company: @NIU-DATA-Lab

Bio: PhD candidate, DATA Lab (https://alhoori.github.io). 💙💜💖

Twitter: akhilpandey95

Location: Chicago, IL

Blog: https://akhilpandey95.github.io/

🏡

About Me

I'm a Ph.D student working on addressing the Reproducibility crisis in AI. I am advised by Dr. Hamed Alhoori, and my research is fully funded by the NSF grant.

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

🔭 I’m currently working on Positive-Unlabelled Learning, Graph Learning, and AutoML.
🌱 I’m currently exploring Ways to exploit GraphGym to and build AutoML pipelines for Graphs
👯 I’m looking to collaborate on NLP applications of Graph Neural Networks
🤔 I’m looking for help with Building Knowledge Graphs within Citation Networks
💬 Ask me about Graph Learning, Uncertainty Quantification, AutoML, Neural Architecture Search.
📫 How to reach me: @akhilpandey95
😄 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:

Akhil Pandey's Projects

akhilpandey95

akhilpandey95.github.io

Fully rendered web pages for https://akhilpandey95.com

altpred

An independent study trying to understand the relationship between scholarly articles and scholarly reference indicators

arduino-gesture-module

Different projects done on arduino micro-controller board

atlanta

Understanding the economic story of atlanta using relay bike share ride statistics

bucket

Link Sharing on steroids

cocoa-hugo-theme

Responsive Hugo blog theme

commute

Visualizing a weeks commute using geo spatial data

config

Includes all the Config files stored in my machine.

cs228-notes

Course notes for CS228: Probabilistic Graphical Models.

cs651

Comparing the efficacy of Graph Networks in predicting the scholarly impact of articles

cs680

A repository to store all the information useful for the course on neural networks | cs680

csci658

Coursework, Literature, and programs utilized for CSCI 658 - Natural Language Processing II

datasets

A collection of datasets ready to use with TensorFlow

deepgraphcnnfortexts

deepuq

Bayesian Uncertainty Quantification by Deep Generative Model

dissertation

Experiments, Literature, and programs utilized towards my doctoral dissertation titled "Effort of Reproducibility: A new paradigm in research reproducibility"