Ayush Shrivastava
Data ScientistPhD Student at UMich
University of Michigan
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
PhD Student at UMich
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Michigan
Data Scientist
June 25, 2026 – Present
cmrw
June 3, 2025 – June 9, 2025
Official PyTorch implementation of Self-Supervised Spatial Correspondence Across Modalities, CVPR 2025.
View Projectgmrw
September 10, 2024 – November 4, 2024
Official PyTorch implementation of Self-Supervised Any-Point Tracking by Contrastive Random Walks, ECCV 2024.
View Projectvln-chasing-ghosts
December 4, 2019 – January 10, 2020
Code for 'Chasing Ghosts: Instruction Following as Bayesian State Tracking' published at NeurIPS 2019
View Projectmammogram-project
August 26, 2017 – August 26, 2017
Various implementation and analysis on MIAS Mammogram Dataset in Python
View Projectmemento-app
August 25, 2017 – October 27, 2017
Android App which serves as an AI assistant for human memory
View Projectgs-quantify2016
August 25, 2017 – October 27, 2017
Questions attempted in GS Quantify conducted by Goldman Sachs
View Projectdbms-project-parliament-elections
August 24, 2017 – October 27, 2017
This project is a online voting system which serves the full functionality of Parliament Elections conducted in an institute. It is Django Framework in Python and RDBMS is built in MySQL.
View ProjectMammogram-Classification-using-GLCM-Features
June 3, 2016 – June 3, 2016
Detection and Classification of breast cancer in mammogram using textual and statistical features of image
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards academic and research-oriented data science, particularly in computer vision and NLP. This aligns well with roles requiring innovation and deep technical problem-solving. However, the projects are predominantly personal and academic, with limited insight into collaborative or industry-specific work environments. The single listed professional experience as a 'Data Scientist' at the University of Michigan is current but lacks details, making it difficult to fully assess cultural fit for a corporate or fast-paced startup environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions suggest an ability to work on complex problems, but there is no information on collaboration, communication, or problem-solving approaches in a team setting.