Skip To Main Content
Piyush Gupta on Muck Rack

Piyush Gupta

Waltham
As seen in: LinkedIn, IMDb, Medium, MSN India, The New York Times, ET Government, Financial Times, Nature, The Economic Times, The Times of India and
The NavDx test is the first and most clinically validated liquid biopsy test for early detection of HPV+ cancer recurrence.
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Piyush

Contact Piyush, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Building a Community Plugin Marketplace for OWASP OWTF (GSoC 2026)

|
By Piyush Gupta
| DEV Community
This is a write-up of what I built for Google Summer of Code 2026. I worked with the OWASP Foundation on OWTF (Offensive Web Testing Framework) over the summer. The rest of this post is basically: what the project was, why it needed to exist, how I built it, what went wrong along the way, and what I took away. What I built A Community Plugin Marketplace on top of OWTF. Any logged-in OWTF user could upload a Python plugin through the web UI.
Open in Who Shared Issue with article?

From Sandbox to Review Queue: My GSoC 2026 Project with OWASP OWTF

|
By Piyush Gupta
| DEV Community
When I started GSoC in May, my plan was to build a runtime sandbox for community plugins. By week two my mentor had talked me out of it, and I ended up spending the rest of the summer building a review queue instead. This post is about how that happened and what I actually shipped.
Open in Who Shared Issue with article?

Machine Learning for Predicting Delayed Graft Function and Graft Survival After Kidney Transplantation: A Systematic Review and Meta-Analysis

|
By Shekhar Gogna, Piyush Gupta, David Walls
| Preprints.org
You are already at the latest version Background/Objectives: Machine-learning (ML) models have been proposed to improve prediction of delayed graft function (DGF) and graft survival after kidney transplantation. Whether they provide better predictive performance than conventional regression remains uncertain. We systematically reviewed prediction models for both outcomes and assessed the quality of the supporting evidence.
Open in Who Shared Issue with article?
See all 954 licensed articles (966 Total)