Shubhangi Gupta
Open Source & AI Ecosystem Builder | Product & DevRel | Community of 35K+ | Inclusive Tech Advocate 🏳️🌈
Delhi, India
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Shubhangi is a Product and DevRel leader building at the intersection of open source, AI, and inclusive tech communities.
She leads a 35,000+ member developer network and drives initiatives through Claude Code, Google Developer Groups Noida and Women Techmakers Delhi. A GitHub Campus Expert and speaker at multiple tech events like DevFest and MLH Hackcon, she champions open collaboration, equitable representation, and community-led innovation in AI and infrastructure.
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From Bias to Balance: Data-Driven Moves in Scaling Inclusive Open Source Communities
Past a few thousand contributors, the human review systems that once felt fair quietly begin to fail. For open source projects at scale, selection committees burn out, and unconscious exclusion moves in. Mentorship slots go to the loudest voices. Months later, CNCF DevStats shows the damage.
24 months, one deployed stack, three FOSS communities with more than 15,000 contributors across APAC.
The talk presents an agentic contributor-operations stack we built on vendor-neutral primitives.
MCP servers wrapping GitHub, Slack, CHAOSS, and DevStats; single-purpose agents with AGENTS.md defined scope, gated by an audit layer with human-in-the-loop checkpoints.
Through the architecture walkthrough, attendees will see,
1. What the agents were and weren't allowed to do
2. Three production failures, told plainly, and how we recovered
3. Bias-prevention protocols that survived production
Leaving with a tested playbook, a deployment roadmap, and a clear sense of the way ahead.
Beyond transcription: deploying Whisper for neurodivergent-aware voice inference
Most voice interfaces flatten speech into text and discard everything else; they were never designed to "listen" to human intent.
With 15-20% of the global population neurodivergent, this is an accessibility failure at infrastructure scale. This session presents a voice-first research prototype (not a diagnostic tool) that uses PyTorch-based Whisper to extract speech pattern markers: pacing, hesitation, repetition, and adapt responses based on those signals.
The speaker walks through containerising the Whisper inference pipeline, deploying it on Kubernetes with GPU acceleration, and designing adaptive systems that preserve privacy by keeping voice data local. Attendees will see a live demo comparing standard and ADHD speech patterns, learn how to build voice interfaces users can tailor to their own communication style, and leave with a forkable repo containing Dockerfiles, K8S manifests, and the full adaptive response pipeline.
Shubhangi Gupta
Open Source & AI Ecosystem Builder | Product & DevRel | Community of 35K+ | Inclusive Tech Advocate 🏳️🌈
Delhi, India
Actions
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