Sep 2026
7 Mon 03:00 PM – 11:59 PM IST
8 Tue 03:00 PM – 11:59 PM IST
9 Wed 03:00 PM – 11:59 PM IST
10 Thu 03:00 PM – 11:59 PM IST
11 Fri 03:00 PM – 11:59 PM IST
12 Sat
13 Sun
Submitted Sep 2, 2026
{Submission type - choose one:
If talk/session proposal, showcase, or poster
{Describe your session in 2 paragraphs.}
{Mention 1-2 takeaways from your session.}
{Which audiences will benefit most from your session?}
{Add your bio: who you are, where you work, and any relevant context.}
{Add a link to draft slides, if available. PDF/PPT preferred. Please make sure comments are enabled.}
{Optional: What don’t you know yet, or what do you want help with?
This can be an open question, unresolved challenge, missing dataset, technique you are unsure about, implementation blocker, or a place where you want critique.}
{Optional: match making tags - choose any that apply:
{Topic/domain tags - choose 2-3 broad tags that describe your session or problem space.
Examples: data for good, causal inference, synthetic data, computer vision, fraud, ecology, healthcare, governance, evaluation, safety, education, public sector, climate, finance.}
If problem/reverse CfP
{Describe the problem in one short card: what is broken, blocked, unclear, or worth exploring?}
{What kind of help would be useful? Choose any that apply:
{Topic/domain tags - choose 2-3 broad tags that describe your problem space.
Examples: data for good, causal inference, synthetic data, computer vision, fraud, ecology, healthcare, governance, evaluation, safety, education, public sector, climate, finance.}
{Your role as problem owner: by submitting this, you are the default owner of this problem card. Are you willing to be contacted before the event for matching or clarification?}
{Add name, affiliation, and short bio. Make it intriguing!}
If problem exchange facilitator/helper
{How do you want to help? Choose any that apply:
{What can you help with? Choose any that apply:
{Topic/domain tags - choose 2-3 broad tags that describe where you can be useful.
Examples: data for good, causal inference, synthetic data, computer vision, fraud, ecology, healthcare, governance, evaluation, safety, education, public sector, climate, finance.}
{Availability: are you available before the event for light-touch matching/facilitation?}
{Add name, affiliation, and short bio. Make it intriguing!}
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