Event Data.Gov.in

We welcome you to participate in the Online Hackathon on data-driven innovation for Aadhaar, organised by the Unique Identification Authority of India (UIDAI) in association with National Informatics Centre (NIC), Ministry of Electronics and Information Technology (MeitY).

UIDAI has made anonymised datasets of Aadhaar enrolment and updates, available to the participating teams to identify meaningful patterns, trends, anomalies, or predictive indicators and translate them into clear insights or solution frameworks that can support informed decision-making and system improvements.

PARTICIPATION

• This contest is open to any student enrolled in any accredited Indian university/Institution.
• Participant(s) must be at least 18 years of age on 1st Jan 2026.
• Participants can participate individually or form teams – ideally heterogeneous, consisting of people with different skill sets – up to a maximum of five members, including the Team Lead.
• The team lead must submit his/her student ID card along with those of the team members during project submission.
• People associated with service delivery at UIDAI and NIC are not allowed to participate in this Hackathon.

LOGIN AND REGISTRATION

All participants must register/sign up at JanParichay. A registered user can directly login at https://event.data.gov.in and submit required details to participate in the Hackathon. It is expected that the participants would submit accurate and up-to-date details and they have to confirm this before submission.

A team leader and each team member can be part of only one team. Any one of the team members can create a team for participation.

STRUCTURE OF THE HACKATHON

• Event will be conducted online.
• There would be a time of 15 days from the launch of the Hackathon to register and submit an idea.
• Interested candidates would access the event registration and submission links at challenge page.
• Shortlisted teams will be invited to make presentations before UIDAI officials and the Jury Panel. An award ceremony will be organized by UIDAI in either Delhi or Bengaluru (venue to be notified in due course). UIDAI will reimburse the travel expenses incurred by the shortlisted teams.

#UIDAI Data Hackathon 2026 Winners

S.No.	Prize Category	Idea/Concept	Team ID, Lead and Member
1	First Prize Winner	Our approach analyzes India Aadhaar enrollment using 4.35 million records across 36 states 960 districts and 19700 pincodes. We developed a framework integrating 50 plus features through 14 external APIs including Open Meteo Census 2011 NITI Aayog SDG indices and RBI statistics. Our methodology combines statistical analysis ANOVA and Kruskal Wallis with machine learning 117 models Random Forest XGBoost LightGBM and Bayesian causal networks to uncover temporal geographic socioeconomic and climate patterns. Key findings reveal geographic inequality Gini 0.707 inverse HDI enrollment relationships indicating successful penetration in underserved regions weekend efficiency gains 33 percent higher and significant climate impacts. We achieve 99.97 percent classification accuracy R squared greater than 0.85 for demand forecasting and identify 20 priority underserved districts in UP and Bihar. Results provide actionable policy recommendations for optimizing coverage and resource allocation.	Id: UIDAI_549, Lead: Aheli Poddar, Member:Shuvam Banerji Seal, Alok Mishra
2	Second Prize Winner	This project presents a data driven strategy to optimize UIDAI Aadhaar operations using 5.4 million enrolment and update records We introduce the Outreach Priority Index OPI to rank districts using coverage gaps youth concentration migration pressure and enrolment trends enabling targeted deployment of mobile units staffing update kiosks and biometric devices to reduce failures and improve service reliability	Id: UIDAI_10137 Lead: Sumit Kumar, Member: Ansh Patidar
3	Third Prize Winner	Aadhaar Data Intelligence and Migration Patterns Analysis An analytical framework transforming UIDAI Aadhaar data into actionable policy insights KEY INNOVATIONS 1 MIGRATION INDEX for population mobility analysis 2 ANOMALY DETECTION using Z score analysis 3 DIGITAL DESERT MAPPING for underserved areas 4 DATA QUALITY FRAMEWORK for state name normalization METHODOLOGY Multi level analysis from State to District to Pincode Cross dataset correlation Time series and age pattern analysis 12 visualizations with reproducible Python code	Id: UIDAI_4136 Lead: Satyam
4	Fourth Prize Winner	Child Biometric Gap Index – CBGI – A Data Driven Framework for Prioritizing District Level Interventions in Mandatory Biometric Updates	Id: UIDAI_1867 Lead: Madhav Dogra
5	Fifth Prize Winner	Predictive Gap Analysis Engine for Mandatory Biometric Updates MBU Gap Analyzer is a predictive analytics system designed to identify children who have not completed their Mandatory Biometric Updates in the Aadhaar system Children must update their biometrics at ages 5 and 15 years If they miss these updates their Aadhaar becomes inactive blocking access to school admissions scholarships mid-day meals and Direct Benefit Transfers Our solution uses a 3-layer approach Cohort Tracking to calculate district-wise compliance gaps Service Desert Identification using K-Means clustering to find underserved areas and Demand Forecasting using LSTM deep learning to predict future MBU workloads This helps UIDAI proactively deploy resources to prevent children from losing government benefits	Id: UIDAI_1494, Lead: Piyush Verma, Member: Stiwart Stance Saxena

Problem Statement: Unlocking Societal Trends in Aadhaar Enrolment and Updates

Identify meaningful patterns, trends, anomalies, or predictive indicators and translate them into clear insights or solution frameworks that can support informed decision-making and system improvements.

For all queries related to UIDAI Data Hackathon, please contact:

To: sitaa-support[at]uidai[dot]net[dot]in and CC: ndsap[at]gov[dot]in

PRIZES

Top 5 most innovative submissions will be awarded the following prizes:

These terms and conditions govern the Online hackathon on data-driven innovation on Aadhaar- 2026. By participating in the hackathon, one is deemed to have accepted the terms and conditions mentioned below, as well as the terms of use of the OGD Platform India.

GENERAL TERMS & CONDITIONS

Please read these Terms and Conditions carefully as they apply to the Hackathon. To be eligible to participate and declare as shortlisted or winners in the Hackathon, the participants must accept these Terms and Conditions:

• Participants must not provide any false information in the registration and team creation process.
• Participants must keep their contact information accurate and up-to-date.
• Only a single MyGov/Janparichay/OGD account is permitted for an individual or a team. If more than one account exists for the same candidate, then it will automatically result in the disqualification of the candidate.
• As a part of the submission, the contestant certifies the originality and ownership of the solution as detailed/described in the documentation uploaded at the time of submission.
• The participant(s) must ensure that his/her/their work has not been previously published or awarded.
• The participants will not use this contest to do anything unlawful, misleading, malicious, or discriminatory.
• The winning submissions must be maintained in working condition by the contestant(s) for a period of one year. No functional enhancements are expected, but all bugs identified according to the description in the documentation should be fixed immediately on reporting.
• If any participant is determined to have violated the terms of the contest, UIDAI have all rights to disqualify the participant without prior notice.
• If the Applications shortlisted do not meet the expectations of the Jury, Jury has the discretion and the right, not to confer an award in one or more categories/ subcategories.
• The Jury’s decision shall be final and cannot be challenged.
• UIDAI reserves the right to change the terms and conditions, if required.
• The organizers reserve the right in their sole discretion to withdraw participation of any individual/team from the event or reject any submission at any point of time during the process.

Participants must submit one consolidated PDF containing the following sections:

1. Problem Statement and Approach: A concise description of the problem being addressed and the proposed analytical or technical approach.
2. Datasets Used: A clear description of the dataset(s) and columns used for the analysis. Participants must use the Aadhaar enrolment and/or update dataset provided by UIDAI.
3. Methodology: A detailed explanation of the methodology adopted, including data cleaning, preprocessing, and any transformations applied before analysis.
4. Data Analysis and Visualisation: A description of key findings and insights, and the visualisations or infographics developed. Participants must also include code files or notebooks used for the analysis (in the PDF itself).

Note: Shortlisted teams may be asked to submit the code file/notebook separately on GitHub.

All applications will be rated on the parameters listed below:

• Data Analysis & Insights:
  • Depth, accuracy, and relevance of univariate/bivariate/trivariate analysis
  • Ability to extract meaningful findings from the data
• Creativity & Originality:
  • Uniqueness of the problem statement or solution, innovative use of datasets
• Technical Implementation:
  • Code quality, reproducibility, and rigour of approach, appropriate methods, tooling, and documentation
• Visualisation & Presentation:
  • Clarity and effectiveness of data visualisations, Quality of written report or slides
• Impact & Applicability:
  • Potential for social/administrative benefit, Practicality and feasibility of insights/solutions