Regional Ideathon

The Regional Ideathon is a one-day, offline-only innovation sprint designed for student teams eager to participate in a fast-paced challenge without being part of the larger hackathon journey.

• Standalone Track – Teams apply separately for the Ideathon and participate only on the designated day in their city.
• One-Day Format – No prior or post-event commitments; everything happens in a single day.
• Focused Innovation – Teams brainstorm, build, and pitch their solutions during the event.
• Same-Day Recognition – Winners are announced on the spot, with a dedicated prize pool exclusive to this track.

Prizes

Winners of the Regional Ideathon will receive exclusive awards from a separate prize pool, ensuring recognition for their creativity and innovation.

Regional Demo Day

The Regional Demo Day is an exclusive offline stage for teams who applied through the AMD Slingshot contest, submitted their ideas, and successfully cleared the shortlisting process. These selected teams will be invited to their respective city to showcase their prototypes in front of experts and mentors.

• Exclusive for Slingshot Teams – Only shortlisted teams from the AMD Slingshot contest are eligible.
• Prototype Showcase – Teams present their solutions, demonstrating innovation, feasibility, and impact.
• Expert Jury – Solutions are evaluated by industry leaders and AMD professionals.
• Path to the Finale – From each city, one team will be shortlisted to advance to the National Grand Finale.

1. Generative AI for everyone

Essence: Open up creation—text, image, audio, video, code—to any student, club, or campus team.

Why it matters: College life is full of ideas but short on time, skills, and budgets. Tools that lower the barrier to create a level playing field.

Exploration paths:
• Multimodal creativity suites for fests, events, and classrooms (draft → design → publish).
• Low/no-code “app makers” that let non-CS students assemble useful AI utilities.
• Responsible GenAI (attribution, bias checks, content filters) built into the flow.
• Efficient/on-device options for speed, privacy, and cost control.
• Collaboration features so creators, designers, and writers can co-produce seamlessly.

2. AI in Education & Skilling

Essence: Personalise learning with explainable, multilingual support that boosts confidence and outcomes.

Why it matters: Students learn differently; adaptive guidance and clear feedback reduce anxiety and improve mastery.

Exploration paths:
• Concept coaches/tutors with stepwise hints and mastery tracking.
• Rubric-aware feedback on essays, presentations, code, and labs.
• Study planners using spaced repetition; exam readiness insights.
• Multilingual (Indian languages) content and voice interfaces for inclusivity.
• Academic integrity: originality checks, citation helpers, anti-cheat by design.

3. Future of Work & Productivity

Essence: Reimagine everyday workflows for students, researchers, and early professionals.

Why it matters: Time saved on admin and busywork is time earned for deep work and creativity.

Exploration paths:
• Research copilots that find sources, manage notes, and draft with citations.
• Smart orchestration across mail, calendar, files, and chat to reduce friction.
• Private-by-default summaries of classes/meetings; offline/edge fallbacks.
• Task automation for repetitive processes (forms, logs, reminders).
• Team knowledge hubs that capture tacit know-how from projects and clubs.

4. Sustainable AI & Green Tech

Essence: Use AI to cut waste, energy use, and emissions on campus and in nearby communities.

Why it matters: Sustainability goals need data-driven action students can influence today.

Exploration paths:
• Energy/water dashboards for hostels, labs, and facilities with actionable nudges.
• Agri-tech decision support (irrigation, pests, soil health) for college farms/incubators.
• Low-power sensing + efficient inference for continuous monitoring.
• Air-quality and climate insights tied to local policy or campus behaviours.
• Upcycling/e-waste flows with computer vision and simple logistics planning.

5. AI for Social Good

Essence: Build inclusive tech that improves access, wellbeing, and resilience.

Why it matters: Campuses reflect wider society—solutions designed here can scale to communities.

Exploration paths:
• Assistive tools for vision, speech, reading, and neurodiverse learners.
• Verified, multilingual health-information companions (no diagnosis); wellbeing nudges.
• Crisis mapping/alerts for floods, heat, or safety—with humans in the loop.
• Inclusion-by-design UX (contrast, captions, screen-reader support).
• Community partnerships (NSS/NGOs) for pilots and feedback.

6. AI + Cybersecurity & Privacy

Essence: Safer digital experiences for students and institutions—simple, explainable, effective.

Why it matters: Phishing, malware, and data misuse hit learners hard; guardrails protect trust.

Exploration paths:
• Early-warning and teach-back for phishing/malware with plain-language guidance.
• Privacy-preserving analytics for labs/classrooms (no raw PII exposure).
• Consent-first identity/fraud signals; secure access flows for clubs and labs.
• Explainable security so users understand risks and actions.
• Starter “digital hygiene” companions for first-year students.

7. AI in Consumer Experiences

Essence: Personalised, delightful interactions in retail, media, travel, and campus services.

Why it matters: When systems explain choices and respect budgets, people trust and engage more.

Exploration paths:
• Transparent recommenders (“why this”) for canteens, events, and content.
• Conversational shopping/booking assistants with budgets and constraints.
• Travel and campus-life planners balancing time, cost, accessibility, and interests.
• Creator tools that help clubs/teams produce consistent, on-brand media.
• Feedback loops that prevent filter bubbles and promote discovery.

8. AI for Smart Cities (Campus as Micro-City)

Essence: Treat campus as a living lab for mobility, utilities, safety, and planning.

Why it matters: Small, well-measured wins on campus can model scalable urban solutions.

Exploration paths:
• Traffic/footfall insights for shuttles, gates, and events; safe-mobility nudges.
• Smart waste/water management with simple sensors and predictive routing.
• Space-utilisation analytics and lightweight digital twins for facilities.
• Predictive maintenance for labs/classrooms to reduce downtime.
• Edge/low-latency designs for responsiveness and cost efficiency.

9. Open Innovation

Essence: Bring bold ideas that don’t fit neatly above—surprise us with originality and impact.

Why it matters: Breakthroughs often emerge outside categories; this is the space to explore them.

Exploration paths:
• Novel agents/modalities, regional-language AI, or fresh retrieval/interaction paradigms.
• Low-resource or edge-first approaches that run on everyday devices.
• New human–AI collaboration UI patterns with clear user value and safeguards.
• Cross-pollination: combine sustainability + education, or security + consumer UX.
• Measurable outcomes and thoughtful ethics from day one.