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KITS Student Selected Among Ten Quantum Elite Participants
Ganta Chaitra Deepika is a college student from KITS.
She was chosen as one of 10 special participants in a global quantum programme.
Quantum computing is a way of using advanced computers to solve certain problems.
The programme received more than 64,000 registrations from 33 countries.
Students passed through several rounds before the final 10 were selected.
The programme lasted nine months and included lessons, projects and guidance from mentors.
Chaitra worked on improving how orders can be organised using quantum computing.
Her college leaders, teachers and fellow students congratulated her.
Ganta Chaitra Deepika, a third-year B.Tech student at KITS, was selected as one of 10 Quantum Elite participants.
The WISER Global Summer Programme 2026 received 64,436 registrations from 33 countries.
After multiple selection stages, 108 students were shortlisted before the final selection of 10 participants.
The nine-month programme covered quantum algorithms, practical learning, industry challenges and mentorship.
Chaitra Deepika developed ‘Quantum Flow: Intelligent Order Optimisation’ using quantum computing for order-optimisation challenges.
- Who
- Ganta Chaitra Deepika, a third-year B.Tech student at KKR and KSR Institute of Technology and Sciences.
- What
- She was selected as one of 10 Quantum Elite participants in the WISER Global Summer Programme 2026.
- Where
- KKR and KSR Institute of Technology and Sciences in Vinjanampadu, Guntur district.
- When
- The programme is identified as WISER Global Summer Programme 2026; its duration was nine months.
- Why
- She was selected through a multi-stage process and worked on a quantum-computing project focused on order optimisation.
Key facts
- Student
- Ganta Chaitra Deepika
- Institution
- KKR and KSR Institute of Technology and Sciences
- Programme
- WISER Global Summer Programme 2026
- Final selection
- 10 Quantum Elite participants
- Registrations
- 64,436 from 33 countries
- Shortlisted students
- 108
- Project
- ‘Quantum Flow: Intelligent Order Optimisation’
Sources
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