Research Mentorship & Collaboration Application

We welcome motivated students and collaborators to join a wide range of ongoing and future research projects. Our work spans multiple areas of artificial intelligence and applied domains — from reinforcement learning, multi-agent systems, autonomous driving, and generative AI, to finance, healthcare, and beyond.

As a participant, you will have the opportunity to:

  • Work towards publications in leading venues such as NeurIPS, ICML, ICRA, AAAI, IJCAI, IEEE IV, IEEE ITSC, WACV, and even Nature sub-journals depending on project scope and quality.

  • Increase your academic impact by contributing to joint projects that aim for visibility, citations, and long-term recognition in the research community.

  • Gain hands-on experience with advanced datasets, simulators, and machine learning frameworks.

  • Receive structured mentorship covering both technical research and paper writing, enhancing your ability to publish independently in the future.

  • Build your academic profile through collaborations across universities and industry partners, with potential for recommendation letters and professional references.

  • Explore flexible projects tailored to your interests — from algorithmic innovation to applied domains like FinTech, Healthcare AI, and Autonomous Systems.

This program is designed not only to accelerate your learning but also to amplify your academic visibility and publication record.

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Full Name *
Email *
Current Institution & Program *
Current Status *
Collaboration Type *
Required
Work Modality Preference *
Research Interests *
Required
Core Strengths *
Required
Target Venue(s) (e.g., NeurIPS, ICML, IEEE IV)
Motivation Statement (≤ 200 words)
Availability (weekly) *
Earliest Start Date
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DD
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YYYY
Availability Duration *
Time Zone *
Preferred Working Style *
Communication Channels *
Required
Location *
Hardware Access *
Required
Tools & Frameworks *
Required
Domain Experience
Publications (links, up to 3, optional)
Profile Links (website / GitHub / Scholar) *
Referee (optional)
How did you hear about us?
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CV / Resume Link (Google Drive, Dropbox) *
Research Slides Link (optional)
Best Paper / Technical Report Link (optional)
Consent & Data Use *
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