Human Presence AI™ Scholars Fellowship

Deep research on per-user, per-conversation, and per-tenant memory scoping. Explore vector-based semantic retrieval with recency weighting, memory lifecycle management, and techniques for efficient query across tenant hierarchies.

Target Venues

ACL, EMNLP, NeurIPS

Ideal Candidate

PhD in NLP/IR with RAG or memory-augmented model experience

Investigate transition mechanisms from text chat to video call while preserving full conversational context, memory state, and persona configuration. Design interaction patterns that maintain continuity across modalities.

Target Venues

CHI, CSCW, IUI

Ideal Candidate

PhD in HCI or multimodal AI

Develop models for exponential decay, log-recency weighting, and attention-based relevance scoring across multi-session interactions. Incorporate user feedback to refine memory importance over time.

Target Venues

AAAI, ICLR

Ideal Candidate

PhD in ML/AI with temporal models or continual learning

Extend memory retrieval to multilingual contexts where memories stored in one language are retrieved in another. Tackle embedding alignment, language-agnostic semantic search, and cultural context preservation.

Target Venues

ACL, EACL, Multilingual NLP

Ideal Candidate

PhD in multilingual NLP or cross-lingual IR

Design differential privacy mechanisms for vector search, federated memory architectures, encrypted retrieval protocols, and local-first memory systems. Balance privacy, utility, and performance.

Target Venues

IEEE S&P, USENIX Security, PoPETs

Ideal Candidate

PhD in security/privacy or privacy-preserving ML

Evaluate HPAF™ in real-world contexts: adaptive tutoring with persistent student models, healthcare provider memory, refugee support systems, and cultural heritage preservation. Produce empirical and policy papers.

Target Venues

AIED, CHI, Domain-specific + Policy

Ideal Candidate

PhD in learning sciences, global health, or AI for social good

Design memory sharing mechanisms across AI agent personas within a tenant. Explore cross-persona retrieval with attribution, memory permissions, conflict resolution, and persona isolation strategies.

Target Venues

AAAI, AAMAS, NeurIPS

Ideal Candidate

PhD in multi-agent systems or dialogue systems

Taxonomize memory approaches across conversational AI, position HPAF™'s novel contributions, identify open research problems, and chart future directions. A definitive reference for the field.

Target Venues

ACM Computing Surveys, JAIR, FnT ML

Ideal Candidate

Senior PhD or postdoc with broad NLP/AI background

First-author credit on all publications from your research thread

Complete HPAF™ platform data, benchmarks, and evaluation datasets under NDA

Full access to HPAF™ codebase, documentation, and architecture design inputs

Direct mentorship on integrating HPAF™ research into your dissertation

Regular mentoring from HPAF™ Lead on research, writing, and career development

Guidance on submissions, presentation coaching, and networking at top venues

Structured pipeline with internal review, revision cycles, and submission support

Your work becomes part of a high-visibility open-source project with UNESCO/UNICEF partnerships

Introductions to UNESCO, UNICEF, NGOs, EdTech firms, university labs, and AI companies

Structured pipeline with internal review, revision cycles, and submission support

Research summaries translated into 5+ languages for community impact and broader accessibility

Documentation of real-world impact from your research for grant applications and tenure cases

This is a research collaboration, not employment. No financial compensation is provided. This model prioritizes intellectual freedom and research alignment.

All collaborators sign a mutual NDA covering access to proprietary data, source code, and pre-publication research. Standard for IP protection.

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