🌐 Website: https://ankitshah009.github.io/
I’m a Full Stack LLM Development Associate Director at Accenture (Center for Advanced AI) and a Ph.D. graduate from the Language Technologies Institute (LTI) at Carnegie Mellon University.
My work focuses on designing, building, and scaling production-grade AI systems, spanning:
- Large Language Models (LLMs)
- Multimodal and audio-centric learning systems
- End-to-end AI platforms from research to deployment
I operate at the intersection of research rigor, real-world constraints, and system reliability, leading teams that translate cutting-edge ideas into deployed AI solutions.
- Full-stack LLM system design (data → models → orchestration → evaluation → governance)
- Multimodal learning (audio, speech, language)
- Weakly- and semi-supervised learning at scale
- AI platform architecture for enterprise environments
- Bridging academic research with production engineering
- Ph.D., Language Technologies Institute (LTI), Carnegie Mellon University
- Research emphasis on:
- Computational audition
- Weakly labeled and large-scale learning
- Multimodal representation learning
- Contributor and organizer in the DCASE sound event detection benchmark (Task 4)
My academic work is closely aligned with real-world AI deployment challenges, especially where labeled data is scarce or noisy.
This GitHub contains a mix of:
- Research codebases from my academic work
- Experimental systems for audio and multimodal learning
- Tools and prototypes exploring scalable ML systems
Note: A significant portion of my recent work is developed privately or in collaboration with industry and academic partners.
I’m open to:
- Research collaborations in multimodal and trustworthy AI
- Conversations with senior engineers and researchers
- Select industry and platform-level partnerships
📫 Best ways to reach me:
- Website: https://ankitshah009.github.io
- Google Scholar: https://scholar.google.com/citations?user=TqG1H4cAAAAJ&hl=en
- ORCID: https://orcid.org/0000-0002-8838-5421
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