Ramin Anushiravani

Ramin Anushiravani

AI Research Scientist - Meta

New York City | ramin.audio@gmail.com

About Me

I studied at the University of Illinois at Urbana-Champaign and started in audio ML, interning at several industries, including the Advanced Digital Sciences Center in Singapore and Adobe. I later joined Dolby Labs, working on deep learning and audio codecs. Later, as the first hire at CurieAI, I helped develop models that detect respiratory symptoms from noisy audio, scaling the technology to hundreds of patients.

Looking to push myself into unfamiliar territory, I pivoted to NLP. At UnitedHealth Group, I was again the first ML lead on the team. I built natural language search tools for searching health benefits that became the foundation for an enterprise-wide semantic search platform. As the ML lead for the enterprise team, I trained language models from scratch, scaled the team to over 50 people, and reshaped how ML was applied to search through my experiences with sensory signals

At Precision Neuroscience, I applied cutting-edge signal processing and machine learning to brain-computer interfaces. Basically, translating brain signals into real-time actions. Currently, I work at Meta in the wearables team as an AI research scientist.

Written Work & Publications

Granted

  • Sound Enhancement through Reverberation Matching
  • Methods for Explainability of Deep-Learning Models
  • Intelligent Health Monitoring
  • Design of Stimuli for Symptom Detection

Pending

  • Domain aware autocomplete
  • Graph-based data compliance using natural language text
  • Interactive map-based visualization system related to multichannel search for complex search domains
  • Machine learning techniques for generating domain-aware query expansions
  • Multi-channel search and aggregated scoring techniques for complex search domains
  • Text embedding-based search taxonomy generation and intelligent refinement

Education

08/2011 - 12/2016

University of Illinois at Urbana-Champaign

M.S. & B.S., Electrical & Computer Engineering

GPA: 3.97/4.0 (M.S.), 3.86/4.0 (B.S.)

Continuous Learning & Certifications