PeopleofSuperintelligence

Researcher

Homayoon Beigi

Homayoon Beigi is an AI researcher whose work spans neural-network learning, speech recognition, and speaker biometrics. He earned engineering degrees at Columbia, worked on recognition technology at IBM, and led research at Recognition Technologies. His 2011 textbook, Fundamentals of Speaker Recognition, brought speaker identification, verification, and related methods into one volume; his 2025 and 2026 papers applied machine learning to whispered speech, financial audio, and structural monitoring. As of October 2026, he is a Professor of Professional Practice at Columbia, where he teaches control systems.

Timeline

  1. 1984–1991

    Columbia engineering degrees

    At Columbia, he earns a B.S. in mechanical engineering in 1984 and an M.S. in 1985, then completes a doctorate in 1991 on neural-network learning and learning control.

  2. 1991–2001

    Research at IBM

    At IBM TJ Watson Research Center, he works from 1991 to 2001 and coauthors a 1999 paper on hierarchical large-scale speaker recognition.

  3. 1995–2024

    Teaching at Columbia

    From 1995 to 2024, he teaches as an adjunct professor in Columbia's computer science, mechanical engineering, and electrical engineering departments and supervises PhD students in civil engineering.

  4. 2001

    Recognition Technologies research

    In 2001, he becomes president of Recognition Technologies and leads its research on speaker, face, and speech recognition. The company's work includes large-population speaker identification and verification methods and embedded, standalone, and client-server speaker-recognition products.

  5. 2011

    A speaker-recognition textbook

    He publishes Fundamentals of Speaker Recognition in 2011, a 942-page textbook that introduces speaker identification, verification, classification, detection, and tracking.

  6. 2025–2026

    Whispered and financial speech

    In June 2025, he coauthors a paper that uses a Mamba-based state-space model alongside fine-tuned Wav2Vec2, WavLM, HuBERT, and Whisper models to handle whispered speech and dialect diversity. Presented at ICNLSP in September 2026 and posted to arXiv in October 2026, his earnings-call ASR paper finds that models improve on held-out financial speech during adaptation and compares EWC with mini-KFAC regularization.

  7. 2026

    Bridge-damage detection

    At IMAC in January 2026, he coauthors a paper on a streaming neural network for cross-domain structural-damage detection. The paper receives the Best Paper Award in Data Science.

  8. As of October 2026

    Professor at Columbia

    As of October 2026, he is a Professor of Professional Practice in Columbia's Mechanical and Electrical Engineering departments. In Fall 2026, he teaches Continuous Control Systems in Columbia's Mechanical & Electrical Engineering program.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 46% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

Sources and credits

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  1. Homayoon Beigi recognitiontechnologies.com. Checked 19 October 2026.
  2. Homayoon Beigi's Publications recognitiontechnologies.com. Checked 19 October 2026.
  3. Research and Expertise of Recognition Technologies, Inc. recotechnologies.com. Checked 19 October 2026.
  4. Fundamentals of Speaker Recognition - Homayoon Beigi - Google Books books.google.com. Checked 19 October 2026.
  5. State-Space Models in Efficient Whispered and Multi-dialect Speech Recognition arxiv.org. Checked 19 October 2026.
  6. Does Financial Speech Need Continual Learning Regularization? A Study of EWC and mini-KFAC on Earnings Call ASR arxiv.org. Checked 19 October 2026.
  7. Fall 2026 Mechanical & Electrical Engineering E4600 section 002 doc.sis.columbia.edu. Checked 19 October 2026.