PeopleofSuperintelligence

Researcher

Anastasia Razdaibiedina

Also known as Anastasiia Razdaibiedina

Anastasia Razdaibiedina is a machine-learning researcher whose work spans microscopy, language models, protein function, and audio classification. She coauthored a 2019 paper on microscopy restoration and studied protein representations from single-cell images in 2022. Her 2023 work included prompt-tuning research, an NLP internship at Microsoft Research, and Orca-2, a study of reasoning in small language models. A Borealis AI Fellowship supported her research on predicting protein function from fluorescent microscopy. As of October 2026, she advises on LAST, a transformer for audio classification.

Works
16
Citations
119
h-index
5

Publication numbers from OpenAlex, as of 18 October 2026.

Timeline

  1. 2019

    Microscopy image restoration

    In 2019, she coauthors a NeurIPS medical-imaging workshop paper on restoring multi-defect fluorescence microscopy images when training data is limited.

  2. 2022

    Protein representations from images

    In 2022, she coauthors a study of multi-scale protein representations from single-cell microscopy data. It shows that convolutional networks trained on localization classification learn functional protein features.

  3. 2023

    Prompt tuning for language models

    At ICLR 2023, she coauthors Progressive Prompts for continual learning in language models. In Findings of ACL 2023, she coauthors Residual Prompt Tuning, which improves the performance and stability of prompt tuning.

  4. May 2023–August 2023

    An NLP internship at Microsoft

    She works as an NLP research intern at Microsoft Research from May to August 2023. Her project targets LLaMA instruction tuning through hyperparameter optimization and instruction-data selection.

  5. November 2023

    Orca-2 and small-model reasoning

    In November 2023, she coauthors Orca-2: Teaching Small Language Models How to Reason, a Microsoft Research publication.

  6. 2023

    A Borealis AI Fellowship

    In 2023, she receives a Borealis AI Fellowship to support a generalist method for predicting protein function in human cells from fluorescent microscopy data.

  7. 2024

    A Toronto Ph.D. seminar

    She holds a B.Sc. in Applied Mathematics from Taras Shevchenko National University of Kyiv. In August 2024, she presents her University of Toronto Ph.D. seminar on PIFiA, a self-supervised approach to protein functional annotation from single-cell imaging data.

  8. October 2026

    Advising on audio classification

    In October 2026, she advises on LAST, a looped audio spectrogram transformer for audio classification.

A language model matched the links in this timeline to people, organizations and papers (provisional, model-judged).

Career

  1. 2023Microsoft ResearchNLP Research Intern
  2. 2022–2024Vector Institute
  3. 2019–2024University of Toronto

Education

  1. Taras Shevchenko National University of KyivB.Sc. in Applied Mathematics

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Progressive Prompts: Continual Learning for Language Models2023 · 33 citations
  2. Orca 2: Teaching Small Language Models How to Reason2023 · 30 citationsWith Ahmed Awadallah
  3. Residual Prompt Tuning: improving prompt tuning with residual reparameterization2023 · 25 citations
  4. PIFiA: self-supervised approach for protein functional annotation from single-cell imaging data2024 · Molecular Systems Biology · 15 citations
  5. Effects of Single-Nucleotide Polymorphisms in Cytokine, Toll-Like Receptor, and Progesterone Receptor Genes on Risk of Miscarriage2018 · Obstetrics and Gynecology International · 11 citations

From OpenAlex, as of 18 October 2026.

  1. The company share of AI researchers’ top papers rose from 2% to 32%Includes Microsoft. We estimate where leading AI researchers worked when their most-cited papers appeared. The company share rose from 2% in 1975–1979 to 32% in 2020–2024.
  2. Google has the highest combined h-index among AI organizationsIncludes Microsoft. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  3. Google alumni founded or led 79 other organizations, the most among the labs we compareIncludes Microsoft. We trace 181 organizations founded or led by AI lab alumni, and 187 career moves between the labs.
  4. Stanford University trained or employed 27 of the 112 AI major-prize winners, more than any other universityIncludes University of Toronto. Stanford University trained or employed 27 of the 112 AI major-prize winners, more than any other university. We compare doctorate and employment links for major-prize and best-paper winners.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Anastasia Razdaibiedina yet. Send us a free-licensed photo.

  1. Multi-defect microscopy image restoration under limited data conditions arxiv.org. Checked 18 October 2026.
  2. Learning multi-scale functional representations of proteins from single-cell microscopy data arxiv.org. Checked 18 October 2026.
  3. Progressive Prompts: Continual Learning for Language Models mlanthology.org. Checked 18 October 2026.
  4. Residual Prompt Tuning: improving prompt tuning with residual reparameterization aclanthology.org. Checked 18 October 2026.
  5. Anastasia Razdaibiedina – PhD @ UofT, ML + NLP + Comp Bio arazd.github.io. Checked 18 October 2026.
  6. Orca - Microsoft Research: Publications microsoft.com. Checked 18 October 2026.
  7. Donnelly Centre PhD student wins 2023 Borealis AI Fellowship thedonnellycentre.utoronto.ca. Checked 18 October 2026.
  8. arazd (Anastasia Razdaibiedina) · GitHub github.com. Checked 18 October 2026.
  9. PhD Seminar: Anastasia Razdaibiedina | Molecular Genetics moleculargenetics.utoronto.ca. Checked 18 October 2026.
  10. LAST: Looped Audio Spectrogram Transformer arxiv.org. Checked 18 October 2026.