PeopleofSuperintelligence

Researcher

Kristina Monakhova

Kristina Monakhova is a computer scientist whose computational imaging research pairs optical design with machine-learning reconstruction algorithms. After winning a Goldwater Scholarship at the University at Buffalo in 2015 and an NSF Graduate Research Fellowship in 2016, she earned a PhD in electrical engineering and computer sciences at UC Berkeley with Laura Waller in 2022. Her doctoral research included learned neural reconstruction for mask-based lensless cameras in 2019, the Spectral DiffuserCam hyperspectral camera in 2020, and starlight video denoising in 2022. From 2022 to 2024, she held a Postdoctoral Fellowship for Engineering Excellence in MIT's Department of Electrical Engineering and Computer Science with Sixian You and George Barbastathis before joining Cornell in 2024, where she received a 2024 Amazon Research Award. She is an assistant professor of computer science at Cornell University, where she leads the Computational Imaging Lab.

Now at
Cornell University and Computational Imaging Lab

Timeline

  1. 2015–2016

    Goldwater and NSF fellowships

    While studying electrical engineering at the University at Buffalo in 2015, she studies abroad in France at the National School of Electronics and its Applications (ENSEA) and wins a Goldwater Scholarship. In 2016, she receives an NSF Graduate Research Fellowship.

  2. 2019

    Learned lensless reconstruction

    Her UC Berkeley PhD work with Laura Waller includes "Learned reconstructions for practical mask-based lensless imaging," submitted in August 2019. The paper unrolls a model-based optimization algorithm into a trainable neural network that reconstructs images from a mask-based lensless camera 20x faster than traditional methods.

  3. 2020

    Spectral DiffuserCam and EECS Rising Star

    In 2020, she coauthors Spectral DiffuserCam with Kyrollos Yanny, Neerja Aggarwal and Laura Waller. The lensless snapshot hyperspectral camera places a tiled spectral filter array directly on the image sensor with a diffuser close to it. In October 2020, she is selected as a 2020 EECS Rising Star.

  4. 2020–2021

    Angelakos award and Intel internship

    She is one of five recipients of the Demetri Angelakos Memorial Achievement Award from Berkeley EECS for 2020–2021, which recognizes doctoral students who help colleagues alongside their research. In January 2021, she starts a research internship at Intel's Intelligent Systems Lab. In 2021, she coauthors "Untrained networks for compressive lensless photography," updating network weights from the camera measurement without labeled training data.

  5. 2022

    Starlight video denoising and Berkeley PhD

    In 2022, she coauthors "Dancing under the stars: video denoising in starlight" with Stephan R. Richter, Laura Waller and Vladlen Koltun for the IEEE/CVF Conference on Computer Vision and Pattern Recognition. The paper shows photorealistic video under starlight for the first time, using a GAN-tuned physics-based noise model. In 2022, she completes her Berkeley EECS PhD dissertation on physics-informed machine learning for computational imaging.

  6. 2022–2024

    Postdoctoral fellow at MIT

    From 2022 to 2024, she is a postdoctoral fellow in MIT's Department of Electrical Engineering and Computer Science, working with Sixian You and George Barbastathis and supported by the MIT Postdoctoral Fellowship for Engineering Excellence.

  7. 2024

    Joining Cornell and Amazon Research Award

    By October 2024, she joins the Cornell Ann S. Bowers College of Computing and Information Science as an assistant professor of computer science, and in Fall 2024 she teaches the graduate course CS6662 Computational Imaging at Cornell University. She also receives a 2024 Amazon Research Award for "Trustworthy extreme imaging for science using interpretable uncertainty quantification."

  8. As of October 2026

    Leading Cornell's Computational Imaging Lab

    At Cornell, she coauthors "QUTCC: Quantile Uncertainty Training and Conformal Calibration for Imaging Inverse Problems" in July 2025, teaches CS4660 Foundations of Computational Imaging in Spring 2026, and coauthors "Sparse Light Field Sampling Improves Casual 3D and 4D Reconstruction" in August 2026. She is an assistant professor in Cornell's Department of Computer Science, where she leads the Computational Imaging Lab. The lab is supported by an Amazon Research Award and startup funding from Bowers CIS.

Career

  1. NowCornell UniversityAssistant Professor
  2. NowComputational Imaging LabLab Lead
  3. Massachusetts Institute of TechnologyPostdoctoral Fellow

Education

  1. University of California, BerkeleyPh.D.

From the biography.

  1. 11% of AI doctorate holders from 2010 to 2016 founded or led a company or lab by 10 years after graduationIncludes Cornell University. We estimate how often AI doctorate holders founded or led a company or lab by 10 years after graduation, how waiting times compare between founders and top jobs, and which universities trained the most.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Cornell University. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  3. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes Cornell University. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Cornell University. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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

  1. Three engineering students win coveted Goldwater scholarships - Office of Fellowships and Scholarships - University at Buffalo buffalo.edu. Checked 22 October 2026.
  2. Kristina Monakhova kristinamonakhova.com. Checked 22 October 2026.
  3. Learned reconstructions for practical mask-based lensless imaging (arXiv) arxiv.org. Checked 22 October 2026.
  4. PI | Computational Imaging Lab @ Cornell kristinamonakhova.com. Checked 22 October 2026.
  5. Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array (arXiv) arxiv.org. Checked 22 October 2026.
  6. news | Computational Imaging Lab @ Cornell kristinamonakhova.com. Checked 22 October 2026.
  7. Student Award: Demetri Angelakos Memorial Achievement Award | EECS at UC Berkeley www2.eecs.berkeley.edu. Checked 22 October 2026.
  8. [2103.07609] Untrained networks for compressive lensless photography arxiv.org. Checked 22 October 2026.
  9. Dancing under the stars: video denoising in starlight (arXiv) arxiv.org. Checked 22 October 2026.
  10. Kristina Monakhova » Computational Imaging Lab laurawaller.com. Checked 22 October 2026.
  11. Kristina Monakhova | Department of Computer Science | Cornell Bowers cs.cornell.edu. Checked 22 October 2026.
  12. Engineering Excellence | MIT School of Engineering engineering.mit.edu. Checked 22 October 2026.
  13. Meet the new faculty: Kristina Monakhova | Cornell Bowers bowers.cornell.edu. Checked 22 October 2026.
  14. Kristina Monakhova - Amazon Science amazon.science. Checked 22 October 2026.
  15. [2507.14760] QUTCC: Quantile Uncertainty Training and Conformal Calibration for Imaging Inverse Problems arxiv.org. Checked 22 October 2026.
  16. [2608.20602] Sparse Light Field Sampling Improves Casual 3D and 4D Reconstruction arxiv.org. Checked 22 October 2026.
  17. Computational Imaging Lab @ Cornell kristinamonakhova.com. Checked 22 October 2026.