Reza Zadeh

Reza Zadeh is an American-Canadian-Iranian computer scientist and technology executive working on machine learning. He is adjunct professor at Stanford University and CEO of Matroid.[1][2] He has served on the technical advisory boards of Databricks and Microsoft.[3] His work focuses on machine learning, distributed computing, and discrete applied mathematics.[4][5][6]

Reza Zadeh
NationalityUSA, Canada, Iran
CitizenshipUSA, Canada, Iran
Alma materStanford University (Ph.D.)
Carnegie Mellon University (M.Sc.)
University of Waterloo (B.S.)
Known forMachine Learning
Recommender Systems
Computer Vision
Scientific career
FieldsComputer Science
InstitutionsStanford University
ThesisLarge Scale Graph Completion
Doctoral advisorGunnar Carlsson
Websitestanford.edu/~rezab

In Industry, to evaluate new ventures formed at the University of Toronto, Reza serves as a chief scientist of Machine Learning[7] at the Rotman School of Management.[8] His awards include a KDD Best Paper Award[9] and the Gene Golub Outstanding Thesis Award at Stanford.

Work

Computer Vision

The Princeton University ModelNet challenge is an object recognition competition to classify 3D Computer-aided design models into object categories. In 2016, Matroid was a leader in this competition and the relevant neural networks were integrated into the Matroid product.[10]

In a collaboration with his own doctor at Stanford hospital, Reza's research team created a neural network to automatically detect Glaucoma in 3D optical coherence tomography images of the eyeball. The net surpassed human doctor performance and is providing diagnostic hints at the hospital.[11]

In 2016, Reza founded Matroid, inc to commercialize Computer Vision research by building a product accessible to industries such as manufacturing and industrial sensors. Matroid has raised $13.5 million from New Enterprise Associates, Intel, and others. The company's flagship product makes it simple to perform fast visual search across large video datasets, monitor real-time video streams, and create custom computer vision models without any programming.

Distributed Machine Learning

Reza is a coauthor of Apache Spark, in particular its Machine Learning library, MLlib,[12][13] for which he won a best paper award[9] at KDD 2016. Through open source, Reza's work has been incorporated into industrial and academic cluster computing environments.[14] He was an early technical advisor and employee at Databricks, the company commercializing Spark.

Recommender Systems

Reza created the machine learning algorithm behind Twitter's Who-To-Follow project[15] and subsequently released it to open source.[16] During that time he also led research tracking earthquake damage via machine learning, gaining wide media attention as an example of real-time social information flow.[17][18][19]

Personal

Reza was born during the Iran–Iraq War in the under-siege city of Ahvaz. From there, his family immigrated to London, England where Reza grew up until age 17, after which he immigrated to Toronto, Canada, obtaining a degree from University of Waterloo. He frequently visited the US at age 18 to work on the Google Research team, and later moved to the US for a masters at Carnegie Mellon University and PhD at Stanford, all in Computer Science and Mathematics.

He holds three citizenships: Canadian, American, and Iranian. During confusion surrounding the 2017 travel ban, his pro-immigration stance stood as voice of protest to the Trump Administration’s Anti-Immigration policies.[20] He is a private pilot and ironman triathlete.

References
  1. "Institute for Computational and Mathematical Engineering Faculty". Stanford University. Archived from the original on May 14, 2016. Retrieved 14 May 2016.CS1 maint: unfit URL (link)
  2. Martin, Scott (2017-03-27). "A Life's Ambition, Matroid Launches". Wall Street Journal. ISSN 0099-9660. Retrieved 2017-04-14.
  3. "University of Toronto - Creative Destruction Lab". University of Toronto - Creative Destruction Lab. Retrieved 2016-06-15.
  4. Beyer, David (3 May 2015). "On the evolution of machine learning". O'Reilly Media.
  5. Simonite, Tom. "AI Supercomputer Built by Tapping Data Warehouses for Their Idle Computing Power". MIT Technology Review.
  6. Beyer, David (February 2016). The Future of Machine Intelligence: Perspectives from Leading Practitioners (PDF). O'Reilly Media.
  7. "Pre-seed start-up program | Creative destruction Lab (CDL) | Toronto". Pre-seed start-up program | Creative destruction Lab (CDL) | Toronto. Retrieved 2016-06-15.
  8. jackclarkSF, Jack Clark. "Google Sprints Ahead in AI Building Blocks, Leaving Rivals Wary". Bloomberg.com. Retrieved 2016-07-30.
  9. "SIGKDD Awards : 2016 SIGKDD Best Paper Award Winners". www.kdd.org. Retrieved 2016-07-29.
  10. Hegde, Vishakh; Zadeh, Reza (2016-11-26). "FusionNet: 3D Object Classification Using Multiple Data Representations" (PDF). Princeton ModelNet. arXiv:1607.05695 – via Princeton University.
  11. Noury, Erfan; Mannil, Suria S.; Chang, Robert T.; Ran, An Ran; Cheung, Carol Y.; Thapa, Suman S.; Rao, Harsha L.; Dasari, Srilakshmi; Riyazuddin, Mohammed; Nagaraj, Sriharsha; Zadeh, Reza (2019-10-14). "Detecting Glaucoma Using 3D Convolutional Neural Network of Raw SD-OCT Optic Nerve Scans". arXiv:1910.06302 [eess.IV].
  12. Meng, Xiangrui; Bradley, Joseph; Yavuz, Burak; Sparks, Evan; Venkataraman, Shivaram; Liu, Davies; Freeman, Jeremy; Tsai, D. B.; Zadeh, Reza (2015-05-26). "MLlib: Machine Learning in Apache Spark". arXiv:1505.06807. Bibcode:2015arXiv150506807M. Cite journal requires |journal= (help)
  13. Organisers, KDD 2015. "Matrix Computations and Optimization in Apache Spark". www.kdd.org. Retrieved 2016-06-15.
  14. "Machine Learning using Big Data: How Apache Spark Can Help | Biomedical Computation Review". biomedicalcomputationreview.org. Retrieved 2016-06-22.
  15. Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Bosagh Zadeh WTF:The who-to-follow system at Twitter, Proceedings of the 22nd international conference on World Wide Web
  16. Harris, Derrick. "Gigaom | Twitter open sourced a recommendation algorithm for massive datasets".
  17. Shu, Catherine. "Tweets Can Guide Emergency Responders Almost Immediately After An Earthquake". TechCrunch. Retrieved 2016-06-15.
  18. Wagner, Kurt. "Can Studying Tweets Lead to Faster Earthquake Recovery?". Mashable. Retrieved 2016-06-15.
  19. "Stanford turns to Twitter to track earthquakes". Engadget. Retrieved 2016-06-15.
  20. Greenberg, Issie Lapowsky and Andy (2017-01-28). "Trump's Ban Leaves Refugees in Civil Liberties Limbo". Wired. ISSN 1059-1028. Retrieved 2020-08-09.
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