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Kamelia Aryafar, Ph.D. is the Head of Retail and Consumer (CPG) Solutions Engineering in Google Cloud AI where she leads applied artificial intelligence and engineering teams focused on solving retailer's problems.


Prior to Google, Dr.Aryafar was the Executive Vice President, Chief Algorithms and Analytics Officer, and board member for Dr. Kamelia Aryafar led the company’s analytics, data platform, technology, machine learning, data science, data engineering, and algorithmic product functions across the organization. Dr. Aryafar joined, after several years at Etsy where she worked with different product teams across several platforms to integrate analytics, machine learning (ML) and artificial intelligence (AI) algorithms throughout the organization. 


Dr. Aryafar holds a Ph.D. and M.Sc. in computer science and ML from Drexel University and has published several papers in scientific journals. As an active member of the ML community, she frequently speaks at academic and industry conferences focusing on advancing the field of AI, ML, Technology and women in STEM. Dr. Aryafar has served on several boards including:, Initiative of Analytics and Data Science Standards (IADSS), Retail Management Institute at Santa Clara University, and Women of MENA in Tech.

Dr. Kamelia Aryafar

AI & Technology Executive


Forbes 30 Inspirational Women 2021



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2020 - Present

Google Inc.

Head of Retail/CPG AI & Engineering

Director of Engineering

2019 - 2020

Member, Board of Directors

2018 - 2020

Chief Algorithms and Analytics Officer, EVP

2017 - 2018

 Head of Data Science, Machine Learning, and AI (Engineering and Product)

2012 - 2017


Senior Machine Learning and Data Science Lead

Board Memberships
2021 - Present

Member, Board of Directors, 
The JED Foundation

2021 - Present

Dean's Executive Advisory CouncilCCI, Drexel University

2019 - 2020
2019 - Present

Advisory Board Member, Initiative for Analytics & Data Science Standards (IADSS)

Member, Board of Directors,

2019 - Present

Member, Board of Directors, Persian women in tech (non-profit)
Compensation committee member

2019 - Present

Advisory Board Member, Retail Management Institute at Santa Clara University (RMI)


University of Utah - David Eccles School of Business

Executive Training 

Strategic Leadership


Drexel University

Doctor of Philosophy (Ph.D.)


Computer Science (Machine Learning)


Drexel University

Master of Science (M.Sc.)

Computer Science

2003 - 2007

Sharif University

Bachelor of Science (B.Sc.)

Computer Science





The Power of Multimodal Learning

in Production Scale E-Commerce

Search l Activate 2019

AI: Building the Future of E-Commerce | Kamelia Aryafar | Demystifying Data Science 2018

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AI in Practice: Fact and Fiction l Activate 2019

Learning to Rank with Deep Visual Semantic Features l 2017

Learning to Rank in e-commerce l AI With The Best 2017

Machine Learning as the Key to Personalized Curation l 2015

The Market Place Holy Grail l Extract 2015


Recent Industry Publications

Full Publications List:

Featured Press

Forbes, "30 Inspirational Women 2021"

​[1]  Murium Iqbal, Kamelia Aryafar, and Timothy Andertoon. Style conditioned recommendations. In Proceedings of the 13th ACM Conference on Recommender Systems, RecSys 2019, Copenhagen, Denmark, September 16-20, pages 128-136, 2019.

[2]  Murium Iqbal, Nishan Subedi, and Kamelia Aryafar. Production ranking systems: A review. In Proceedings of SIGIR 2019 Workshop on eCommerce, co-located with the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, eCom@SIGIR 2019, Paris, France, July 25, 2019, 2019.

[3]  Murium Iqbal, Adair Kovac, and Kamelia Aryafar. Discovering style trends through deep visually aware latent item embeddings. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. IEEE, 2018.

[4]  Murium Iqbal, Adair Kovac, and Kamelia Aryafar, A multimodal recommender system for large-scale assortment generation in e-commerce. In The International ACM SIGIR Conference on Research and Development in Information Retrieval Workshop on eCommerce. ACM, 2018.​

[5]  Kamelia Aryafar, Devin Guillory, and Liangjie Hong. An ensemble-based approach to click-through rate prediction for promoted listings at etsy. In Proceedings of the ADKDD'17. ACM, 2017.​​

[6]  Corey Lynch, Kamelia Aryafar, and Josh Attenberg. Images don't lie: Transferring deep visual semantic features to large-scale multimodal learning to rank. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2016.

[7]  Kamelia Aryafar, Corey Lynch, and Josh Attenber. Exploring user behaviour on etsy through dominant colors. In 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, August 24-28, 2014, 2014.

"The Future of Knowledge at Work " 

 - Bloomfire Interview

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