Unaiza Ahsan, Ph.D.

Assistant Professor, Computer Science
Dhanani School of Science & Engineering


Unaiza Ahsan is a computer scientist and researcher interested broadly in areas within Machine Learning, Computer Vision and Recommendation Systems.

Unaiza obtained her Ph.D. at the Georgia Institute of Technology in Atlanta, where she pursued her doctorate in Computer Science. Her research involved complex activity recognition, specifically focusing on leveraging mid-level representations to enhance the accuracy and efficiency of video recognition systems without requiring large labeled datasets. Prior to her Ph.D., Unaiza obtained a Master’s degree in Computer and Information Systems from NED University of Engineering and Technology in Karachi, Pakistan. Her academic journey began with a Bachelor’s degree in Telecommunications from the same institution. Throughout her academic pursuits, Unaiza consistently demonstrated exceptional dedication and academic prowess, earning top ranks among her peers.

Unaiza’s academic accomplishments have been paralleled by her professional contributions. She served as a Lead Data Scientist at The Home Depot in Atlanta, where she worked on cutting-edge recommendation algorithms using computer vision and natural language processing techniques.

As a Graduate Research Assistant at the Georgia Institute of Technology, she worked with programs such as Data Science for Social Good, where she developed web applications to address real-world challenges. Unaiza’s research findings have been disseminated through a series of notable publications and conference presentations. Her work has spanned a wide range of topics, from event recognition in images to generating visually compatible recommendations for home décor.

During her studies, Unaiza was awarded the Schlumberger Faculty for the Future Fellowship which provided full funding for her Ph.D. at Georgia Tech.

Beyond her professional achievements, Unaiza possesses a creative spirit and enjoys expressing herself through writing poetry.


  • Ph.D. in Computer Science, Georgia Institute of Technology, Atlanta, GA, 2012-2018
  • Master of Engineering in Computer and Information Systems, NED University of Engineering and Technology, Karachi, Pakistan, 2009-2012
  • Bachelor of Engineering in Telecommunications, NED University of Engineering and Technology, Karachi, Pakistan, 2005-2009

Teaching Experience

  • Graduate Research and Teaching Assistant, Georgia Institute of Technology, Atlanta, GA, 2012-2019

Courses Taught

  • Computer Vision
  • Computer Technology

Research Interests

  • Video Recognition, Semi-Supervised Learning, Transfer Learning, Complex Event Recognition, Few-shot Learning, Action Recognition, Multi-modal Recommendations

  • Publications

  • Wang, Yuanbo, Unaiza Ahsan, Hanyan Li, and Matthew Hagen. ”A Comprehensive Review of Modern Object Segmentation Approaches.” Foundations and Trends in Computer Graphics and Vision 13, no. 2-3 (2022): 111-283.
  • Unaiza Ahsan, Yuanbo Wang, Alexander Guo, Kevin D. Tynes Jr., Tianlong Xu, Estelle Afshar and Xiquan Cui. ”Visually Compatible Home Decor Recommendations Using Object Detection and Product Matching” The 2021 International Conference on Computational Science and Computational Intelligence (CSCI), 2021.
  • Al Jadda, Khalifeh, Unaiza Ahsan, and Huiming Qu. ”Complementary item recommendations based on multi-modal embeddings.” U.S. Patent Application 17/011,543, filed March 11, 2021.
  • Al Jadda, Khalifeh, Huiming Qu, Nian Yang, San Hwu, and Unaiza Ahsan. ”Product collection recommendations based on transaction data.” U.S. Patent Application 16/785,104, filed October 22, 2020
  • Guo, Mingming, Nian Yan, Xiquan Cui, Unaiza Ahsan, Rebecca West, and Khalifeh Al Jadda. ”Deep Learning-based Online Alternative Product Recommendations at Scale.” In Proceedings of The 3rd Workshop on e-Commerce and NLP, pp. 19-23. 2020.
  • West, Rebecca, Khalifeh Al Jadda, Unaiza Ahsan, Huiming Qu, and Xiquan Cui. ”Interpretable Methods for Identifying Product Variants.” In Companion Proceedings of the Web Conference 2020, pp. 448-453. 2020.
  • Pigi Kouki, Ilias Fountalis, Nikolaos Vasiloglou, Nian Yan, Unaiza Ahsan, Khalifeh Al Jadda and Huiming Qu, Product Collection Recommendation in Online Retail, ACM Conference on Recommender Systems (RecSys), 2019
  • Unaiza Ahsan, Rishi Madhok and Irfan Essa, Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition, IEEE Winter Conference on Applications of Computer Vision (WACV) 2019.
  • Unaiza Ahsan, Chen Sun and Irfan Essa, DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops ‘Women in Computer Vision (WiCV)’, 2017.
  • Unaiza Ahsan, Munmun De Choudhury and Irfan Essa, Towards Using Visual Attributes to Infer Image Sentiment Of Social Events, In Proceedings of the 2017 International Joint Conference on Neural Networks (Anchorage, AK, May 14-19, 2017), IJCNN 2017.
  • Unaiza Ahsan, Chen Sun, James Hays and Irfan Essa, Complex Event Recognition from Images with Few Training Examples, IEEE Winter Conference on Applications of Computer Vision (WACV) 2017.
  • Unaiza Ahsan, Oleksandra Sopova, Wes Stayton, Bistra Dilkina, Interactive tool to prioritize housing options for refugee resettlement Bloomberg Data for Good Exchange 2016.
  • Unaiza Ahsan and Irfan Essa, Clustering social event images using kernel canonical correlation analysis, IEEE Conference on Computer Vision and Pattern Recognition Workshops 2014.
  • Unaiza Ahsan, SA Sattar, Humera Noor and Munzir Zafar, Multi-cue object detection and tracking for security in complex environments, SPIE Defense, Security, and Sensing 201
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