• [09/21/2022] Our paper, Denoising Self-Attentive Sequential Recommendation, received the Best Paper Award at RecSys 2022!
  • [06/30/2022] Our paper, Denoising Self-Attentive Sequential Recommendation, with Huiyuan Chen, Menghai Pan, Lan Wang, Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang and Hao Yang, was accepted for the 16th ACM Conference on Recommender Systems (RecSys 22)!
  • [06/06/2022] Our paper, Semi-supervised Context Discovery for Peer-Based Anomaly Detection in Multi-Layer Networks, with Bo Dong, Yuhang Wu, Michael Yeh, Yuzhong Chen, Hao Yang, Fei Wang, Wanxin Bai, Krupa Brahmksri, Zhang Yimin, Chinna Kummitha and Verma Abhisar, was accepted for the 24th International Conference on Information and Communications Security (ICICS 22)!
  • [04/01/2022] Our paper, OutfitGAN: Learning Compatible Items for Generative Fashion Outfits, with Maryam Moosaei, Ablaikhan Akhazhanov, Huiyuan Chen, Fei Wang and Hao Yang, was accepted to CVPR 2022 workshop, Workshop on Computer Vision for Fashion, Art, and Design!
  • [01/10/2022] I joined Amazon Fashion as an Applied Scientist!
  • [12/29/2021] My podcast with Kyle Polich where we talked about predicting fashion trends with AI is now available on Data Skeptic!
  • [10/27/2021] Our paper, Forecasting-based Multi-aspect Framework for Multivariate Time-series Anomaly Detection, with Lan Wang, Huiyuan Chen, Yuhang Wu, Fei Wang and Hao Yang is accepted to IEEE Big Data 2021 as full research paper.
  • [07/07/2021] Our paper, Tops, Bottoms, and Shoes: Building Capsule Wardrobes via Cross-Attention Tensor Network, with Huiyuan Chen, Fei Wang and Hao Yang is accepted to RecSys 2021 as full research paper.
  • [04/18/2021] I gave a talk at Z Combinator, Taiwan, on the topic of AI在時尚消費領域上的應用.
  • [04/14/2021] Our paper, Structured Graph Convolutional Networks with Stochastic Masks for Recommender Systems, with Huiyuan Chen, Lan Wang, Michael Yeh, Fei Wang and Hao Yang is accepted to SIGIR 2021 as full research paper.
  • [08/05/2020] Our paper, Economic Worth-Aware Word Embeddings, with Peifeng Yin and Wang-Chien Lee was accepted to DSAA 2020 as a full research paper.
  • [01/11/2020] Our paper, OutfitNet: Fashion Outfit Recommendation with Attention-Based Multiple Instance Learning, with Maryam Moosaei and Hao Yang was accepted to TheWebConf 2020 (WWW 20) as a full research paper.
  • [10/05/2019] I was interviewed by InStyle Taiwan in their October 2019 issue's article, 結合數據與時尚的熱情!專訪數據科學家Yusan Lin.
  • [06/10/2019] Our paper, Next-Season Design Prediction on High-Fashion Runway, with Hao Yang was accepted to KDD 2019 workshop, AI for Fashion.
  • [04/24/2019] I was on the panel of Future of Fashion with AR/AI at Fashion Tech Conference in Fashion Tech Week, San Francisco
  • [04/12/2019] Our paper, Learning Personal Tastes in Choosing Fashion Outfits, with Maryam Moosaei and Hao Yang was accepted to CVPR 2019 workshop, Understanding Subjective Attributes of Data: Focus on Fashion and Subjective Search.
  • [03/05/2019] I was mentioned in WTVOX's interview with Leanne Luce, Debating “Artificial Intelligence for Fashion” With Google’s Product Manager, as one of the inspirational women in Fashion and Tech.

I was a research intern at Trendalytics Innovation Labs Inc in summer 2015, and at Visa Research in spring 2018. I worked as a AI Research Scientist at Visa Research from 2018 to 2021, and I am now an Applied Scientist at Amazon Fashion.

Publications

  • Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang and Hao Yang, Denoising Self-Attentive Sequential Recommendation, 16th ACM Conference on Recommender Systems (RecSys 22), Seattle WA, United States, Sep. 2022. Best Paper Award [paper]
  • Bo Dong, Yuhang Wu, Michael Yeh, Yusan Lin, Yuzhong Chen, Hao Yang, Fei Wang, Wanxin Bai, Krupa Brahmksri, Zhang Yimin, Chinna Kummitha and Verma Abhisar, Semi-supervised Context Discovery for Peer-Based Anomaly Detection in Multi-Layer Networks, The 24th International Conference on Information and Communications Security (ICICS 22), Canterbury, United Kingdom, Sep. 2022
  • Maryam Moosaei, Yusan Lin, Ablaikhan Akhazhanov, Huiyuan Chen, Fei Wang and Hao Yang, OutfitGAN: Learning Compatible Items for Generative Fashion Outfits, 5th Workshop on Computer Vision for Fashion, Art, and Design (CVPR 22), New Orleans, LA, United States, Jun. 2022 [paper][poster]
  • Lan Wang, Huiyuan Chen, Yuhang Wu, Yusan Lin, Fei Wang and Hao Yang, Forecasting-based Multi-aspect Framework for Multivariate Time-series Anomaly Detection, IEEE International Conference on Big Data (IEEE Big Data 2021), 2021 [paper]
  • Huiyuan Chen, Yusan Lin, Fei Wang and Hao Yang, Tops, Bottoms, and Shoes: Building Capsule Wardrobes via Cross-Attention Tensor Network, 15th ACM Conference on Recommender Systems (RecSys 21), 2021 [paper]
  • Huiyuan Chen, Lan Wang, Yusan Lin, Michael Yeh, Fei Wang and Hao Yang, Structured Graph Convolutional Networks with Stochastic Masks for Recommender Systems, 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 21), 2021 [paper]
  • Yusan Lin, Peifeng Yin and Wang-Chien Lee, Economic Worth-Aware Word Embeddings, 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA 20), 2020 [paper] [source code] [slides]
  • Maryam Moosaei, Yusan Lin, and Hao Yang, Fashion Recommendation and Compatibility Prediction Using Relational Network, arXiv, 2020 [paper]
  • Yusan Lin, Maryam Moosaei, and Hao Yang, OutfitNet: Fashion Outfit Recommendation with Attention-Based Multiple Instance Learning, IW3C2 The Web Conference (WWW 20), 2020 [paper]
  • Yusan Lin and Hao Yang, Next-Season Design Prediction on High-Fashion Runway, 22th ACM SIGKDD Workshop on AI for Fashion (KDD 19), Workshop paper, 2019 [paper]
  • Yusan Lin, Maryam Moosaei, Hao Yang, Learning Personal Tastes in Choosing Fashion Outfits, IEEE Computer Vision and Pattern Recognition (CVPR 19), Workshop paper, 2019 [paper]
  • Yusan Lin, Peifeng Yin, Wang-Chien Lee, Modeling Dynamic Market Competition on Crowdfunding, IW3C2 The Web Conference (WWW 18), 2018 [paper]
  • Yusan Lin, Peifeng Yin, Wang-Chien Lee, Modeling Menu Bundle Designs of Crowdfunding Projects, 26th ACM Conference on Information and Knowledge Management (CIKM 17), 2017 [paper]
  • Yusan Lin, Tawei Wang, Dress Up Like a Stylist? Learning from A User-Generated Fashion Network, 20th ACM SIGKDD Workshop on Machine Learning Meets Fashion (KDD 17), 2017 [paper]
  • Yusan Lin, Chung-Chou H. Chang and Wang-Chien Lee, Analysis of Rewards on Reward-Based Crowdfunding Platforms, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 16), 2016 [paper]
  • Jorge Alé Chilet, Cuicui Chen, Yusan Lin, Analyzing Social Media Marketing in the High-End
    Fashion Industry Using Named Entity Recognition
    , IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Multidisciplinary Track (ASONAM 16), 2016 [paper]
  • Yusan Lin, Heng Xu, Yilu Zhou, Wang-Chien Lee, Styles in the Fashion Social Network: An Analysis on Lookbook.nu, International Social Computing, Behavioral Modeling and Prediction Conference (SBP15), 2015 [paper]
  • Yusan Lin, Yilu Zhou, Heng Xu, Text-Generated Fashion Influence Model: An Empirical Study on Style.com, Hawaii International Conference on System Sciences, 2015 [paper] [ACM TechNews] [Penn State News]
  • Yusan Lin, Yilu Zhou, Heng Xu, The Hidden Influence Network in the Fashion Industry, 24th Workshop on Information Technologies and Systems, 2014 [paper]

Selected Talks

  • Panelist: Future of Fashion with AR/AI, Fashion Tech Conference, San Francisco, April 2019
  • Keynote: Artificial Intelligence in Fashion, Fashion Technology Week New York, New York, September 2018
  • Fashion Meets Data Science, Fashion Technology Week New York, at 5th Avenue Microsoft Flagship Store, New York, 2017

Sessions

  • When Fashion Meets Markeing Science, INFORMS Marketing Science, Philadelphia, June 2018

I have gained experience teaching the following courses:

  • Teaching Assitant
    • CMPSC 431W Database Management (Spring 2015)
    • CMPSC 465 Data Structures and Algorithms (Fall 2014)
    • CMPSC 122 Advanced Programming in C++ (Spring 2013)
    • CMPSC 101 Introduction to Programming in C++ (Fall 2012)
  • Instructor
    • CMPSC 431W Database Management Systems (Fall 2015, Spring 2016, Fall 2016) [course website]
      • Received 6.7/7 student evaluation
    • Girlz Digital World: Fashion and Design in the Digital World (Summer 2013)

I recorded and uploaded one semester of my lectures on this YouTube channel. Feel free to browse and subscribe!

  • Fashion Prediction, December 2021, hosted by Kyle Polich [iTunes Podcast] [Spotify] [webpage]
  • InStyle: 結合數據與時尚的熱情!專訪數據科學家Yusan Lin, October 2019 [article]
  • Women Data Leaders, KDD Impact Progres, April 2018
  • TechOrange: 【台灣最美資料科學家】專訪林郁珊: 美國資工學生不只在意分數,更會思考如何學以致用, December 2016 [article]
  • The Amazing Women Who Have Inspired Us This Year, December 2016 [article]
  • Teen Vogue: Meet the Fashion Data Analyst Working to Predict the Next Big Trend, December 2016 [article]
  • This Girl Chose to be Someone Who Can Do Both, November 2016 [article]
  • Data Skeptic: Measuring the Influence of Fashion Designers, hosted by Kyle Polich [iTunes Podcast] [webpage]
  • Selected participation: Deep Learning & Reinforcement Learning Summer School, CIFAR Vector Institute, 2018
  • Research grant: Learning Latent Representations of Heterogeneous Information Networks (NSF IIS-1717084 ), National Science Foundation, with Wang-Chien Lee
  • Student Travel Grants, 2017 ACM Conference on Information and Knowledge Management (CIKM'17/SIGIR)
  • Research grant: Competition is Good? The Role of Competitive Actions on Fashion Social Network, University Research Council Competitive Research Grant, 2017, Kellstadt Graduate School of Business, DePaul University, with David Wang
  • Graduate Student Teaching Award, 2016, Department of Computer Science and Engineering, Penn State University
  • Research grant, 2016, The Institute for Quantitative Social Science (IQSS), Harvard University, with Cuicui Chen and Jorge Alé Chilet
  • Student Travel Award, 2015 International Social Computing, Behavioral-Cultural Modeling and Prediction Conference (SBP15)
  • Diversity Travel Award, 2014 International Social Computing, Behavioral-Cultural Modeling and Prediction Conference (SBP14)
  • I am a fashion model represented by the MDT Agency Inc. You can find my portfolio here.
  • I speak Mandarine, English and Japanese.
  • 2012 - 2018, Ph.D., Computer Science and Engineering, The Pennsylvania State University, USA
  • 2008 - 2012, B.S., Computer Science and Information Engineering, National Central University, Taiwan
Contact

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