Short Bio

I am a research assistant at MIT and a contract researcher at Microsoft Research. At MIT, I work with Fredo Durand on building photorealistic, procedural models for cities as a platform for studying generalization behaviour of neural networks across variations in viewpoints, light source distributions, object poses and other scene atttributes. At MSR, I work with Nebojsa Jojic on non parametric reservoir sampling (sampling points from a larger pool which best matche a non parametric distribution) and it's applications for creating conversational agents.


Before this, I was a Master's student at Harvard University where my thesis was co-supervised by Hanspeter Pfister and Fredo Durand. Before Harvard, I was at IIT Delhi back home in India, working with Durai Sundar and David Roos.


Apart from research, I am extremely passionate about teaching, and spend significant time writing tutorials/giving lectures in and around Boston. Click on the "Talks" or "Tutorials" section above for those.


Actively seeking collaborators for side projects. This includes tutorials, and other tools I am interested in building. If interested, please drop me a mail.

Experience


Awards and Scholarships

  • Snapchat Research Scholarship, 2018
  • UIST conference honorable mention paper award, 2017
  • Harvard SEAS Fellow, 2016-2018
  • Government of India MHRD scholarship, 2014-2015
  • One of thirteen students in the Viterbi India Program, 2012

Publications

Computer Vision

  • Effects of title wording on memory of trends in line graphs[PAPER]
    Newman, A., Bylinskii, Z., Haroz, S., Madan, S., Durand, F., Oliva, A., 2018.
  • Synthetically trained icon proposals for parsing and summarizing infographics. [PAPER]
    Madan, S.*, Bylinskii, Z.*, Tancik,M.*, Zhong, K., Recasens, A.,Alsheikh, S., Pfister, H., Durand, F., 2018.
  • Understanding Infographics through Textual and Visual Tag Prediction. [PAPER]
    Madan, S.*, Bylinskii, Z.*, Alsheikh, S.*, Recasens, A.*, Zhong, K., Pfister, H., Durand, F. and Oliva, A., 2017.
  • Learning Visual Importance for Graphic Designs and Data Visualizations (Honorable Mention Award). [PAPER][CODE][WEB]
    Zoya Bylinskii, Nam Wook Kim, Peter O'Donovan, Sami Alsheikh,Madan, S., Hanspeter Pfister, Fredo Durand, Bryan Russell, Aaron Hertzmann.

Machine Learning in Biology

  • An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA. BMC Genomics, 17(13), 97 (2016). [PAPER]
    Shayoni Dutta , Spandan Madan, Harsh Parikh, Durai Sundar.
  • Exploiting the recognition code for elucidating the mechanism of zinc finger protein-DNA interactions. BMC Genomics, 17(13), 109. (2016). [PAPER]
    Shayoni Dutta , Spandan Madan, Durai Sundar.

Posters

  • Understanding Infographics through Textual and Visual Tag Prediction. NECV'17.
    Madan, S.*, Bylinskii, Z.*, Alsheikh, S.*, Recasens, A.*, Zhong, K., Pfister, H., Durand, F. and Oliva, A., 2017.

    Invited Talks

    • U.C. Berkeley vision seminar.

    • MIT graphics seminar.

    • Harvard Business School - machine learning for managers[LINK]
    • HackMIT - AI v/s Deep Learning v/s Machine Learning.
    • MIT Blueprints - an introduction to computer vision.[LINK]

    Reviewing Experience

    • One paper for TPAMI
    • Two papers for CVPR'18