09/16/2019
At the MIT AI conference. With Hemant Taneja, Kyle Vogt, Ramesh Raskar, and Guy Satat. Ramesh spoke about AI in health care.
Camera Culture, MIT Media Lab
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Page maintained by students of the Camera Culture Group, MIT Media Lab Stay in touch with posts from members of the Camera Culture group at MIT Media Lab.
Feel free to post to the wall with interesting links to all aspects of imaging. This informal page is regularly updated by students of the group. What does the research group do? Building new tools to better capture and share visual information. What will a camera look like in ten years? How should we change the camera to improve mobile photography? How will a billion networked and portable camera
09/16/2019
07/22/2019
Seeing Through Fog is a finalist for the 2019 AutoSens Awards – MIT Media Lab Winners will be announced at the third annual AutoSens Awards Ceremony at the Atomium in Brussels, on September 18, 2019.
07/19/2019
Imaging Cafe in action at MIT Media Lab!
Imaging Cafe once again brought together researchers and engineers interested in imaging fostering deeper conversations with entrepreneurs, mentors and investors.
Minutes of the meeting:
Taleb Alashkar – Interested in developing a facial recognition algorithm that is able to match linguistic facial descriptions to picture of the face.
Adrian Gropper - (HIE of one): Focuses on health information exchange and self-sovereign technology.
Alex Hornstein - (co-founder of Looking Glass Factory): Makes light field displays and spends time in underwater imaging.
Maryam Najafian: Performs natural language processing and computer vision for commercial real estate investments and wants to use machine learning to help manage real estate investment portfolios.
Richard Zhang & Francesco Benedetti: Organize conferences that highlight the experience of failure among individuals and enterprises in academia and industry: an initiative that aims to destigmatize failure.
Alan Foster, ArcLive: Works on a tool that temporarily digitizes archives using rapid computer vision
algorithms
Lagnojita Sinha: Plans to incorporate machine learning with optical imaging in diverse applications like helping in rescue operations. She also plans to incorporate artificial intelligence to help choose the best optical imaging system depending on the sample being imaged.
Amey Chaware: Plans to develop microscopes that automatically adjust their focus and brightness based on a sample and environmental conditions.
Krishna Samayamantri: Uses infrared imaging for faster and more accurate injury assessment
Perikumar Javia: Develops automated computer vision algorithm that can detect lesions in the colon
during a colonoscopy
Younes Sobhi: Uses Computer vision for Neuroscience data dissection and labeling and aims to
accelerate scientific discovery
04/29/2019
Ai on Siloed Data, Tuesday workshop at MIT with several Fortune 500 companies
04/25/2019
It was exciting to see the member companies coming together in our AI and Siloed Private Data workshop and discussing the possible challenges in varied domains that can be addressed by split learning (https://splitlearning.github.io)
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