Prashant motwani biography definition
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Mr. Nandan Nilekani
Co-founder & Chairman of the Board - Infosys
Nandan Mohanrao Nilekani was born in Bengaluru and received his bachelor’s degree from IIT Bombay. “My five years at IIT-Bombay were the defining experience of my life,” said Mr Nilekani.
Read More arrow_outwardRead More arrow_outwardB. Tech. - 1978
Electrical Engineering
Mr. Ashank Desai
Founder, Chairman & Former Managing Director of Mastek Limited
Mr. Ashank Desai, a Distinguished Alumnus of IIT Bombay and a top-ranked graduate in Mechanical Engineering from Bombay University in 1972, earned his M.Tech in Mechanical Engineering from IIT Bombay in 1974. Following a three-year tenure as a Design Engineer at Godrej & Boyce Manufacturing Co., he completed his PGDBM from IIM Ahmedabad in 1979. Mr. Desai has made significant contributions to both the IT industry and philanthropy.
Read More arrow_outwardRead More arrow_outwardM. Tech. - 1974
Mechanical Engineering
Mr. Bharat Desai
Co-Founder - Syntel Inc
Bharat Desai and his wife Neerja Sethi established the Desai Sethi School of Entrepreneurship to champion entrepreneurial activity on campus. It serves as a world-class knowledge center and a launching pad for new venture creation at IITB
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Aaron Aboagye
PartnerDetroit
Ashwin Adarkar
Senior PartnerSouthern California
Praveen Adhi
Senior PartnerChicago
Gaurav Agrawal
PartnerNew York
Kabir Ahuja
Senior PartnerNew York
Mina Alaghband
PartnerNew York
Kari Alldredge
PartnerMinneapolis
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Activities
TITLE
Conceptualizing Visualizations as Functions, Spaces, and Grammars
ABSTRACT
Visualization is often regarded as a static artifact – an image-based representation of data. However, from a mathematical and programmatic perspective, it can be more accurately described as a function: an action that transforms data and parameters into visual form. By framing visualization as a function, we can investigate its properties by examining its inputs (domain) and outputs (range), both of which can be conceptualized as distinct spaces. In this talk, I first present our work on learning the input and output spaces of visualizations using neural networks. I then introduce other spaces considered by the visualization research community, such as pixel space, interaction space, and design space. Finally, I discuss our research on viewing visualizations through the lens of grammars, demonstrating how this approach helps us uncover key properties and delineate the boundaries between data, task, and visualization spaces.
PAPERS:
- NeuralCubes: Deep Representations for Visual Data Exploration: https://arxiv.org/pdf/1808.08983
- A Grammar of Hypotheses for Visualization, Data, and Analysis: https://arxiv.org/pdf/2204.14267
- Design-Specific Transforms In Visualiza