Raghuram Rajan

Raghuram Rajan

Former Governor of the Reserve Bank of India (2013 - 2016); Katherine Dusak Miller Distinguished Service Professor of Finance, Chicago Booth at the University of Chicago

Biography

Raghuram Rajan is the Governor of the Reserve Bank of India. Previously, he was the Eric J. Gleacher Distinguished Service Professor of Finance at the University of Chicago’s Booth School of Business.

Dr. Rajan is also currently an economic advisor to the Prime Minister of India. Prior to resuming teaching in 2007, Dr. Rajan was the Economic Counselor and Director of Research (in plain English, the Chief Economist) at the International Monetary Fund (from 2003). Since then, he has chaired the Indian government’s Committee on Financial Sector Reforms, which submitted its report in September 2008.

Dr. Rajan’s research interests are in banking, corporate finance, and economic development, especially the role finance plays in it. His papers have been published in all the top economics and finance journals, and he has served on the editorial boards of the American Economic Review and the Journal of Finance. His recent book, Fault Lines: How Hidden Cracks Still Threaten the World Economy, won the Financial Times Business Book of the Year award in 2010. He also has an earlier book co-authored with Luigi Zingales entitled Saving Capitalism from the Capitalists

Dr. Rajan is a senior advisor to BDT Capital, Booz and Co, and is on the international advisory board of Bank Itau-Unibanco. He is a director of the Chicago Council on Global Affairs and on the Comptroller General of the United State’s Advisory Council as well as an advisory council to the FDIC. Dr. Rajan is President of the American Finance Association and a member of the American Academy of Arts and Sciences. In January 2003, the American Finance Association awarded Dr. Rajan the inaugural Fischer Black Prize, given every two years to the financial economist under age 40 who has made the most significant contribution to the theory and practice of finance.

Rajan was previously a member of the 21st Century Council and The WorldPost Advisory Council.


composed by Arswain
machine learning consultation by Anna Tskhovrebov
commissioned by the Berggruen Institute
premiered at the Bradbury Building
downtown Los Angeles
april 22, 2022

Human perception of what sounds “beautiful” is necessarily biased and exclusive. If we are to truly expand our hearing apparatus, and thus our notion of beauty, we must not only shed preconceived sonic associations but also invite creative participation from beings non-human and non-living. We must also begin to cede creative control away from ourselves and toward such beings by encouraging them to exercise their own standards of beauty and collaborate with each other.

Movement I: Alarm Call
‘Alarm Call’ is a long-form composition and sound collage that juxtaposes, combines, and manipulates alarm calls from various human, non-human, and non-living beings. Evolutionary biologists understand the alarm call to be an altruistic behavior between species, who, by warning others of danger, place themselves by instinct in a broader system of belonging. The piece poses the question: how might we hear better to broaden and enhance our sense of belonging in the universe? Might we behave more altruistically if we better heed the calls of – and call out to – non-human beings?

Using granular synthesis, biofeedback, and algorithmic modulation, I fold the human alarm call – the siren – into non-human alarm calls, generating novel “inter-being” sonic collaborations with increasing sophistication and complexity. 

Movement II: A.I.-Truism
A synthesizer piece co-written with an AI in the style of Vangelis’s Blade Runner score, to pay homage to the space of the Bradbury Building.

Movement III: Alarmism
A machine learning model “learns” A.I.Truism and recreates Alarm Call, generating an original fusion of the two.

Movement IV: A.I. Call
A machine learning model “learns” Alarm Call and recreates A.I.Truism, generating an original fusion of the two.


RAVE (IRCAM 2021) https://github.com/acids-ircam/RAVE