Anil Ananthaswamy Named “HITS Journalist In Residence


May 14, 2023


The Heidelberg Institute for Theoretical Studies gives science journalists the opportunity to deepen their knowledge of computer-based, data-driven science with a longer stay at the institute. For the fifth time, the program was announced internationally. Candidates from six continents applied. A committee of science journalists and scientists selected Anil Ananthaswamy (USA/India) as “HITS Journalist in Residence”.   The award-winning science journalist and book author plans to use his stay to interact with the HITS scientists in machine learning methods.  

Indian-American science journalist and author Anil Ananthaswamy is the 11th “Journalist in Residence” at the Heidelberg Institute for Theoretical Studies (HITS), having joined the institute in late April. 

Anil Ananthaswamy is an award-winning science journalist and former staff writer and deputy news editor at New Scientist magazine. As a freelance journalist, he writes for Quanta, Scientific American, New Scientist and Nature, among others. He’s the author of three popular science books, a former guest editor at the University of California, Santa Cruz’s science writing program, and he teaches science journalism at the National Centre for Biological Sciences, Bangalore, India. Before he switched to science writing, Anil had trained as an electronics and computer engineer at the Indian Institute of Technology, Madras (BSEE) and the University of Washington, Seattle (MSEE), and was working as a software engineer in Silicon Valley.  

In recent years, Anil Ananthaswamy has been drawn to writing about Machine Learning (ML) and computational neuroscience.  This year, he has finished the first draft of a new book on the mathematics of ML, titled Why Machines Learn. To aid his book, he has written code that illustrates the basic principles of some key machine learning algorithms.

During his stay at HITS, Anil Ananthaswamy plans to link all these activities: “I would like to think deeply about developing modules that combine journalism, coding, algorithms and math”, he says. To this end, he is also interested in learning from the ML expertise in the HITS research groups and in understanding the use of these methods in astrophysics and life sciences. He’s also keen on interacting with the Natural Language Processing (NLP) group at HITS, to better understand the strengths and limitations of large language models.