Like many engineers, Sarang Gupta spent his childhood tinkering with on a regular basis objects round the home. From a younger age he gravitated to tasks that would make a distinction in somebody’s on a regular basis life.
When the household’s microwave plug broke, Gupta and his father found out the way to repair it. When a drawer deal with began jiggling annoyingly, the teenager made positive it didn’t achieve this for lengthy.
Sarang Gupta
Employer
OpenAI in San Francisco
Job
Information science employees member
Member grade
Senior member
Alma maters
The Hong Kong College of Science and Know-how; Columbia
By age 11, his curiosity expanded from nuts and bolts to software program. He realized programming languages equivalent to Basic and Logo and designed easy packages together with one which helped a neighborhood restaurant automate on-line ordering and billing.
Gupta, an IEEE senior member, brings his mixture of curiosity, hands-on problem-solving, and a want to make issues work higher to his function as member of the data science employees at OpenAI in San Francisco. He works with the go-to-market (GTM) group to assist companies undertake ChatGPT and different merchandise. He builds data-driven fashions and programs that assist the gross sales and advertising and marketing divisions.
Gupta says he tries to make sure his work has an influence. When making choices about his profession, he says, he thinks about what AI options he can unlock to enhance individuals’s lives.
“If I had been to sum up my general objective in a single sentence,” he says, “it’s that I need AI’s advantages to succeed in as many individuals as doable.”
Pursuing engineering by a enterprise lens
Gupta’s early curiosity in tinkering and programming led him to decide on physics, chemistry, and math as his higher-level topics at Chinmaya International Residential School, in Tamil Nadu, India. As a part of the highschool’s International Baccalaureate chapter, college students choose three topics through which to specialize.
“I used to be excited by engineering, together with the theoretical a part of it,” Gupta says, “However I used to be at all times extra within the functions: the way to promote that expertise or the way it ties to the actual world.”
After graduating in 2012, he moved abroad to attend the Hong Kong University of Science and Technology. The college provided a dual bachelor’s program that allowed him to earn one diploma in industrial engineering and one other in enterprise administration in simply 4 years.
In his spare time, Gupta constructed a smartphone app that allow college students add their class schedules and discover classmates to eat lunch with. The app didn’t take off, he says, however he loved creating it. He additionally launched Pulp Adverts, a enterprise that printed ads for scholar teams on tissues and paper napkins, which had been distributed within the faculty’s cafeterias. He made some cash, he says, however shuttered the enterprise after a few 12 months.
After graduating from the college in 2016, he determined to work in Hong Kong’s monetary hub and joined Goldman Sachs as an analyst within the financial institution’s operations division.
From finance to course of optimization at scale
After two events agree on securities transactions, the financial institution’s operations division ensures that the commerce particulars are recorded accurately, the securities and funds are able to switch, and the transaction settles precisely and on time.
As an analyst, Gupta’s activity was to search out bottlenecks within the financial institution’s workflows and repair them. He recognized a possibility to automate commerce reconciliation: when analysts would manually examine information throughout spreadsheets and programs to verify a transaction’s particulars had been constant. The method helped guarantee monetary transactions had been recorded precisely and settled accurately.
Gupta constructed inner automation instruments that pulled commerce information from totally different programs, ran validation checks, and generated reviews highlighting any discrepancies.
“As a substitute of analysts manually checking giant datasets, the instruments mechanically flagged solely the instances that required investigation,” he says. “This helped the group spend much less time on repetitive verification duties and extra time resolving complicated points. It was additionally my first actual publicity to how software program and information programs might dramatically enhance operational workflows.”
“Whether or not it’s serving to an individual enhance a trait like that or driving efficiencies at a enterprise, AI simply has a lot potential to assist. I’m excited to be a bit of a part of that.”
The expertise made him understand he needed to work extra deeply in expertise and data-driven programs, he says. He determined to return to highschool in 2018 to check information science and AI, when the fields had been simply starting to surge into broader consciousness.
He found that Columbia provided a devoted grasp’s diploma program in information science with a concentrate on AI. After being accepted in 2019, he moved to New York City.
All through this system, he gravitated to the utilized aspect of machine learning, taking programs in utilized deep learning and neural networks.
One in every of his main tutorial highlights, he says, was a mission he did in 2019 with the Brown Institute, a joint analysis lab between Columbia and Stanford centered on utilizing expertise to enhance journalism. The group labored with The Philadelphia Inquirer to assist the newsroom employees higher perceive their protection from a geographic and social standpoint. The mission highlighted “information deserts”—underserved communities for which the newspaper was not offering a lot protection—so the publication might redirect its reporting sources.
To determine these areas, Gupta and his team built tools that extracted locations such as road names and neighborhoods from information articles and mapped them to visualise the place many of the protection was concentrated. The Inquirer carried out the software in a number of methods together with a brand new web page that aggregated stories about COVID-19 by county.
“Journalism was an fascinating downside set for me, as a result of I actually prefer to learn the information day by day,” Gupta says. “It was a possibility to work with an actual newsroom on an issue that felt actually impactful for each the enterprise and the local people.”
The GenAI inflection level
After incomes his grasp’s diploma in 2020, Gupta moved to San Francisco to affix Asana, the corporate that developed the work administration platform by the identical title. He was drawn to the chance to work for a comparatively small firm the place he might have end-to-end possession of tasks. He joined the group as a product data scientist, specializing in A/B testing for brand spanking new platform options.
Two years later, a brand new alternative emerged: He was requested to steer the launch of Asana Intelligence, an inner machine studying group constructing AI-powered options into the corporate’s merchandise.
“I felt I didn’t have sufficient expertise to be the founding information scientist,” he says. “However I used to be additionally actually within the area, and spinning up an entire machine studying program was a possibility I couldn’t flip down.”
The Asana Intelligence group was given six months to construct a number of machine studying–powered options to assist clients work extra effectively. They included automated summaries of mission updates, insights about potential dangers or delays, and suggestions for subsequent steps.
The group met that objective and launched a number of different options together with Smart Status, an AI software that analyzes a mission’s duties, deadlines, and exercise, then generates a standing replace.
“If you lastly launch the factor you’ve been engaged on, and also you see the utilization go up, it’s exhilarating,” he says. “You are feeling like that’s what you had been constructing towards: customers truly seeing and benefiting from what you made.”
Gupta and his group additionally translated that first wave of labor into reusable frameworks and documentation to make it simpler to create machine studying options at Asana. He and his colleagues filed a number of U.S. patents.
On the time he took on that function, OpenAI launched ChatGPT. The mainstreaming of generative AI and large language models shifted a lot of his work at Asana from mannequin growth to assessing LLMs.
OpenAI captured the eye of individuals all over the world, together with Gupta. In September 2025 he left Asana to affix OpenAI’s information science group.
The transition has been each energizing and humbling, he says. At OpenAI, he works carefully with the advertising and marketing group to assist information strategic choices. His work focuses on creating fashions to grasp the effectivity of various advertising and marketing channels, to measure what’s driving influence, and to assist the corporate higher attain and serve its clients.
“The tempo may be very totally different from my earlier work. Issues transfer rapidly,” he says. “The trade is extraordinarily aggressive, and there’s a robust expectation to ship quick. It’s been a fantastic studying expertise.”
Gupta says he plans to remain within the AI area. With expertise evolving so quickly, he says, he sees monumental potential for activity automation throughout industries. AI has already reworked his core software engineering work, he says, and it’s helped him improve areas that aren’t pure strengths.
“I’m not author, and AI has been enormous in serving to me body my phrases higher and present my work more clearly,” he says. “Whether or not it’s serving to an individual enhance a trait like that or driving efficiencies at a enterprise, AI simply has a lot potential to assist. I’m excited to be a bit of a part of that.”
Gupta has been an IEEE member since 2024, and he values the group as each a technical useful resource and knowledgeable community.
He recurrently turns to IEEE publications and the IEEE Xplore Digital Library to learn articles that preserve him abreast of the evolution of AI, information science, and the engineering profession.
IEEE’s member directory instruments are one other invaluable useful resource that he makes use of typically, he says.
“It’s been a good way to attach with different engineers in the identical or comparable fields,” he says. “I really like sharing and listening to about what of us are engaged on. It brings me exterior of what I’m doing day after day.
“It conjures up me, and it’s one thing I actually take pleasure in and cherish.”
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