Manish Gupta is a Senior Director at Google DeepMind and leads AI research teams across India and Japan.
His career covers high-performance computing, AI research, software systems, entrepreneurship, and technology leadership.
His work focuses on practical and inclusive AI across areas such as language, healthcare, agriculture, and reasoning.
Artificial intelligence is moving from research labs into everyday life. Few Indian technology leaders have worked across this transition as closely as Dr. Manish Gupta. As Senior Director at Google DeepMind, Gupta leads AI research teams across India and Japan. His work spans machine intelligence, software systems, and practical AI applications. He also brings decades of experience across research, industry, and entrepreneurship.
Gupta's technology career began well before today's generative AI boom. He earned his PhD in Computer Science from the University of Illinois Urbana-Champaign. Gupta later held senior research roles at IBM and Xerox. At IBM's T.J. Watson Research Center, he led work on system software for the Blue Gene/L supercomputer.
This experience gave him a strong foundation in computing systems and large-scale technology. His career later expanded into AI research, entrepreneurship, and technology leadership. Gupta also led VideoKen, a video technology startup. His professional record includes around 75 research papers and 19 US patents.
He is a Fellow of ACM and the Indian National Academy of Engineering. He has also received a Distinguished Alumnus Award from IIT Delhi.
Gupta has played an important role in expanding Google's AI research presence in India. Today, his teams work on problems connected to language, voice, model efficiency, and reasoning.
He described Google's Bengaluru research operation as an important part of its frontier AI efforts. The India team has around 75 researchers, according to a recent interview.
Several researchers returned to India after completing advanced degrees overseas. Gupta believes meaningful research problems can help attract global Indian talent back home. This approach reflects a wider shift in India's technology ecosystem. The country is increasingly becoming a research destination, not simply an engineering hub.
One of Gupta's strongest themes is inclusive AI. India presents an unusual challenge because of its many languages, cultures, and social contexts. He argues that AI cannot simply translate English responses into Indian languages. Models need to understand local context and cultural differences.
This thinking has influenced work around Project Vaani and Indian-language datasets. Such efforts aim to improve speech and language technologies for communities often overlooked by mainstream systems.
Gupta has also highlighted healthcare applications. Google DeepMind's diabetic retinopathy work was first tested in Madurai. The technology has since supported more than 600,000 screenings worldwide. It continues to support screening efforts in India and Thailand.
Gupta's vision extends beyond building AI specifically for India. He sees India's unique challenges as opportunities for developing solutions with wider applications.
Agriculture offers one example. AI models developed for Indian agricultural needs have expanded to countries including Malaysia, Vietnam, Indonesia, and Japan.
Healthcare provides another promising area. Google DeepMind's work with Indian institutions is exploring AI applications for medical research and healthcare delivery.
This approach gives India a distinctive position in the global AI race. Local problems can become testing grounds for technologies with international relevance.
Gupta's work also reflects how AI research is changing. Today's systems need more than strong prediction capabilities. They increasingly need reasoning, efficiency, multimodal understanding, and useful interaction. His teams are involved in research supporting Google's broader AI ecosystem, including Gemini.
Gupta has also argued that India needs greater ambition in AI. He has called for more startups capable of competing globally and stronger research investment from Indian companies. India has talent, but retaining and empowering that talent remains crucial, according to Gupta.
Gupta does not frame AI simply as a replacement for human work. His view focuses more on using technology to expand what people can accomplish. This philosophy connects with his broader emphasis on inclusive AI. The goal is to make advanced technology useful beyond a narrow group of users.
For Gupta, responsible development remains equally important. He has stressed the need for safety, evaluation, ethics, and scientific rigour alongside rapid innovation. As AI enters healthcare, agriculture, education, and everyday applications, that balance will become increasingly important. Gupta's career shows how Indian technology leadership can influence both local innovation and the global AI conversation.