6 Influential Indian Women in AI
On this International Women’s Day, we celebrate and recognize the incredible achievements of women in Artificial Intelligence who have made significant contributions to the field. These remarkable Indian women in AI have shattered stereotypes, pushed boundaries, and inspired countless individuals with their innovative work. From pioneering new algorithms to leading research teams and founding groundbreaking startups, they have left an indelible mark on the landscape of AI. As we honor their accomplishments, we also acknowledge the importance of diversity and inclusion in technology.
These women not only showcase the immense talent within the AI community but also serve as role models for future generations of women in STEM. Today, we applaud their dedication, brilliance, and unwavering commitment to advancing the frontiers of AI, paving the way for a brighter and more inclusive future. Let’s dive into the stories of six remarkable Indian women in AI who are redefining what’s possible in AI, each with a unique journey and a shared goal of pushing boundaries and inspiring the next generation.
1. Aakanksha Chowdhery
After earning a bachelor’s degree in electrical engineering from IIT Delhi, Aakanksha Chowdhery pursued a Ph.D. program at Stanford University. Reflecting on her career, she expressed, “Teaching and mentoring students has always been rewarding, but academia didn’t always go as planned.” Before joining Princeton University as an associate research scholar in 2017, she served as a postdoctoral researcher at Microsoft Research. Aakanksha Chowdhery recalled her time at Microsoft, noting, “I had the opportunity to create tangible solutions through my research.”
Currently, as the Director of Machine Learning at Qualcomm AI Research, she focuses on deep learning algorithms for computer vision and speech recognition. Her expertise contributes to the development of efficient and accurate deep learning models for mobile devices, aligning with her goal to enhance AI capabilities for edge devices and improve user experiences.
Chowdhery’s impressive career spans a wide range of research areas, including signal processing, machine learning, edge computing, and mobile networked systems. Her contributions have impacted industry consortiums and standards, such as the OpenFog Consortium and DSL standards.
One of her significant achievements is the book she primarily authored, “PaLM: Scaling Language Modeling with Pathways,” showcasing a massive AI model with 540 billion parameters designed for language comprehension and generation.
2. Niki Parmar
Niki Parmar, a co-author of the groundbreaking research paper “Attention Is All You Need,” which pioneered the development of transformers, has had a remarkable career in the field of machine learning. She embarked on her journey in the field during her undergraduate years, sparked by the first MOOCs by Andrew Ng and Peter Norvig on ML and AI. After earning her Masters degree from the University of Southern California, Parmar began her career as a research assistant at the Computational Social Science Lab, USC.
Her career path led her to prominent roles at Google Research and Google Brain, where she delved into end-to-end deep learning systems. Reflecting on her time there, Parmar stated, “Here, I got the opportunity to learn and work on end-to-end deep learning systems that were trying to create alternative ways of solving NLP problems.”
Throughout her career, Parmar has made significant contributions to the field, with 28 published papers focusing on areas such as self-attention, inductive biases, and their impact on improving models in machine translation, language modeling, and other tasks related to natural language processing.
In 2021, Parmar co-founded Adept AI, and since 2023, she has been actively involved as the co-founder of Essential AI, alongside Ashish Vaswani, another co-author of the “Attention Is All You Need” paper. The startup has received $56.5 million in funding, with support from industry giants such as AMD, Google, and Nvidia.
Additionally, Parmar serves as a Research Scientist at Google Research India, where her recent work has focused on natural language understanding and generation. Her research projects aim to enhance conversational AI and language models, ultimately improving the capabilities of AI systems in understanding and generating human-like text.
3. Anima Anandkumar
Anima Anandkumar, originally from Mysore, obtained her Ph.D. in computer science from Cornell University following her master’s degree from IIT Madras. She currently holds the Bren Professorship at the California Institute of Technology (Caltech), focusing on machine learning.
Previously, Anandkumar served as the director of NVIDIA’s machine learning research division, overseeing research on deep learning, tensor algebraic techniques, and non-convex optimization challenges. Her extensive research output is evidenced by her remarkable h-index of 74.
With numerous accolades to her name, including the ACM Grace Hopper Award and the IEEE Fellow Award, Anandkumar’s research spans a broad spectrum of topics. She has contributed significantly to machine learning research, particularly in the fields of deep learning and optimization.
At Caltech, Anandkumar serves as the Director of ML Research at NVIDIA, where she has played a pivotal role in developing efficient algorithms for large-scale machine learning tasks. Her work has been recognized with the prestigious NeurIPS Test of Time Award in 2020 for her paper on tensor decompositions.
4. Monisha Ghosh
Monisha Ghosh, currently a professor at the University of Notre Dame and an Adjunct Research Professor at the University of Chicago, embarked on her academic journey with a bachelor’s degree from IIT Kharagpur in 1986. She later earned her PhD in electrical engineering from the University of Southern California in 1991. In addition to her academic pursuits, Ghosh has been actively involved in national telecommunications policy and research.
Recently completing her tenure as the Chief Technology Officer (CTO) at the Federal Communications Commission (FCC) in June 2021, Ghosh focused her work on national strategy and technological specifications for broadband wireless communications. This included spearheading the development of rules for the 6 GHz unlicensed bands, standardizing broadband signal measurements, and advancing open RAN technology.
Prior to her role at the FCC, Ghosh served as a rotating program director at the NSF from 2017 to 2019, where she managed wireless networking research and pioneered the application of machine learning in wireless networks.
Ghosh’s research contributions are notable, particularly during her time as a research professor at the University of Chicago. Her research interests span a wide range of wireless technologies, including those for the Internet of Things (IoT), 5G cellular systems, next-generation Wi-Fi, and spectrum sharing.
Before her academic appointments, Ghosh gained valuable experience in industrial research and development. She held positions at Interdigital, Philips Research, and Bell Laboratories.
Monisha Ghosh’s recent work continues to be at the forefront of innovation, focusing on the application of AI and machine learning in wireless communications and spectrum management. She has led initiatives exploring AI-driven approaches to enhance spectrum utilization and efficiency, making significant strides in promoting AI technologies for improving connectivity and wireless infrastructure.
5. Suchi Saria
Suchi Saria, with a master’s degree in computer science and a doctorate in electrical engineering with a focus on statistics from Stanford University, holds key roles in the healthcare technology sector. Currently serving as the CEO of Bayesian Health and the founding research director of the Malone Center for Engineering in Healthcare, she also leads the Machine Learning and Healthcare Lab at Johns Hopkins University.
At Johns Hopkins, Saria collaborates across various departments, including computer science, statistics, medicine, and health policy, to advance healthcare technology using machine learning. Her innovative work has garnered her numerous accolades, including the designation of Young Global Leader by the World Economic Forum and the prestigious Sloan Research Fellowship. Additionally, she was recognized as one of the “35 Innovators Under 35” by the MIT Technology Review.
Her Google Scholar profile showcases an impressive portfolio of 109 papers focusing on healthcare, machine learning, and their intersection. Saria’s research contributions include the development of tools for clinical decision-making, models for personalized care, and algorithms for predicting illnesses such as sepsis and cardiac arrest. She addresses challenges in managing uncertain medical data and drawing causal inferences, especially in chronic conditions like scleroderma.
Suchi Saria is an Associate Professor at the Johns Hopkins University School of Computer Science, where her recent research is centered on developing AI-driven healthcare solutions for early detection and diagnosis. Her work extends to creating machine learning models to predict patient deterioration and enhance clinical decision-making processes.
6. Parvati Dev
Parvati Dev, currently Head of Data Science at Pype, an AI-powered construction platform, has a diverse educational background. Following her undergraduate studies at IIT Kharagpur, she pursued master’s and doctoral degrees in technology and education at Stanford University.
With an impressive portfolio of 94 publications, Parvati has made substantial contributions to various fields, including haptics, virtual patient simulations, 3D anatomy models, and surgical simulation. Her groundbreaking work at Stanford University has established her as a pioneer in medical education technology, especially in digitizing curriculums.
Parvati Dev at Pype applies AI and data science to boost construction project efficiency and productivity. She played a crucial role in developing AI algorithms for automating project documentation and workflow analysis, highlighting her expertise.
Dev actively uses AI to address challenges within the construction industry and drive innovation. Her work at Pype reflects her commitment to leveraging AI for transformative solutions in construction project management.
Conclusion
The stories of these six influential Indian women in AI paint a vivid picture of innovation, determination, and excellence. From pioneering new algorithms to leading research teams and founding groundbreaking startups, they have significantly shaped the trajectory of AI.
As India remains a driving force in the global tech scene, these women in AI stand as inspiring beacons. Their contributions not only advance AI but also pave the path for a more inclusive and diverse future in technology. As we celebrate their accomplishments, we’re reminded that AI’s future isn’t just about technology—it’s about diverse minds shaping it. These Indian women in AI aren’t just making waves; they’re leading a revolution that promises to transform industries and inspire generations.
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Let’s continue to uplift and empower each other in the journey towards a more inclusive and innovative future.
