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Hi, I'm Smriti Singh!

I'm a graduate student studying Computer Science at the University of Texas at Austin, advised by Dr. Jessy Li. Broadly, I'm passionate about using natural language processing for social good. 

I am an NLP researcher with experience in LLM research, multimodal generative AI, explainable and ethical AI, bias detection and mitigation in language models, data visualization/ exploration, and leveraging language models to answer important questions about healthcare and global politics. I aspire to use my skillset to develop products that make the world a better place. I hope you can learn a little more about me and my vision here. Please feel free to reach out to me with any additional questions that you might have! 


Featured Talks
What do I care about?
Making a difference:

"Success in creating true Artificial Intelligence would be the biggest event in human history." - Stephen Hawking. I firmly believe that NLP and Generative AI can be used to solve the most prominent challenges that society faces today, such as the global healthcare crisis we are facing and the ever increasing plethora of social issues. My long term goal is to create sustainable algorithms that are capable of making intelligent decisions. 


Sadly, only 28% of women work in STEM even today. I strongly believe in women and minorities receiving equal treatment and equal opportunities. I am constantly trying to advocate the motto, "Diversity drives innovation" through my community outreach endeavors and research activities too. My work with WiCS UT, ACM-W, Women in AI and Women Techmakers is an effort to increase the involvement of undergraduate women in technology, particularly artificial intelligence. 

What am I currently working on?

I am currently pursuing my Masters in Computer Science at the University of Texas at Austin, with a minor in Computational Linguistics and a specialisation in ethical AI. My thesis focuses on the ability of large language models to peceive and interact with human emotions. As an NLP researcher, I am also  working on projects that look to detect and mitigate various biases (socioeconomic, gender, race, etc.) in current state of the art language models.

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