MS. Swati Tyagi, Researcher, University Of Delaware, United States.
Swati Tyagi, Ph.D. Candidate in Statistics, AI, and Machine Learning at the University of Delaware, is a distinguished researcher and applied scientist with extensive expertise in AI, ML, and data science. Known for her impactful work in large language models (LLMs) and ethical AI practices, Swati has contributed significantly to the fields of machine learning, predictive analytics, and algorithmic fairness. With over a decade of industry and academic experience, she has been recognized through awards, panel speaker roles, and key technical contributions.
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Strengths for the Award 🌟
Swati Tyagi demonstrates notable strengths in the field of AI and machine learning, particularly through her work on socially impactful topics such as bias mitigation in machine learning and the ethical applications of AI. Her research includes the development of models aimed at fairness and transparency in AI, showcased by her recent publications on bias reduction and explainable AI, making her a relevant and forward-thinking candidate for the award. Additionally, her strong technical skills (Python, TensorFlow, PyTorch, and more) and practical achievements, such as winning the JPMC Global Hackathon and being recognized by IEEE as a Senior Member, highlight her influence in the field and dedication to research excellence.
Areas for Improvement 📈
To further strengthen her candidacy, Swati could focus on increasing her visibility through additional publications in high-impact journals, which would increase her citation count and scholarly impact. Engaging in more collaborations could also diversify her research outputs and establish a broader research network. Swati might also consider expanding her focus to include more applied AI projects, potentially those with direct industrial or societal applications, which could provide practical proof of her research’s impact.
Education 🎓
Swati’s educational journey spans top institutions. She is pursuing her Ph.D. in Statistics, AI, and ML from the University of Delaware, where she has achieved a 3.7 GPA and the prestigious JPMC Graduate Scholarship. Prior to her Ph.D., she earned her Master’s in Business Analytics from the Indian Institute of Technology, Delhi, graduating with a 3.8 GPA, and completed her bachelor’s in computer science from JSS Academy of Technical Education, Noida.
Experience 💼
Swati’s professional path includes diverse roles in analytics, credit risk, and digital transformation. Currently, she serves as a Senior Applied Scientist – AI/ML at JPMC, where she spearheads LLM initiatives and financial application automation. Her previous roles include Lead Data Scientist at Elevate, Solution Consultant at Nucleus Software, and Senior Software Engineer at Newgen Software, each showcasing her versatility and ability to drive substantial financial impact through advanced data science solutions.
Research Interests 🔍
Swati’s research delves into areas such as large language models, ethical AI, and fairness in NLP and computer vision. She has also focused on topics like credit scoring, predictive analytics, and digital workflow automation. Her dedication to these areas has led to several publications and innovations that address real-world problems, including ethical considerations in AI and the mitigation of biases in model predictions.
Awards 🏆
Swati has been recognized with multiple prestigious awards. She won the JPMC Global Hackathon (2024), was honored as Best Presenter at an international AI/ML conference in Singapore, and is an IEEE Senior Member for her significant contributions to AI/ML. Additionally, she has been an invited panel speaker at the University of Delaware and served as a technical advisor for an LLM-based startup, reflecting her influence in the field.
Publications 📚
Swati’s research has been featured in leading journals and conferences. Key publications include:
- “E-VAN: Enhanced Variational Autoencoder Network for Mitigating Gender Bias in Static Word Embeddings” (2023), published in NLPIR ’22 and cited for advancing gender fairness in NLP.
- “Analyzing Machine Learning Models for Credit Scoring with Explainable AI and Optimizing Investment Decisions” – A foundational piece in credit scoring using explainable AI.
- “Promoting Gender Fair Resume Screening Using Gender-Weighted Sampling” (2024), presented at CMLDS ’24 by the Association for Computing Machinery, notable for its contributions to fair hiring practices.
Conclusion 🎓
Swati Tyagi’s impressive academic record, ongoing contributions in AI ethics and explainability, and recognition through awards and patents make her a promising candidate for the “Best Researcher Award.” Her skill set and research align well with the values of the award, especially given her dedication to ethical AI applications and commitment to excellence. With further engagement in impactful publications and collaborative projects, Swati is likely to continue making significant strides in the AI and machine learning fields.