class ShivaniSutrave:
def __init__(self):
self.role = "MS Computer Science @ Texas A&M University–San Antonio"
self.title = "Full Stack AI Engineer"
self.focus = ["Research-driven AI", "System Analysis", "Scalable Solutions"]
self.interests = ["Artificial Intelligence", "Machine Learning", "LLMs",
"Cloud Computing", "DevOps", "Data Analytics"]
self.location = "San Antonio, TX"
self.currently = "Benchmarking LLM-generated code & building deep learning pipelines"
def say_hi(self):
print("Always exploring how AI systems can be evaluated, scaled, and trusted!")|
ML system predicting SME loan default risk using alternative data (GST filing, UPI transactions, cash flow) with SHAP explainability.
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Benchmarking LLM-generated code against human-written implementations using performance and correctness metrics. |
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Deep learning-based wildfire risk prediction using satellite imagery. |
Development of AI agents and conversational chatbots for automation, analytics, and information retrieval. |
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Full-stack JavaScript app delivering live, context-aware suggestions. Live demo →
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SwiftUI prototype mapping emotional wellness to physical activity — recommends workouts (yoga for stress, lifting for energy) using Swift Charts to track emotional trends.
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Python-based hospital operations system (latest project — add a description on GitHub for it to show up here).
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