Astha Garg

AI Development Architect at Lenovo

Singapore
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Summary

👤
Senior
🎓
Top School
Astha Garg is an AI Development Architect and builder-scientist with a decade of experience turning complex datasets—time-series, IoT, and natural language—into production-grade AI products across chemicals, semiconductors, retail and sustainability. She blends deep research (PhD-level work on time-series anomaly detection published in TNNLS) with hands-on engineering, having led teams to deliver RAG-based chatbots, recommendation systems, and scalable ML modules that cut manual work by up to 80%. At companies from A*STAR and Citrine to Terrascope and Lenovo she has driven end-to-end solutions from concept to continuous product while partnering closely with business, product and domain experts. Her recent focus is on generative-AI, multi-agent systems and robust LLM engineering for real-world deployments. Notably, she bridges lab-scale experimentation and field-ready systems—automating large-scale data pipelines and evaluation protocols informed by thousands of experiments. Based in Singapore, she’s equally comfortable as scientist, product engineer, and pragmatic builder who prioritizes measurable business impact.
code10 years of coding experience
job8 years of employment as a software developer
bookDoctor of Philosophy (Ph.D.) Chemical Engineering, Doctor of Philosophy (Ph.D.) Chemical Engineering at Penn State University
bookIndian Institute of Technology Bombay
bookMatriculation, Matriculation at J. H. Ambani School
languagesBengali, Hindi, English
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Github Skills (29)

autoencoder10
residual-networks9
anomaly-detection9
time-series8
evaluation8
prediction-model7
deep-learning7
uncertainty6
regression6
machine-learning6
classification6
wikipedia6
random-forest5
keras5
recurrent4

Programming languages (4)

ScalaRoffJupyter NotebookPython

Github contributions (5)

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astha-chem/mvts-ano-eval

Jul 2021 - May 2022

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)
Contributions:1 review, 5 commits, 2 PRs in 10 months
autoencoderanomalydeep-learninganomaly-detectionevaluation
Contributions:48 commits, 39 pushes in 1 month
residual-networksdeep-learningresidualtensorflowkeras
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Astha Garg - AI Development Architect at Lenovo