Shubhomoy Das
Senior Machine Learning Scientist at Espressive
Miami, Florida, United States
Summary
👤
Senior🎓
Top SchoolShubhomoy Das is a Senior Machine Learning Scientist with 11 years of experience blending rigorous statistics and production-grade engineering to solve anomaly detection, NLP, and enterprise agent problems. He holds a PhD in Computer Science and a strong MS in Statistics, and has transitioned research on ensembles, active learning, and interpretability into open-source implementations used for anomaly detection and adversarial analysis. At Espressive he combines large language models with lightweight ML systems to build smarter enterprise assistants, and previously improved search, recommendation, and ticketing workflows for reinsurance and service centers. Comfortable shifting between research and product delivery, he has a rare track record of integrating user feedback, active learning, and interpretability into deployed systems. His GitHub showcases practical, reproducible AD methods and active-learning tooling, reflecting both academic depth and production focus.
10 years of coding experience
19 years of employment as a software developer
Bachelor's Degree, Electrical Engineering, Bachelor's Degree, Electrical Engineering at Govt. Engg. College, Jabalpur, MP, IndiaDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Oregon State University
Github Skills (18)
anomaly-detection10
python10
machine-learning10
generative-adversarial-network10
autoencoder10
tensorflow10
ensemble-learning9
time-series9
active-learning9
data-analysis9
scikit8
graph-neural-network8
scikit-learn8
adversarial-attacks8
n7
Programming languages (1)
Github contributions (5)
shubhomoydas/ad_examples
Nov 2017 - Dec 2019
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:447 commits, 9 PRs, 417 pushes in 2 years 1 month
Contributions summary:Shubhomoy contributed significantly to anomaly detection methods within the repository, including implementations of various techniques. The commits show the user's focus on practical aspects, such as code fixes and reorganizations. The user demonstrates understanding of the underlying concepts and the application of these techniques, including the incorporation of label feedback, along with an interest in integrating adversarial attacks within the project.
anogandiversityruleadversarialensemble
shubhomoydas/pyaad
Feb 2017 - Dec 2017
Contributions:45 commits, 41 pushes, 1 branch in 10 months
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