I am a PhD researcher specializing in Data Science with extensive experience in predictive analytics, scalable machine learning pipelines, and Bayesian modeling. I have a strong background in implementing cloud-native solutions for healthcare and pharmaceuticals, applying solid software engineering principles, and building intuitive dashboards that enable real-time data exploration. I am passionate about developing robust AI systems with MLOps and LLMOps frameworks, integrating large language models, and deploying end-to-end machine learning workflows in production environments. My work spans collaborating with international research teams and industry partners to build impactful data-driven applications.…

Shubbham Gupta

I am a PhD researcher specializing in Data Science with extensive experience in predictive analytics, scalable machine learning pipelines, and Bayesian modeling. I have a strong background in implementing cloud-native solutions for healthcare and pharmaceuticals, applying solid software engineering principles, and building intuitive dashboards that enable real-time data exploration. I am passionate about developing robust AI systems with MLOps and LLMOps frameworks, integrating large language models, and deploying end-to-end machine learning workflows in production environments. My work spans collaborating with international research teams and industry partners to build impactful data-driven applications.…

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I am a PhD researcher specializing in Data Science with extensive experience in predictive analytics, scalable machine learning pipelines, and Bayesian modeling. I have a strong background in implementing cloud-native solutions for healthcare and pharmaceuticals, applying solid software engineering principles, and building intuitive dashboards that enable real-time data exploration.

I am passionate about developing robust AI systems with MLOps and LLMOps frameworks, integrating large language models, and deploying end-to-end machine learning workflows in production environments. My work spans collaborating with international research teams and industry partners to build impactful data-driven applications.

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Experiencia laboral

PhD Researcher at University College Dublin
September 1, 2020 - April 30, 2025
Designed and developed 'MetaboVariation', a novel multivariate Bayesian generalised linear model capturing intra-individual variations in metabolite levels across repeated measurements. Applied SOLID principles to create a user-friendly R package with an interactive Shiny dashboard, enabling clinicians to explore model outputs easily. Collaborated with international researchers and presented findings through interactive dashboards, winning the Best Poster Award at a major conference. Authored peer-reviewed publications and contributed to open-source packages.
Data Science and Artificial Intelligence Research Intern at Novartis Ireland Limited
June 1, 2021 - September 30, 2021
Built a Python-based survival modeling pipeline analyzing real-world data of over 40,000 patients to identify predictors of Atherosclerotic Cardiovascular Disease outcomes using Cox and parametric survival models. Developed interactive dashboards with Plotly and SHAP, enabling dynamic filtering by risk factors. Followed SOLID principles for clean code integrated into Novartis' internal framework. Delivered findings in an in-house seminar, demonstrating data-driven methods in clinical approaches.
Research Fellow (Short-term) at University College Dublin
January 1, 2021 - June 30, 2021
Developed the Sheepdog Algorithm, a bio-inspired metaheuristic feature selection tool inspired by sheepdog herding behavior to reduce dimensionality by balancing low feature count and high accuracy. Integrated with machine learning models such as Random Forest, SVM, and Logistic Regression for dynamic feature pruning, achieving a 10% improvement in predictive performance based on benchmarking and A/B testing on biomedical datasets. Presented algorithm findings at major European and international conferences.
Master's Researcher at University College Dublin
April 1, 2020 - August 31, 2020
Identified key risk factors for clinical mastitis using Cox regression models, mixed-effects models, and L1 penalization. Enhanced early detection strategies by estimating survival curves and evaluating model fit through residual analysis, contributing to better disease management protocols.

Educación

PhD at University College Dublin
September 1, 2020 - April 30, 2025
MSc at University College Dublin
September 1, 2019 - August 31, 2020
B.Tech at Guru Gobind Singh Indraprastha University
September 1, 2015 - August 31, 2019

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Experiencia en el sector

Healthcare, Life Sciences, Financial Services, Software & Internet

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