Abhidnya Patharkar

About Abhidnya Patharkar

I have completed Ph.D. in Industrial Engineering from Arizona State University (ASU), specializing in Data Science, particularly in Machine Learning, Deep Learning, and Time Series Analysis. My studies include minors in Operations Research and Mechanical Engineering, showcasing a broad, interdisciplinary skill set. My additional abilities encompass Time Series Analysis, Classification, Regression, Forecasting, Clustering, Deep Neural Networks, Supervised and Unsupervised Machine Learning, Feature Selection, and Dimensionality Reduction.Research and Expertise:My research focuses on temporal (time-series) machine learning in biomedical applications. My key projects include- Designing an instance selection framework for multivariate time series (MTS) data- Developing a theoretical foundation for tackling heterogeneities in non-temporal and temporal biomedical datasets- Creating an interpretable classification framework for Mayo Clinic MTS data.These projects show my ability to tackle complex biomedical issues using advanced data science techniques.Technical SkillsI possess proficiency in programming languages including Python, SQL, and R, alongside expertise in utilizing tools such as Jupyter Notebook, Scikit-learn, NumPy, and deep learning frameworks including Keras, TensorFlow, and PyTorch.Industry Experience:My passion for research was ignited during my time as an R&D Engineer at BD Medical, where I conducted statistical analyses to optimize manufacturing processes. This experience, combined with my recent internship as a Data Scientist at Amazon Prime Video, has provided me with valuable industry insights and practical applications of data science.Academic Performance and Goals:I have excelled in courses like Mathematical Statistics, Probability and Stochastic Processes, Data Mining, Modern Temporal Learning and Advanced Mathematics.I am actively pursuing a Data Scientist/Research Scientist position in the industry. My goal is to leverage my expertise in data science to build highly efficient technologies that can make a significant impact.

Experience

1. Applied Ai Ml Senior Associate

   JPMorganChase

   Aug 2025 — Present · Houston, TX, US

   Design and deploy ML and LLM-based solutions across fraud detection, customer journey modeling, summarization, recommendation systems, and time-series forecasting.• Leverage Graph RAG for enhanced context-aware generation and QA using knowledge graphs.• Build Agentic AI systems for autonomous decision-making and workflow automation.• Collaborate with Technology, Product, Legal, Compliance, and Strategy teams to operationalize models.• Conduct data wrangling, modeling, and evaluation using Python and cloud-native tools.• Lead the end-to-end ML lifecycle including CI/CD, A/B testing, and production monitoring.

Education

• Arizona State University

  Doctor of Philosophy - PhD, Industrial Engineering

• University of Utah

  Master of Science (M.S.), Mechanical Engineering

  2015 — 2017

• Savitribai Phule Pune University

  Bachelor of Engineering (B.E.), Mechanical Engineering

  2009 — 2013

Skills

• Research
• Ptc Creo
• Goal Oriented
• Bill of Materials
• Project Management
• Solidworks
• Materials Science
• Finite Element Analysis
• C
• Programming
• Nastran
• Geometric Dimensioning & Tolerancing
• C++
• Mechanical Engineering
• Research and Development (R&D)
• Design of Jigs and Fixtures
• Lab View
• Nonprofit Organizations
• Six Sigma
• Microsoft Office
• Image J
• Microsoft Powerpoint
• Design for Manufacturing
• Ansys
• Microsoft Word
• Optistruct
• Simulations
• Product Development
• Manufacturing
• Powerpoint
• Microsoft Excel
• Easily Adaptable
• Management
• Lean M
• Phantom
• Autocad
• Statistical Process Control (Spc)
• Matlab
• Public Speaking
• Leadership