Priyanka Makhijani
Development
New york, United States
Skills
Machine Learning (ML)
About
PRIYANKA MAKHIJANI's skills align with IT R&D Professionals (Information and Communication Technology). PRIYANKA also has skills associated with Database Specialists (Information and Communication Technology). PRIYANKA MAKHIJANI has 6 years of work experience.
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Work Experience
DEEP LEARNING ENGINEER INTERN (MedTech)
SIEMENS HEALTHINEERS
May 2018 - December 2018
- Researched & developed imaging solutions for clinical applications by applying deep learning and computer vision techniques on 3-D neuro DynaCT images. Implementation of fully automatic stenosis(lesion) segmentation by developing prototypes of Deep neural networks: Extraction of features and stenosis detection using CNN for DICOM reconstructed image formats. Conducting experiments on different model choices to achieve competitive performance by devising custom loss and metric functions and analyzing images for information rich exemplars. Key Strengths: Tensorflow, Keras, ITK-SNAP, DICOM Formatted Images, Dyna-CT Images, Semantic Segmentation.
ILLINOIS INSTITUTE OF TECHNOLOGY
January 2018 - May 2018
- Jan. 2018 to May 2018 Conducting weekly tutorials on software models, postgreSQL, heat maps, postGIS using python, node.js and ECMAScript6. Assisted student grade evaluation and record keeping.
UNDERGRADUATE INTERN
THINK & LEARN PVT. LTD
January 2016 - June 2016
- Developed 'Advanced E-Learning system'. A web-based application. Implemented features - e-mail sending, upload & download of PDFs, private message feature, course wise weekly tests and discussion forum for students/faculty. Required JavaServer Pages, servlets, Java API for RESTful services using Java EE web profile and SQL.
SOFTWARE DEVELOPMENT ENGINEER INTERN
DOTPOWER
June 2015 - July 2015
- Worked on 'Tender Management System'. A web-based application to help local bidders in Tunis. Using HTML, MySQL, phpyadmin for the administration of MySQL and Wamp as Apache server to work with PHP.
RESEARCH ASSISTANT
ILLINOIS INSTITUTE OF TECHNOLOGY- LINGUISTIC COGNITION LAB, DEPT
April 2019 - May 2019
- Deep learning approaches for the analysis of synchrotron data of materials used in energy and environmental applications. Key Strengths: PyTorch, Python, Larch library for XAFS data analysis.
Senior Lead Machine Learning Engineer (SaMD)
IDEA EVOLVER LLC
May 2023 - Present
- Ideating Solutions for ACNU platform - First kind approach for Rx to OTC switch in The USA market for FDA approved drugs. Assisted with designing Drug database - matching prescribing information on drug products with a 85% match. Utilizing supervised machine learning approach for ACNU feasibility with a precision of 93%. Utilizing Generative AI approach with LLMs to fine-tune foundation models on self-assessment data to predict outcome for cholesterol and hypertension medications in conjunction with ACNU feasible drugs with an accuracy pf 98%. Adherence modeling to analyze cholesterol medication qualified users with 88% accuracy. Key strengths: Statistical analysis, Clinical Trials, ACNU, Generative AI, LLMs, explainable AI.
Machine Learning Scientist
CHEMIMAGE CORPORATION
December 2021 - May 2023
- Designing Deep Learning Models for Hyperspectral Imaging (HSI) for minimally invasive surgeries done laparoscopically to detect real-time critical structures. Worked on ex vivo Tissue Vis-NIR Signatures + Key Wavelengths to understand different critical structures reflectance and absorbance standards using univariate analysis. Using Supervised and semi-supervised approach to analyze images and driving in-house GT methodology in medical imaging and post-hoc approaches to meet improvement in overall system performance. Designing end-to-end algorithms with custom training parameters and evaluation on blind datasets for robust and generalizable models. Researched novel approaches for CNN models in TensorFlow for semantic segmentation with fuzzy GT. Precision on segmentation model >80% and recall > 90%. Key strengths: Image Processing, Deep Learning, Statistical analysis, Clinical Trials, Fuzzy Ground Truth, Hyperspectral Images, Image Registration.
SOFTWARE ENGINEER - Data Science and NLP
DEEPNORTH INC
May 2019 - December 2021
- Python development for data analysis, statistical inference and visualization on large datasets. Worked on prescriptive and predictive analytics to offer more insights about metrics directly impacting customers to take decisions. Worked on NLP platform integrated as a part of dashboard. Key strengths: Structured Large Datasets, Machine Learning, Statistical analysis, Retail Analytics, Hypothesis Design, GCP, Microsoft Azure
Education
MANIPAL UNIVERSITY JAIPUR
Bachelors of Technology
July 2012 - July 2016
Masters of Computer Science
