Machine Learning Los Angeles

Sanskruti Raut Email: ********@***.***

Portfolio: sanskrutiraut14.wixsite.com/mysite Mobile: +1-213-***-**** Github: github.com/sanskruti-raut LinkedIn: https://www.linkedin.com/in/sanskruti-raut/ Education

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University of Southern California, Los Angeles, USA Los Angeles, USA Master of Science, Electrical Engineering (Machine Learning and Data Science) Aug 2023 - May 2025 Courses: Linear Algebra, Probability, Deep Learning, Machine Learning, Natural Language Processing, Cloud Computing

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Maharashtra Institute of Technology Pune, India

Bachelor of Technology, Electronics and Communication Engineering Aug 2017 - July 2021 Skills

Languages: Python, MATLAB, JAVA, SQL, C++, JavaScript Libraries/Frameworks: Pandas, Sklearn, Matplotlib, Seaborn, PyTorch, NumPy, SciPy, Scikit-learn, Tensorflow, Selenium, MONAI, NiLearn, spaCy, BeautifulSoup, Node.js, Express.js, LangChain, ChromaDB, Pinecone Tools: Eclipse, Jupyter Notebook, VSCode, JIRA, JAMA, ServiceNow, AWS (SageMaker, EC2, S3), Git, Docker, Intellij, Postman

Experience

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Lee Lab, Keck School of Medicine, USC (Research) Los Angeles, USA Natural Language Processing Researcher - Advisor: Prof. Dr. Hayoun Lee Jan 2025 - Present

Implemented a Medical Retrieval-Augmented Generation (RAG) MVP to analyze HIV guidelines and research, generating regimen recommendations for Physicians.

Developed a LangChain-based system to convert complex medical PDFs into structured text and integrated Chroma DB for retrieval.

Leveraged Qwen-2.5-7B for LLM and achieved accuracy of 85.7%.

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ViyaMD (Internship) Los Angeles, USA

Machine Learning Engineer May 2024-July 2024

Conducted a Virtual Product Reveiw (VPR) on multiple Data Ingestion platforms (Azure Data Explorer, Adobe Experience Platform Data Ingestion, PDFMiner, LangChain data loaders, etc.) for Medical RAG use-case.

Compared extracted PDFs from the VPR with ground-truth PDFs by designing a custom Data ingestion-evaluation pipeline.

Evaluated pipeline accuracy by measuring precision (92.3%), recall (89%), and F1(90.12%) scores to quantify extraction and conversion reliability.

Visualized the above performance analysis using CometML and found Adobe Experience Platform Data Ingestion to be the best.

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Biomedical Imaging Group, USC (Research) Los Angeles, USA Machine Learning Researcher - Advisor: Prof. Dr. Anand Joshi Jan 2024 - April 2024

Project1: Adapted DeepBet v1.0 tool with U-Net architecture for macaque MRI dataset achieving high precision ( 99%) for skull-stripping.

Project2: Trained a PyTorch+MONAI-based SwinUNETR pipeline on NVIDIA A100 GPU, reaching an 80% Dice score for macaque brains.

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Deloitte USI (Full Time) Mumbai, India

Software Engineer (Analyst) - State of North Dakota, Health and Human Services Sept 2021-Jun 2023

Created and implemented 150+ automation scripts using Keyword and Data-driven frameworks with Java, Selenium, TestNG, Jenkins, and Maven to test AngularJS based web application with 2026 web pages and performing backend validations with SQL.

Spearheaded the automation of the regression suite for SIT sign-offs and identifying 200+ defects and reducing manual effort by 60%.

Collaborated cross-functionally by managing project workflows with JIRA and JAMA, adhering to Agile methodologies and SDLC.

Recognized with a ’Spot Award’ for outstanding automation expertise and contributing to 3 major releases. Projects

• Code Detective: Fine-tuned GraphCodeBERT on NVIDIA A40 for detecting semantically similar Python snippets (F1: 0.96) (Dec’25)

• Transfer Learning for Image Classification: Built a multi-class classifier (ResNet50/101, EfficientNetB0, VGG16), achieving 91.21% F1 and 99.19% AUC with EfficientNetB0. (Dec’25)

• Laptop Price Prediction using Machine Learning Algorithms: Compared Linear Regression, Random Forest, Support Vector Regression, K-nearest neighbors, and Neural Networks, scoring R = 0.844 with Random Forest.(May’24)

• Computer Vision Super Resolution using SRGAN: Achieved 3x enhancement on DIV2K images with SRGAN

(Adversarial Loss: 0.0010, VGG Loss: 0.0014, Pixel Loss: 0.0625) (Dec’23) Publications

Raut, S., et al., “Real Estate Based Recommender System Using ML”, GIS Science Journal, 2022. [Paper]

Raut, S., Motade, S., “IOT Based Smart Irrigation System using Cisco Packet Tracer”, IJCSE, 2021. [Paper]

Raut, S., Naware, S., Tank, V., “Vehicle Cluster Development”, ICTCS, 2021. [Paper]

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