Sreenidhi Iyengar Munimadugu Email & Phone Number

Mountain View, CA, US

Marina Del Rey, California, United States

• Conducting research at ISI AI4Health Lab with Prof. Michael Pazzani, Prof. Carl Kesselman, Prof. Rostami, Dr. Benjamin Yixing Xu, and Dr. Van Nguyen, resulting in the development of advanced deep learning systems for.
• Devise image segmentation and localize scleral spur on AS-OCT open-angle images. Adopting a specific modeling approach to accomplish high levels of Intraclass Correlation Coefficient (ICC) of 0.99 between model.
• Execute AWS data extraction, ingestion, and cleaning processes utilizing the Deriva Research Framework and BDBag. Includes implementing two-factor authentication and constructing pipelines for pre-processing using.
• Developed EYE-AI.org hosted on AWS, designed database schemas on Lucidchart, and, with a team of 3, wrote code to automate incoming data stream into structured and citeable data tables on the EYE-AI website

Los Angeles, California, United States

• Collaborating with LA General and Roski Eye Institute to deploy AI-driven multimodal algorithms on screening sites, decreasing patient screening time from 3 months to 6 weeks, preserving eyesight, and ensuring data.
• Integrated high-resolution DICOM patient scan data of 6 years from 7 Roski Eye Institute and LA General County hospital servers. Streamlined data cleaning and augmentation for enhanced reliability, eliminating manual.
• Led a data extraction team to engineer OCR pipelines for ZEISS Humphrey Field Analyzer 3 (HVF), Optical Coherence Tomography (CIRRUS 5000/4000 - RNFL and GCC), ZEISS CLARUS 500, OphthaVision, and Nikon Optos (Fundus.
• Implemented advanced algorithms (vision transformers, fine-tuned EfficientNetV2M) utilizing vision and text data to predict glaucoma severity (5-scale) and laterality and scan quality (1-100 scale) in real-time.
• Evaluated model using ROC and AUC metrics against ground truths generated by ten graders of varying expertise levels (novice, intermediate, students, professionals, clinical experts) based on the Glaucoma 2023.

Hyderabad, Telangana, India

• Production Forecast of Surface Miner Technology: Directed comprehensive data analysis and improved coal production forecasts with ARIMA, ARIMAX, and Holt-Winter models, optimizing accuracy (RMSE, MAPE). Leveraged.
• Cross-Selling Insurance Products using Predictive Analytics: Led customer scoring with Random Forest and XGBoost models, increasing business alignment, boosting performance with a 15% increase in conversion rates.
• Customer Feedback Analytics: Spearheaded analyzing customer chat transcripts in the telecom domain, applying advanced NLP techniques for data cleaning and topic modeling, and employing various visualization techniques.
• Oversaw SVM machine learning model development and hyperparameter tuning for Telugu language detection

Raurkela, Orissa, India

• Achieved implementing and hosting the eWarn voice recognition system on Heroku within a team of three. Streamlined employee authentication and slashed login times by 1.5 times compared to the previous system.
• Designed a desktop GUI applying PYQt, Python, and MySQL for model retraining and fine-tuning, simplifying voice data record management. Conducted testing, debugging, and implemented logging for efficient backend code.

Hyderabad, Telangana, India

• Enhanced image and text classification accuracy by 4% by fine-tuning advanced GAN architectures (DCGAN, WGAN, WPGAN, CTGAN) for optimal synthetic data generation, emphasizing secure augmentation of confidential and.
• Collaborated with the NLP team in establishing a deep learning pipeline for transcribing Hindi voice calls into text, translating Hindi to English, and analyzing sensitive COVID-19 healthcare data from over 600,000.
• Engineered TCScovihealth, a Python module automating sentiment analysis report generation and storage, improving healthcare service efficiency by 11% and reducing transcription errors by 50%

Hyderabad Area, India

• Fine-tuned Faster R-CNN-based deep learning framework for semantic segmentation, object recognition, and extraction, achieving a 97.64% accuracy in human object extraction, a 7.9% improvement over the existing framework
• Created a custom object detection API leveraging RESTful web services for seamless integration with client applications, resulting in a 16% increase in project adoption rates

Hyderabad Area, India

• Media Sentiment Analysis for CinYstore: Formulated and advocated strategic hashtag and keyword strategies for TV shows andmovies, elevating information reach by 25%. Utilized Python, Tweepy, and NLP to extract and.
• Shifted the Facial Recognition System Pipeline to a MongoDB database and optimized the image preprocessing pipeline withmultithreading, leading to an 18% increase in operational efficiency for client Outshade
• Worked with libraries such as sklearn, pycaret, and Keras for Machine Learning model development.

Master Of Science - Ms, Computer Science, 4.0

Btech - Bachelor Of Technology, Computer Science, 8.97