About

Senior AI Engineer
I'm Sreenath Kyathanahally, a Senior AI Engineer with expertise in deep learning and computer vision. I hold a Ph.D. in Biomedical Engineering from the University of Bern and have worked on diverse projects, including medical image analysis. My passion lies in solving real-world challenges using AI techniques. Currently, I'm at b-rayZ, assembling complex medical datasets and designing AI algorithms for image segmentation and classification. I enjoy staying at the forefront of AI research and have a strong track record of publications in top conferences and journals. Let's innovate and make a positive impact with AI!
Skills
- Deep Learning: TensorFlow, PyTorch, Keras
- Computer Vision: OpenCV, Vision Transformer
- Web Development: Flask
- Machine Learning: Scikit-learn, CNN, Transformer, Unet
- Data Manipulation and Analysis: NumPy, Pandas
- Cloud Platforms: Amazon AWS, Microsoft Azure
- Database Management: SQL, MongoDB
- Programming Languages: Python, MATLAB
- Model Tracking: Weights and Biases
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Version Control: Git
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Containerization: Docker
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Medical Imaging: MRI, CT, PET
Experience

Senior AI Engineer
Zurich, SwitzerlandJune 2023 - Present
- Assemble large, complex medical datasets for AI models.
- Implement process improvements for automation and scalability.
- Build infrastructure for data extraction and loading using Mongo, SQL, and Cloud.
- Develop AI algorithms for medical image segmentation and classification using TensorFlow and PyTorch.
- Implement YOLO-v8 based object detection and segmentation for medical images.
- Conduct data exploration and analysis to derive insights for model development.
- Maintain pipelines for continuous integration and deployment.
- Ensure compliance with medical device standards.

Senior Deep Learning Engineer
Zurich, SwitzerlandFeb 2022 - May 2023
- Develop deep learning algorithms for medical imaging.
- Utilize heart atlas based training for cardiac image segmentation.
- Annotate and segment CT images to improve AI model accuracy.
- Adhere to Quality Management System (QMS) requirements.
- Support cloud-based AI algorithms for real-time analysis.
- Foster collaboration and knowledge sharing within the team.

Machine Learning Researcher - Scientist FS8
Zurich, SwitzerlandSep 2020 - Present
- Develop deployable deep learning algorithms, including GANs, for plankton classification.
- Use transfer learning and data augmentation techniques, characterizing noise, to improve model generalization.
- Collaborate with domain experts to understand and address ecological implications of plankton classifications.
- Implement vision transformers for efficient and scalable image processing.
- Publish research findings in top-tier machine learning and ecology venues.

Computer Vision Scientist
Zurich, SwitzerlandDec 2019 - Aug 2020
- Developed state-of-the-art machine learning algorithms for computer vision problems, such as classifying Soybeans and Corn based on certain features.
- Maintained modular, scalable, and sustainable code following Scrum Agile methodologies.
Postdoctoral Researcher
Zurich, SwitzerlandNov 2017 - Nov 2019
- Develop deep learning algorithms for segmenting spinal cord lesions using medical images.
- Investigated neuro-imaging biomarkers responsible for pain in spinal cord injury patients.
- Conducted longitudinal studies to analyze structural and microstructural changes in the brain of spinal cord injury patients.
- Predicted clinical outcomes of spinal cord injury patients based on tissue bridges using deep learning algorithms.

Research Scholar
Montreal, CanadaAug 2018 - Sept 2018
- Implement a machine learning pipeline for automatic lesion segmentation in spinal cord images using Python and TensorFlow.
- Utilize transfer learning techniques to improve the performance of lesion segmentation models on limited annotated data.

Early Stage Researcher - Marie-Curie ITN
University of Bern, SwitzerlandSept 2013 - Aug 2017
- Develop machine learning tools and classifiers to analyze brain tumor spectra and assist radiologists in interpreting data.
- Implement deep learning networks, including CNNs and autoencoders, to remove artifacts and improve the quality of MR spectra.
- Research and develop methodologies to predict and assess the quality of clinical MR spectra data.
- Develop a JAVA plugin for the jMRUI tool, enhancing its functionality and usability for medical image analysis.

Early Stage Researcher Secondment
Barcelona, SpainDec 2014 - Feb 2015
- Acquire and apply basic machine learning skills to classify brain tumor spectra using RUSBOOST, SVM, and Random Forest algorithms.

Graduate Research Assistant
Auburn, AL, USASept 2011 - Aug 2013
- Apply signal processing techniques (denoising, ICA, PCA) to remove noise and motion artifacts from fMRI and EEG data.
- Integrate fMRI and EEG data to enhance spatial and temporal resolution for more precise brain activity analysis.
- Conduct statistical analysis and generate visualizations for research papers and conference presentations.

Bachelors Thesis: Real-Time Industrial Production Counter
Bangalore, IndiaJanuary 2011 - June 2011
- Develop an improved counter using Arduino microcontroller board for efficient assembly line production monitoring.
- Design and implement control algorithms to synchronize the counter with the assembly line system.

Internship
Bangalore, IndiaJuly 2010 - Oct 2010
- Design an LCD Timer handheld device using PIC microcontroller assembly language programming.
- Develop firmware for the device to accurately measure and display time.
Education

Doctor of Philosophy: Biomedical Sciences/Engineering
University of Bern
Thesis: Quality Aspects of Clinical Magnetic Resonance Spectroscopy: Quantification Issues, Quality Prediction, and Quality Assessment by Machine Learning

Master of Science: Electrical and Computer Engineering
Auburn University
Thesis: Blind Source Separation Methods for Analysis and Fusion of Multimodal Brain Imaging Data

Bachelor of Engineering: Electronics and Communication Engineering
Visvesvaraya Technological University
Thesis: Real-Time Industrial Production Counter using Arduino Microcontroller
Awards & Honors
IRP Research grant, Zurich, Switzerland
Co-applicant, 150k CHF, 2020-23
Magnetic Resonance in Medicine journal
Top downloaded author, 2018-19
Ecole Polytechnic, Montréal, Canada
Research travel grant, 4k CHF, 2018
ISMRM
Educational stipend award, 2013, 2014, 2015
ISMRM
Magna Cum Laude merit award, 2014-2015
ISMRM
Summa Cum Laude merit award, 2013
Auburn University, USA
Graduate Assistantship Award, ~45k USD, 2011-13
Auburn University, USA
Graduate Fellowship Award, ~20k USD, 2011-13
University of Bern, Switzerland
2nd prize in SLAM competition, 2016
Contact
sreenath.kyathanahally@gmail.com
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