Sunil Kumar
Verified Expert in Engineering
Senior Data Scientist and Developer
Zürich, Switzerland
Toptal member since December 20, 2021
Sunil's expertise lies in developing novel statistical and mathematical models for quantitative and qualitative data assessment. His primary strengths are ML, AI, big data, systems biology, and high-performance computing. He has co-authored 5+ papers in sleep science and helped develop solutions for wireless data transfer, DB management, and monitoring software lifecycle processes. Sunil is adept in overseeing research to ensure rapid development and deployment of innovative product lines.
Portfolio
Experience
Availability
Preferred Environment
MacOS, Unix, Python 3, Teams, Slack, Amazon Web Services (AWS), Azure
The most amazing...
...statistical tools I've built use advanced machine learning for sleep disorder assessment.
Work Experience
Senior Data Scientist
Sleepiz AG
- Co-authored 5+ conference papers and posters in the area of sleep science.
- Demonstrated the importance of cardiorespiratory features in terms of sleep staging and sleep disorder diagnosis.
- Obtained ethics approval from the Swiss Association of Research Ethics Committees (Swissethics) on sleep research.
Doctoral Student, Contractor
IBM Research
- Developed inference algorithms for protein networks using cytometry data.
- Created inference algorithms for protein networks using mass spectrometry data.
- Built probabilistic graphical models using moment dynamics.
Research Manager
IMRB International, Kantar
- Developed a market simulation application using Visual Basic Applications (VBA).
- Created a user segmentation model using their consumer product's uses and behavior.
- Gained corporate-level presentation skills and project management.
Experience
AI-based Sleep Disorder Assessment
http://www.sleepiz.comStabilized Reconstruction of Signaling Networks from Single-cell Cue-response Data
Inferring Gene Expression Networks with Hubs Using Degree-weighted Lasso Approach
https://academic.oup.com/bioinformatics/article/35/6/987/5085370Hybrid Approach for Improved Content-based Image Retrieval Using Segmentation
https://arxiv.org/abs/1502.03215To bridge the semantic gap that exists between the representation of an image by low-level features, namely color, shape, texture, and its high-level semantic content as perceived by humans, CBIR systems typically make use of the relevance feedback (RF) mechanism. RF iteratively incorporates user-given inputs regarding the relevance of retrieved images to improve retrieval efficiency.
In this work, an attempt has been made to improve retrieval accuracy by enhancing a CBIR system based on color features alone, through implicit incorporation of shape information obtained through prior segmentation of the images. Novel schemes for feature reweighting and initialization of the relevant set for improved relevance feedback, have also been proposed for boosting the performance of RF-based CBIR. At the same time, new measures for evaluating retrieval accuracy have been suggested to overcome the limitations of existing measures in the RF context.
Feature Selection for Sleep Staging Using Cardiorespiratory and Movement Signals
https://openres.ersjournals.com/content/5/suppl_3/P40Education
Ph.D. in Biomedical Science
Swiss Federal Institute of Technology (ETH) - Zurich, Switzerland
Master's Degree in Statistics
Indian Statistical Institute - Kolkata, India
Bachelor's Degree in Statistics
Indian Statistical Institute - Kolkata, India
Certifications
Information Security and Management Refresher
National Institutes of Health (NIH)
Software Lifecycle (EN 62304) Training
Medidee Services SA
Active Medical Devices–Standard Requirements Training
Medidee Services SA
Skills
Libraries/APIs
NumPy, Pandas, PyTorch, Keras, TensorFlow, PyQt, SciPy, Scikit-Learn
Tools
Slack Development, Plotly, Azure Machine Learning, MATLAB, Git, IBM SPSS Statistics
Languages
Python, SQL, Python, Visual Basic, Excel VBA, R
Platforms
Docker, Data Science, Linux, MacOS, Unix, AWS, Azure Design
Storage
Data Integration, Cassandra
Other
Teams, Statistics, Machine Learning, English, Data Science, Data Science, Deep Learning, Time Series Analysis, Machine Learning Operations (MLOps), Dash, Cloud Computing, Project Design & Management, Mathematics, Cell Biology, Signal Processing, Team Management, Offshore Development, Artificial Intelligence, Stochastic Modeling, Probability Theory, Data Science, Multivariate Statistical Modeling, Optimization, Bayesian Statistics, Statistical Modeling, Causal Inference, Bayesian Inference & Modeling, Data Science, Software Development Lifecycle (SDLC), Medical Devices, Information Security analysis, Privacy, Data Privacy, Records Management, Pattern Recognition, Random Forests, Hyperparameters, Linear Algebra, Numerical Analysis, Physics, Hypothesis Testing, Discrete Multivariate Modeling
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