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Yadunandan Vivekanand Kini
Munich, Germany
I'm a curious problem solver highly passionate about medical image analysis and deep learning. I've worked on many challenging machine learning and deep learning projects in the areas of image classification, image generation, and language translation. My intention is to make medical imaging technology more accurate and aid in the correct diagnosis of diseases.
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
29.7
CodersRank Rank
Top 7%
Top 100
Jupyter Notebook
Developer
Germany
Highest experience points: 0 points,
0 activities in the last year
Jupyter Notebook
4.3
exp.
HTML
9.7
exp.
Python
15.7
exp.
List your work history, including any contracts or internships
Technical University of Munich
Jul 2020 - Mar 2021 (8 months)
Student Research Assistant (Carl Zeiss Meditec AG)
Deep Learning for medical applications
The Hi-Tech Robotic Systemz Ltd
Mar 2018 - Jun 2019 (1 year 3 months)
Research Engineer
-Worked on state of the art deep learning techniques and computer vision algorithms for self driving robots.
-Conducted simulations of real world scenarios using Gazebo and RViz.
-Good working knowledge of ROS (Robot Operating System)
-CARLA simulator (open source simulator for autonomous driving research)
Technologies: Python, tensorflow, keras, numpy, scipy, ROS, OpenCV.
-Conducted simulations of real world scenarios using Gazebo and RViz.
-Good working knowledge of ROS (Robot Operating System)
-CARLA simulator (open source simulator for autonomous driving research)
Technologies: Python, tensorflow, keras, numpy, scipy, ROS, OpenCV.
Aricent
Jan 2016 - Mar 2018 (2 years 2 months)
Python Developer
-Implemented machine learning and natural language processing techniques to perform document clustering and text classification and substantially reduced manual human effort thereby reducing time to market of the product.
-applied machine learning approaches to reduce false negatives and false positives during vulnerability analysis.
-Implemented HTML/XML parsers for scraping data from websites.
-Attended Machine Learning training conducted by Tarah.ai which was taught by Dr. Srinivas Padmanabhuni (Ex-President ACM India).
-Technologies: scikit-learn, pandas, tensorflow, numpy, scipy, beautifulsoup.
-applied machine learning approaches to reduce false negatives and false positives during vulnerability analysis.
-Implemented HTML/XML parsers for scraping data from websites.
-Attended Machine Learning training conducted by Tarah.ai which was taught by Dr. Srinivas Padmanabhuni (Ex-President ACM India).
-Technologies: scikit-learn, pandas, tensorflow, numpy, scipy, beautifulsoup.
Add some compelling projects here to demonstrate your experience
Face Generation using Generative Adversarial Networks (GAN)
Dec 2017 - Dec 2017
Language Translation using Recurrent Neural Networks (English to French)
Dec 2017 - Dec 2017
Bike sharing ridership prediction using Neural Networks
Aug 2017 - Sep 2017
This section lets you add any degrees or diplomas you have earned.
Udacity
Deep Learning Foundations Nanodegree, Deep Learning
Dec 2016 - Dec 2016
Neural Networks
Convolutional Neural Networks (CNN)for image classification
Recurrent Neural Networks (RNN) for language translation
Generative Adversarial Networks (GAN) for image generation
Convolutional Neural Networks (CNN)for image classification
Recurrent Neural Networks (RNN) for language translation
Generative Adversarial Networks (GAN) for image generation
Technical University Munich
M.Sc., Biomedical Computing (Dept. of Computer Science)
Dec 2018 - Dec 2020
Ramaiah Institute Of Technology
Bachelor of Engineering (B.E.), Electronics and Communications Engineering
Dec 2010 - Dec 2014
Major Modules:
- Programming in C
- Data Structures
- Analog and Digital Communication
- MATLAB
- Digital Signal Processing
- Image Processing
- Linear Algebra
- Data Compression
- Computer Communication Networks
- Neural Networks and Fuzzy Logic
- Embedded Systems
- Optical Fiber Communication
- Programming in C
- Data Structures
- Analog and Digital Communication
- MATLAB
- Digital Signal Processing
- Image Processing
- Linear Algebra
- Data Compression
- Computer Communication Networks
- Neural Networks and Fuzzy Logic
- Embedded Systems
- Optical Fiber Communication