Machine Learning Engineer2019 - 2021Miracle Mill, GmbH
Technologies: Amazon Web Services (AWS), AWS FireHose, AWS Glue, Amazon SageMaker, Machine Learning, AWS, Python
- Contributed to several projects using AWS (Glue, SageMaker, DynamoDB, and Lambda) and ETL using Apache Spark.
- Led the choice, training, and validation of the machine learning models.
- Placed the algorithms into production.
Audio Signal Processing Engineer2020 - 2020Leybold (via Toptal)
Technologies: Machine Learning, Audio Single Proccessing, Digital Signal Processing, Python
- Analyzed, processed, and classified sound recordings.
- Used discrete Fourier transform (DFT) and other signal processing techniques.
- Used logistic regression and other machine learning techniques.
Data Scientist2016 - 2019Nucleics
Technologies: DNA Sequencing, Bioinformatics, Machine Learning, Keras, Python, R, C, C++
- Contributed to improving and developing production-ready software in C/C++.
- Researched cutting edge ideas in the field of genomics and DNA sequencing.
- Implemented and tested several complex ideas, including the training and testing of deep convolutional neural networks.
Computer Vision Engineer2016 - 2017Sentice Tech
- Worked on anomaly detection in images.
- Used OpenCV.
Signal Processing Consultant2016 - 2016ECGalert
Technologies: Digital Signal Processing, C++
- Implemented the electrocardiogram (ECG) signal processing and denoising.
- Implemented a pipelined discrete wavelet transform (DWT).
- Researched the use of several FIR and IIR filters for the ECG denoting.
Machine Learning Research Scientist2014 - 2016NAGI
Technologies: Emotion Recognition, Machine Learning, MATLAB, Spark, C++, Python
- Worked on research and development of a state-of-the-art emotion recognition algorithm.
- Took part in the Fifth International Audio/Visual Emotion Challenge and Workshop.
- Led the development of a people tracking solution through wifi. Implemented the model using Apache Spark.
Junior Teaching and Research Assistant2010 - 2014Faculty of Electrical Engineering and Information Technologies
Technologies: Digital Signal Processing, Computer Vision, Machine Learning, MATLAB, C
- Held auditory and laboratory exercises for several courses from the fields of digital signal processing.
- Worked on power quality assessment. Used machine learning techniques to detect and classify the disturbances.
- Took active participation in the research project "Algorithms for time-varying harmonic analysis for power quality assessment applicable on modern digital signal processors, ERA.NET PLUS project."
- Utilized OpenCV to implement face detection using SVM.
Junior Researcher2009 - 2011Dip team
Technologies: Digital Signal Processing, Machine Learning, C, MATLAB
- Worked on the detection and quantification of the intensity of ringing artifacts in JPEG coded images.
- Developed a robust multi-frame super-resolution algorithm.
- Got introduced to the fundamental ideas of machine learning and solving inverse problems.