Aleksandar Milchevski
Verified Expert in Engineering
Machine Learning Developer
Skopje, Macedonia
Toptal member since October 30, 2019
Aleksandar has more than ten years of combined research and development experience working with data, machine learning, computer vision, and signal/image processing. He enjoys working remotely and solving complex problems. He prides himself on being able to write clean, readable code.
Portfolio
Experience
Availability
Preferred Environment
Amazon Web Services (AWS), Google Cloud, Python, Linux
The most amazing...
...thing I have worked on is a DNA sequencing software.
Work Experience
Machine Learning Engineer
Collab (Toptal Client)
- Led the research and development of an API that does video processing.
- Extracted valuable information from videos using AWS.
- Used Ruby on Rails for the back-end side of the app.
Machine Learning Engineer
Miracle Mill, GmbH
- 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 Engineer
Leybold (via Toptal)
- 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 Scientist
Nucleics
- 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 Engineer
Sentice Tech
- Worked on anomaly detection in images.
- Used OpenCV.
Signal Processing Consultant
ECGalert
- 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 Scientist
NAGI
- 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 Assistant
Faculty of Electrical Engineering and Information Technologies
- 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 Researcher
Dip team
- 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.
Experience
Multimodal Affective Analysis Combining Regularized Linear Regression and Boosted Regression Trees
Improved Pipelined Wavelet Implementation for Filtering Ecg Signals
Machine Learning Based Super-Resolution Algorithm Robust to Registration Errors
https://ieeexplore.ieee.org/abstract/document/5739234Generic Face Detection and Pose Estimation Algorithm Suitable for the Face De-identification Problem
Education
Progress towards a Ph.D. in Machine Learning
Faculty of Electrical Engineering and Information Technologies - Skopje, Macedonia
Master's Degree in Signal Processing
Faculty of Electrical Engineering and Information Technologies - Skopje, Macedonia
Bachelor's Degree in Electronics and Signal Processing
Faculty of Electrical Engineering and Information Technologies - Skopje, Macedonia
Certifications
AWS Certified Data Analytics - Speciality (prev. Big Data)
AWS
AWS Machine Learning - Speciality
AWS
Google Cloud Certified Professional Data Engineer
Google Cloud
Data Engineering, Big data and Machine Learning on Google Cloud Platform
Coursera (GCP)
Machine Learning with TensorFlow on Google Cloud Platform
Coursera (GCP)
Deep Learning
Coursera (deeplearning.ai)
Skills
Libraries/APIs
TensorFlow, Keras, Amazon Rekognition, OpenCV
Tools
MATLAB, AWS Glue, Amazon Kinesis Data Firehose, Amazon SageMaker
Languages
C++, C, Python, R
Storage
Google Cloud Development
Frameworks
Spark
Platforms
Linux, AWS
Industry Expertise
Bioinformatics
Other
Machine Learning, Data Science, Digital Signal Processing, Big Data Architecture, Deep Learning, Audio Single Proccessing, DNA Sequencing, Computer Vision, Emotion Recognition, Signal Processing, Electronics, Audio Processing
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