Overall 5 years of experience in software development. Expertise in machine learning, Python, R, mobile development (iOS), natural language processing, deep learning, version management systems, unit tests and test automation, data visualization and analysis, Agile/Scrum. Fast learner, self-starter, adaptive, self-organized, open source contributor. I like to share knowledge.
- November 2016 - present.
- “Machine Learning with Swift: Artificial Intelligence for iOS”
- Technologies: Swift, Deep Learning, Machine Learning, Tensor Flow, Metal, Accelerate framefork, computer vision, NLP, Core ML, emotion recognition, motion types recognition.
Software Engineer, GlobalLogic, Lviv, Ukraine
- March 2016 - present.
- Several applications in the domain of intelligent mobile threat detection, secure messaging and VoIP. Research and implementation of POCs for network threat detectors.
- Man-in-the-middle attacks detection
- SSL pinning
- Database encryption
- Beakons communication
- End-to-end encryption
- Jailbreak detection
- Core Technologies: Swift, iOS, WebRTC, Cryptography, security, MongoDB
- January 2016 - March 2016
- Deep neural language model for grammar checking designed with functional programming principles in mind.
- Core Technologies: Torch7, Deep learning, LSTM, convolutional neural networks, Lua, functional programming, machine learning.
Software Developer, Gigaset Communications (Germany), R&D office at Wrocław, Poland
- April 2015 – October 2015
- Home automation platform: Gigaset Elements and Gigaset MobileDock. Developing mobile applications for Gigaset smart house platform. Integration with proprietary Bluetooth LE services and web-APIs.
iOS Software Engineer, Ciklum Interactive Solutions, Dnipro, Ukraine
February 2014 – April 2015
Healthcare application for Babylon Partners (London)
- Machine learning system prototyping (Python/R/OpenCV).
- Custom algorithm for heart rate detection via camera.
- Development of the system for user motion recognition. Our algorithm accuracy is over 80% with possibility to add custom motion types. iPhone’s default accuracy is ~ 55%.
- Data visualization with R.
- REST client and wearable devices integration. Research.
- Technical documentation development.
- Distributed international team of developers and medical specialists.
- Submitting to app store.
- Core technologies: Objective-C, Python, Java, TDD, Appium.
- Mobile application development. I took part in development of 10 apps, 5 of them is for medical or biotech companies. Other includes mobile media platform, social media, games and productivity apps.
- Core technologies: Objective-C, OS X, Git, SVN.
Teacher, Secondary school, Dnipro, 2010-2012
- Biology and chemistry teacher in 5 – 10 grades.
- Skills gained: pedagogy, psychology, public speaking, scientific demonstrations.
Engineer, Dnipropetrovsk National University, Research Institute of Biology, Dnipro, April 2010 – June 2010
- Data analysis. Skills gained: MS Excel, MS Access.
- Subjects: water quality monitoring, bacteriological water analysis.
Junior Laboratory Assistant, Dnipropetrovsk National University, Department of Biology, Aquarium, Dnipro, October 2008 – January 2009
- Caring for aquatic organisms.
- Skills gained: positive mood, self motivation, proactivity, fishkeeping, crocodile keeping.
Master of Science, Biology, Dnipropetrovsk National University, 2009-2010
- Thesis title “Seasonal dynamics of some hydrochemical characteristics of Zaporozhye water reservoir”.
- With distinction. GPA: A.
Bachelor of Science, Biology, Dnipropetrovsk National University, 2005-2009
- Core: R, Python, MongoDB, Apache Spark, MapReduce, time series, statistics.
- Data wrangling: Pandas, NumPy, dplyr.
- Machine learning: scikit-learn, e1071, caret, Core ML.
- Deep Learnign: Caffe, Keras, TensorFlow, Torch7, convolutional neural networks, recurrent neural networks.
- NLP: Topic modelling, sentiment analysis, NLTK, Gensym, tm package(text mining), NSLinguisticTagger, embeddings, language modelling, etc.
- Digital signal processing: computer vision, face detection in video, physical activity recognition, …
- Data visualization: matplotlib, Seaborn, Bokeh, D3.js, ggplot2, RcolorBrewer, igraph, ggmap, graphviz, etc.
- Bioinformatics: PAUP, PHYLIP, MrBayes, PyMOL, UGENE, MEGA5/6, Cytoscape, Bioconductor, BLAST, HMMER, ClustalW, MUSCLE, Bowtie, Prosite, Ensembl genome browser, KEGG Pathway, MEME, MG-RAST, FASTA, FASTAQ, SAM, BAM, PDB, NEXUS …
- Technologies: Bluetooth LE, CoreBluetooth, Kanban, HockeyApp, ReactiveCocoa, Swift
Mobile health system.
“This is a virtual health service in your pocket. With an easy appointment and records system, leading clinicians and state of the art personal health monitoring capabilities, babylon is simply your own virtual health service in your pocket. It is the first organization of its kind to be registered with Care Quality Commission (CQC) and have designated body status from NHS England.”
- Core iOS application development.
- RESTful service integration.
- Research and development of custom motion activity recognition algorithms.
- Unit tests
- Documentation development
- Technologies: Core Plot, HealthKit, Validic, CoreLocation, CoreMotion, CoreGraphics, CoreData, APNS, AFNetworking, HTTPS, Autolayouts, XCTest, Kiwi, REST, TestFlight, Crashalitics, Jira, Jenkins, GitHub, CocoaPods, R, Python, OpenCV, Machine learning.
Football Coach Simulator Mobile Game
- Technologies: UIKit, Foundation, REST.
Mobile eStore Engine
Customizable engine for fast creation of internet store applications.
- Technologies: UIKit, Foundation, REST, MediaPlayer Framework, StoreKit, Flurry.
Mobile Resume App
Create your resume on the go.
- New UI design and iPad version implementing.
- Dropbox integration.
- iCloud synchronization integration.
- LinkedIn API integration.
- Technologies: iCloud, Dropbox SDK, LinkedIn API, CoreData, UIKit.
Taxi Booking Application
- Optical recognition of credit card numbers integration
- UI implementation.
- Technologies: card.io SDK, UIKit.
Diabetes Management Application
- Custom controls and calculators for diabetes management implementation.
- Technologies: RestKit, UIKit
Medical Devices Promo App
Internal iPad app for medical staff.
- Technologies: Google Analitics, UrbanAirsip, TestFlight SDK, Perl and Python scripting, SQLite.
Laser Eye Surgery Promo App
Internal iPad app for medical staff training and promotion:
- Laser eye surgery simulations implementation.
- Custom UI implementation.
- Technologies: UIKit.
Internal app for biotech corporation.
- Offline google-like maps implementation.
- Video player integration.
- Technologies: UIKit.
- Machine learning winter school 2017 at UCU, Computer Vision track.
- Data science summer school 2016 at UCU.
- Introduction to Data Science by University of Washington
- Computing for Data Analysis (R programming) by Johns Hopkins University
- Data Analysis and Statistical Inference by Duke University
- Analitics Edge by MIT
- CS190.1x Scalable Machine Learning by BerkeleyX
- CS100.1x: Introduction to Big Data with Apache Spark by BerkeleyX
- MongoDB for Developers by MongoDB Inc.
- Programming in Objective-C by National Open University Intuit
- FP101x: Introduction to Functional Programming by Delft University of Technology through edX
- Epigenetic Control of Gene Expression by University of Melbourne
- Bioinformatics: Life Sciences on Your Computer by Johns Hopkins University
- Bioinformatics: Introduction and Methods by Peking University
- Bioinformatic Methods I by University of Toronto
- Bioinformatic Methods II by University of Toronto
- Computational Molecular Evolution by Technical University of Denmark
- Programmed cell death by Ludwig-Maximilians-Universität München (LMU)
- Writing in the Sciences by Stanford Online