Together with my team, I support clients at every step of developing data-driven solutions. From designing strategy and planning data collection, to establishing data analytics pipelines and deriving actionable insights, our team works with any kind of data to help you start generating more value.

Analysing data to prevent financial crimes related to money laundering, sanctions, bribery and corruption.

Developing computer vision algorithms and infrastructure to monitor processes around aircrafts.

• Working on transmission, storage, processing, visualisation and analytics of data acquired using wearable devices in the context of monitoring personal safety and health.• Focusing on models and algorithms associated with body temperature, electrical activity of the heart and physical activity.

Developing the next generation wearables for precision health.

• Developing accurate and efficient algorithms to infer quantitative information from image data characterised by a low signal-to-noise ratio. • Focusing on image data acquired using fluorescence microscopy.Tutoring students in the lectures "Image analysis and computer vision" (Prof. Luc Van Gool and Prof. Gábor Székely) and in the sessions dedicated to image denoising during the EXCITE Summer School on Biomedical Imaging hold by ETH Zurich.Theoretical skills: physical-based models, Bayesian framework, hidden Markov models, Monte Carlo methods, variational image processing, convex optimisation.Practical skills: big data analytics, high performance computing, data base management, software engineering, a lot of coding in Python, some coding in R, Java and C++.

Exploring algorithms to segment yeast cells on image data acquired using differential interference contrast microscopy and fluorescence microscopy.

Applying computer vision to study the dynamics of protein expression in E. coli. My goal was to develop an algorithm to quantify the distribution of proteins inside living cells from fluorescence microscopy image data. For the first time I have been working on image deblurring and image segmentation. I was impressed how much quantitative information can be inferred from image data. This internship helped me to decide what I would like to do in the future.

Investigating mechanisms of cancer cell invasion in collagen networks. I have been using optical tweezers to measure the stiffness of collagen and Matlab to process and visualise data.

Studying how would the deployment of genetically engineered organisms affect the natural environment. Together with nine teammates we tackled the problem from technical, legal, ethical prospectives, suggested and implemented a proof-of-concept design for the containment system of synthetically engineered cells. Our team was among finalists and won the award for the best environment project at iGEM 2012.

Learning how to grow bacteria and manipulate with their genome. It was my first wet lab experience! I also constructed and programmed a turbidostat, a device that keeps cell cultures under constant conditions using two pumps controlled by Arduino.

Designing and studying acoustooptical matched filters.

Studying how to control optical waveguide couplers in photorefractive crystals using lasers.