A newly founded MIT startup aiming to transform the healthcare industry and make it more accessible to everyone

As a Research Assistant to Prof. Dimitris Bertsimas:• Developed various interpretable machine learning models for healthcare applications for one of the largest hospitals in New England• Supervised 2 undergraduate students during their summer research projects at MIT• Presented key findings and recommendations to the Hospital’s Director of Analytics and Clinical Research CoordinatorHired as a Data Scientist to a newly founded MIT startup - Holistic Hospital Optimization - created by Prof. Dimitris Bertsimas and the hospital

• Formulated and implemented a robust mixed-integer optimization model in Python improving scheduling and resource allocation in Pfizer's quality control labs, achieved $1.6M in cost savings and reduced total testing time by 35%• Enabled streamlined adoption of optimization model by developing an intuitive GUI that helps lab managers generate test plans in PDF format and reduce test plan creation time by 6xResults presented during:• MIT CISR Annual Research Forum 2023• MIT Analytics Capstone Showcase 2023Winning award:• TOP 10 capstone thesis of the year at MIT

As a member of Machine Learning Engineering group working for one of the biggest retail companies in the world:• Designed and implemented ETL pipelines in Microsoft Azure using Python, PySpark, SQL, Databricks and Azure Data Factory

Thesis: “Deep learning-based sentiment analysis”Supervisor: Prof. Maciej Niedźwiecki (Gdańsk University of Technology)Consultant: Agnieszka Mikołajczyk, PhD (VoiceLab.AI)Results presented during:• IEEE Engineer 4 Science 2022 Gala in the Intel Poland headquarters to the CTO of Intel• ML in PL Conference (the biggest machine learning research conference in Poland)• MLGdańsk Meeting #122 (regional machine learning community)Winning awards:• TOP 3 bachelor's thesis in Poland (IEEE Engineer 4 Science 2022)• Best bachelor's thesis at the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology (IEEE Engineer 4 Science 2022)

As a member of Natural Language Processing group, I worked on:• Sentiment analysis• Topic modeling• Explainable AI (XAI)

• Conducted statistical learning research using R in the international research group led by Prof. Luis M. Correia (University of Lisbon) in the field of path loss estimation in Wireless Body Area NetworksPublished research results:- M. Laskowski, S. J. Ambroziak, L. M. Correia and K. Świder, "On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks," in IEEE Access, vol. 8, pp. 176873-176882, 2020, doi: 10.1109/ACCESS.2020.3025118. - M. Laskowski, S. J. Ambroziak, L. M. Correia and K. Świder, "Performance Evaluation of GAM in Off-Body Path Loss Modelling for Body Area Networks," 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Helsinki, Finland, 2021, pp. 922-927, doi: 10.1109/PIMRC50174.2021.9569725.

• Supported consulting team in the area of data analysis of worldwide online banking market• Took part in a series of workshops conducted by Bain Consultants on M&A and consulting frameworks

As a Summer Intern in Data & Analytics Department:• Optimized a process of partitioning data for Azure Analysis Services (7% time reduction)• Implemented automation tests comparing two different environments in Microsoft Azure (80% time reduction)• Created alerts notification system for Power BI reports informing business managers about rapid fluctuations in the FMCG market