Activity
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We are excited to announce pal: ergonomic LLM assistants designed to help you complete repetitive, hard-to-automate tasks quickly in RStudio or…
We are excited to announce pal: ergonomic LLM assistants designed to help you complete repetitive, hard-to-automate tasks quickly in RStudio or…
Liked by Gabriel Burcea
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Înțeleg că dl Călin Georgescu este agent rus (nu știu, nu neg, nu afirm). Ce ma intrigă este cum de șeful SRI nu și-a dat demisia având în vedere că…
Înțeleg că dl Călin Georgescu este agent rus (nu știu, nu neg, nu afirm). Ce ma intrigă este cum de șeful SRI nu și-a dat demisia având în vedere că…
Liked by Gabriel Burcea
Experience
Education
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Coursera
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Theoretical and practical exercises in Machine Learning and Big Data
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I have gained skills such as Machine Learning & Statistical Data Mining, Big Data Applications, Data Science Research Topics, Data Programming, Data Visualisation, Natural Language Processing, and Geometric Data Analysis by undertaking an MSc Course in Data Science.
In particular, I have developed my knowledge by performing practical and research work in a variety of real-world Data Science applications based on the newest software and hardware technologies (Spark, Hadoop ecosystem, R…I have gained skills such as Machine Learning & Statistical Data Mining, Big Data Applications, Data Science Research Topics, Data Programming, Data Visualisation, Natural Language Processing, and Geometric Data Analysis by undertaking an MSc Course in Data Science.
In particular, I have developed my knowledge by performing practical and research work in a variety of real-world Data Science applications based on the newest software and hardware technologies (Spark, Hadoop ecosystem, R, Python, SQL, running on a cluster of 10 resourceful servers which form the Big Data Management and Analytics resource dedicated to the Data Science MSc programme and research). Moreover, I have made part of a research team that was attached to Kings College and Institute of Psychiatry in predicting the time of remission in psychotic patients using Machine Learning techniques.
The grades l obtained in the MSc studies are good and very good. -
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Statistics module (MSD I and MSD II) represented 50 % of the courses.
Statistical analyses: descriptive analysis such as t-test, data manipulation, correlations, logistic regression, multilevel regression analysis and hypothesis testing; knowledge of data management and data manipulation. The projects entailed analysis of health datasets in UK as well as European ones on internet youth bullying
Licenses & Certifications
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Learning Python Programming Masterclass
Udemy
IssuedCredential ID UC-2249bf8b-176f-416a-a7c5-a3dcb6553f8a -
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Volunteer Experience
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Intern and Researcher
Livada Oprhan Care
- 6 years 3 months
Civil Rights and Social Action
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Data Scientis Volunteer
DataKind
- 1 month
Poverty Alleviation
I, with a team of data scientist, have been analyzing two data sets provided by Christian Aid organizations. The purpose of the project entailed in rethinking and giving insights on the resilience Index developed by Christian Aid. From cleaning the data to data visualization and application of Random Forest Christian Aid was able to spot challenges, improvements they may take into account in data collection, rethinking the questions and redefining the resilience index the organization worked…
I, with a team of data scientist, have been analyzing two data sets provided by Christian Aid organizations. The purpose of the project entailed in rethinking and giving insights on the resilience Index developed by Christian Aid. From cleaning the data to data visualization and application of Random Forest Christian Aid was able to spot challenges, improvements they may take into account in data collection, rethinking the questions and redefining the resilience index the organization worked with over the last 2 years.
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Participant
Open Data Science Conference (ODSC)
- 1 month
Participated in different kind of workshops related to Data Visualisation, Natural Language Processing, Machine Learning, Big Data.
R, Python, SparkR, TensorFlow were few of the software/environments used in this workshops.
Publications
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Variation in global COVID-19 symptoms by geography and by chronic disease: A global survey using the COVID-19 Symptom Mapper
The Lancet/eClinicalMedicine
Summary
Background
COVID-19 is typically characterised by a triad of symptoms: cough, fever and loss of taste and smell, however, this varies globally. This study examines variations in COVID-19 symptom profiles based on underlying chronic disease and geographical location.
Methods
Using a global online symptom survey of 78,299 responders in 190 countries between 09/04/2020 and 22/09/2020, we conducted an exploratory study to examine symptom profiles associated with a…Summary
Background
COVID-19 is typically characterised by a triad of symptoms: cough, fever and loss of taste and smell, however, this varies globally. This study examines variations in COVID-19 symptom profiles based on underlying chronic disease and geographical location.
Methods
Using a global online symptom survey of 78,299 responders in 190 countries between 09/04/2020 and 22/09/2020, we conducted an exploratory study to examine symptom profiles associated with a positive COVID-19 test result by country and underlying chronic disease (single, co- or multi-morbidities) using statistical and machine learning methods.
Findings
From the results of 7980 COVID-19 tested positive responders, we find that symptom patterns differ by country. For example, India reported a lower proportion of headache (22.8% vs 47.8%, p<1e-13) and itchy eyes (7.3% vs. 16.5%, p=2e-8) than other countries. As with geographic location, we find people differed in their reported symptoms if they suffered from specific chronic diseases. For example, COVID-19 positive responders with asthma (25.3% vs. 13.7%, p=7e-6) were more likely to report shortness of breath compared to those with no underlying chronic disease.
Interpretation
We have identified variation in COVID-19 symptom profiles depending on geographic location and underlying chronic disease. Failure to reflect this symptom variation in public health messaging may contribute to asymptomatic COVID-19 spread and put patients with chronic diseases at a greater risk of infection. Future work should focus on symptom profile variation in the emerging variants of the SARS-CoV-2 virus. This is crucial to speed up clinical diagnosis, predict prognostic outcomes and target treatment.
Languages
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English
Full professional proficiency
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