Machine learning techniques, statistical learning, Python, SQL,R

Farideh Tavazoee CV

T 617-***-**** B *.********@*****.***

Personal Information

Date of Birth: 19 September 1988 Gender: Female

Location: Boston Nationality: Iranian US Residency: Pending Green Card Work Experience

MindMics Harvard Innovation Labs, Boston, US

Intern Data Scientist 01/2019–03/2019

Health Data Analyzing and Visualizing, Extract Vital Signs, Apply Machine Learning for Heart Signal Processing

LIPN Lab, Université Paris 13 Paris, France

Research Assistant 09/2017–07/2018

Applying Machine Learning and Text Mining for Social Media Analysis University of Cagliari Cagliari, Italy

Research Assistant 10/2015–08/2017

Applying Machine Learning and Text Mining for Social Media Analysis Skills

Machine Learning, Data Mining, Develop predictive Models, Text Mining, Sentiment Anal- ysis, SQL, Health data analysis, Heart signal processing, Git, Docker Education

University of Cagliari Cagliari, Italy

Ph.D., Computer Science 10/2015–Present

Shahid Beheshti University Tehran, Iran

Master, Information Technology Management 09/2012–02/2014 None State Pasargad University Shiraz, Iran

Bachelor, Software Engineering 02/2007–09/2011

Computer Languages

Current: Python, R, LATE

X

Languages

Persian/Farsi: Mothertongue

English: Advanced

Italian: Intermediate

Publications & Presentations

2019:

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1. (Conference) Farideh Tavazoee, Davide Buscaldi, Claudio Conversano, Francesco Mola,

"Detecting Social Bots and other Malicious Content Spammers on Twitter", Under Submission. 2018:

2. (Journal) Farideh Tavazoee, Claudio Conversano, Francesco Mola, "Predicting Popularity Trend from Twitter", Under Submission.

3. (Journal) Diego Reforgiato Recupero, Mehwish Alam, Davide Buscaldi, Farideh Tavazoee,

"Figurative language detection in Social Media leveraging Semantic Frames and BabelNet Synsets", Under Submission.

2017:

4. (Conference) Farideh Tavazoee, Claudio Conversano, Francesco Mola, "Investigating the Relationship Between Tweeting Style and Popularity: The Case of US Presidential Election 2016", International Conference on Knowledge Engineering and the Semantic Web, Nov 2017, Szczecin, Poland..

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