Resume
## Pablo LasoI am a data scientist and machine learning engineer in Nashville, TN mostly using NLP and machine learning to solve business problems and deliver efficient, scalable solutions.Pablo Laso¶
I am a Data Scientist especialized in Machine Learning, Deep Learning and Computer Vision engineer.
I started my BSc in Biomedical Engineering in Madrid, Spain. There, I had great professors who shaped me into what I am today. Not only did I achieve top grades (which helped me receive scholarships for my Master's studies in Sweden, the Netherlands, and Boston), but I also participated in fascinating projects, especially at LAIMBIO (our medical imaging lab). These projects included MRI instrumentation with the Martinos Center at Harvard Medical School and designing a CAD system for my BSc thesis with Quirón Hospital and General Electric.
After completing my Bachelor's degree, I pursued a Master's in Data Science at KTH in Stockholm and a Master's in Computer Science at UT in the Netherlands to enhance my skills in these areas and fully dive into the medical AI and medical imaging fields. Studying abroad was a unique personal and professional experience that taught me to appreciate diverse environments and the value of teamwork. I was also fortunate enough to work in the Radiology Department at the Karolinska Institutet, one of the top 10 hospitals in the world and home to the Nobel Prize committee in Medicine.
## Education<br><b>Georgia Institute of Technology</b><br/>Currently pursuing a Master's degree in computer science with a specialization in machine learning. <br/>Expected graduation: 2020<b>Belmont University</b><br/>Graduated: May 2015 (economics and statistics)Education¶
University of Twente (Netherlands)
Currently pursuing a M.Sc. Computer Science (with a specialization in Data Science). Expected graduation: 2023
KTH - Royal Institute of Technology (Stockholm)
Graduated: Jun 2022 (M.Sc. Data Science)
Rey Juan Carlos University (Madrid)
Graduated: Jun 2021 (B.Sc. Biomedical Engineering)
xxxxxxxxxx## Experience<br/><b>The General Automobile Insurance Services, Inc.</b> | May 2017 - Present<br/><i>Data Scientist II | Sep 2018 - Present</i>• Utilize paragraph vectors (using gensim's doc2vec implementation) to perform concept detection to search for abstract concepts such as "Spanish speaking", "fracture", and "attorney representation" (among others) in claim notes • Implement online learning in order to update machine learning models in real time with new information<i>Data Scientist I | May 2017 - Sep 2018</i>• Build a nation-wide price elasticity model using a Mixed Effects/Hierarchical Logistic Regression algorithm (with cross classified and nested random effects) to predict demand for a product at various pricing structures</br>• Work closely with the AVP of Analytics and the Data Science Manager to build a model to optimize ad expense allocation for each state using price elasticity</br>• Optimize claim routing using a Support Vector Machine model (Python/SciKit-Learn)</br>• Architect and implement RESTful APIs (Python/Flask, SQLAlchemy, Celery, Redis, RabbitMQ) that expose machine learning models for consumption</br>• Perform various natural language processing tasks (R/tidytext, Python/Gensim), including sentiment analysis, topic modeling (LDA, hLDA), and training Word2Vec and Doc2Vec models</br>• Build a topic modeling dashboard for the Digital Experience team to better understand what our clients are chatting about</br>• Use topic modeling to predict if a claim needs intervention by a supervisor<br/><b>Perception Health</b> | Jan 2015 - April 2017<br/><i>Software Engineer/Data Scientist</i>• Built machine learning models (Python) that used lab data to predict if a patient will be admitted or not within a 30-day window with 75% accuracy</br>• Worked alongside Perception Health's Chief Data Scientist to analyze physicians’ referral patterns and consult hospitals on how to best reduce out-of-network referrals</br>• Used ArcGIS and ESRI data (with PostGIS) to visualize healthcare trends geographically</br>• Lead production on Perception Health's flagship product since March 2015 to the present</br>• Built customizable, interactive dashboards (Leaflet.js, D3.js, Crossfilter.js) </br>• Optimized SQL queries and data preparation for faster graph rendering and page-load times</br>• Utilized Agile methodologies (JIRA) to organize releases while ramping up features</br>• Worked with the lead architect to optimize SQL scripts across the primary product's platform</br>• Converted the platform to a RESTful API for more efficiency and to decouple the server-side code from the client side templatesExperience¶
Karolinska Institutet | Dec 2021 - Sep 2022 | Stockholm, Sweden.
Engineer Assistant
• Designed and implemented a server to manage all image processing queries locally, streamlining the process and increasing efficiency.
• Built a robust and automated image processing pipeline that improves processing times and ensures consistent results by selecting the appropriate software based on the task and available data.
• Streamlined image processing by automating pipelines, resulting in faster and more accurate processing times.
• Demonstrated expertise in database management using Python and SQL, and worked with medical Picture Archiving and Communication Systems (PACS).
• Developed a query engine to retrieve patient information efficiently and accurately.
• Worked with a variety of medical image processing software, including FreeSurfer, SAMSEG, SPM, LST, and FSL.
## Skills<br/>• Creator of SQLCell, an open source SQL client for Jupyter Notebook, which I presented at the first annual JupyterCon 2017<br/>• Creator of Achoo, a predictive system that uses allergen, air quality, and weather data to notify my son’s school nurse when he’ll need his inhaler, and was presented at AnacondaCON 2018<br/>• Contributor to <a href="https://learndatasci.com">learndatasci.com</a>, a data science blog <br/>• Creator of and primary contributor to <a href="https://tmthyjames.github.io">Grid Searched</a>, a machine learning blogSkills¶
• Data Analytics, Creativity and Problem-Solving, Innovation and Business Analysis, Project Management, Software Development, Image Analysis and Processing, Statistical Inference (A/B Testing), Artificial Intelligence and Machine Learning, Data Visualization, Data Mining, Deep Learning and Computer Vision, Database Management and Query Engines, and Electronics and Circuit Design.
Languages:
• English (Cambridge English Advanced (C1) certified, full professional proficiency), Spanish (native speaker), and Italian (professional working proficiency).
Programming and Technical Skills:
• Python, MATLAB, SQL, shell, Julia, Linux, macOS, Windows, Git, Visual Studio Code, Microsoft Excel, Apache Spark, Apache Hadoop.
Libraries and Tools:
• Pandas, TensorFlow 2.0, PyTorch, Keras, OpenCV, scikit-image, Seaborn, pyRadiomics, Pyomo, scikit-learn, PySpark.
Medical Imaging Tools:
• ITK-Snap, 3D Slicer, FSL, SPM, Dartel, CAT12, ANTs, FreeSurfer, TRACULA, Orthanc, PACS management.
Electronics Design Tools:
• PCBA design, Eagle PCB design, Multisim simulation, Arduino programming, 3D design (AutoCAD, Cura).
## Skills<br/>• Creator of SQLCell, an open source SQL client for Jupyter Notebook, which I presented at the first annual JupyterCon 2017<br/>• Creator of Achoo, a predictive system that uses allergen, air quality, and weather data to notify my son’s school nurse when he’ll need his inhaler, and was presented at AnacondaCON 2018<br/>• Contributor to <a href="https://learndatasci.com">learndatasci.com</a>, a data science blog <br/>• Creator of and primary contributor to <a href="https://tmthyjames.github.io">Grid Searched</a>, a machine learning blogProjects¶
• Designed a ML and DL-based algorithm (CAD system) for Prostate MRI detection and classification. Project at Quirón Hospital, funded by General Electric (used as my bachelor's thesis) (2021).
• Contributed to the replication of a Tabletop MRI (Boston, MA, USA). Worked at LAIMBIO in Madrid, in collaboration with the Martinos Center (MGH, Harvard Medical School) (2019-20).
• Built two Deep Learning-based Ultrasound Lung Image Recognition systems (for Pneumonia, and COVID-19). Designed CNNs architecture and utilized Transfer Learning. Completed an internship at Alcorcón HUFA Hospital, Madrid (2020).
• Created Gest2talk (GitHub repo), a myo-armband for people with speech impairments. Completed the project at the University of Salamanca (2020).
## Achievements<br/>• Dean’s list at Belmont University Fall 2012, Spring 2013</br>• 1 of 100 engineers nationally accepted to attend viSFest, a D3.js conference</br>• My project, SQLCell, was accepted to present at JupyterCon 2017</br>• My project, Achoo, was accepted to present at AnacondaCON 2018Achievements¶
• Spanish FMM "Excelencia" scholarship, among top-20 STEM students (2022).
• Swedish CSN scholarship (2021).
• 3rd prize Makeathon 4.0 (Gest2talk project), University of Salamanca (2019).
• Madrid Region "excellence" highschool diploma (2017).