Teaching the course: Artificial Intelligence, which focuses on Symbolic AI. Students explore:

• The foundations of Symbolic AI, from knowledge representation to logic-based reasoning.
• Building intelligent agents that can reason, plan, and solve problems using search algorithms.
• Ethical implications of using AI technology.

Corti builds intelligent machines for augmented medicine.
I contributed in the following ways:

• Built a gRPC microservice adapter for real-time data streaming and conversion to Corti’s online detection service, decreasing latency between services by 70%.
• Main architect of a Data Warehouse solution to allow customers and internal stakeholders access to their usage data, unlocking insights for 30% call reduction time.

Corti builds intelligent machines for augmented medicine. Our AI supports medical personnel on making decisions in real time during medical emergencies, combining bleeding-edge machine learning research and real-world data from emergency calls. I worked on the following types of projects:

• Scoped and built a full-stack end2end testing framework for Microsoft Azure cloud deployments.
• Create and maintain end2end CI/CD Microsoft Azure pipeline for scalable Dockerized using Google developed gRPC-based microservices with Tensorflow models built-in.

Corti builds intelligent machines for augmented medicine. Our AI supports medical personnel on making decisions in real time during medical emergencies, combining bleeding-edge machine learning research and real-world data from emergency calls. I worked on the following types of projects:

• Building and testing REST-APIs for SQL and NoSQL (Mongo, ElasticSearch) databases in Azure Functions.
• Constructing and deploying Data Pipelines with Azure Data Factory
• Automating cloud deployments of Dockerized machine-learning based microservices.
• Develop and deploy machine-learning models for real-time NLP tasks using TensorFlow.
• Improved data upload pipeline to pSQL databases by 98% from ~3 days to 15 minutes.
• Migrate Jenkins-based CI/CD hosted in Amazon AWS to Microsoft Azure Pipelines

Projects:

• U-NET segmentation of microscopy images to quantify wear of piston ring coatings.
• Characterizing graphite defects in cast iron by morphology analysis.

Use of a variety of statistical models (ConvNets, LSTMs, Hidden Markov Models) on diverse biological datasets to streamline current data processing pipelines and determine hidden trends in single-molecule enzymology.
Projects:

• Automating data analysis of smFRET traces in DeepFRET.
• Simulation of CYPOR conformational dynamics.
• Statistical analyses of multiplexed liposome assays in SPARCLD

Maintaining and running a Tourist Cabin for the Norwegian Tourist Association. Responsibilities:

• Tenant relations
• Serving at all meals (>40 people)
• General maintenance of the property

Responsibilities:

• Updating SharePoint, Excel, and M3 databases with biochemical analysis results for shipments
• Maintaining Excel spreadsheets and assisting in preparing Q3 reports
• Taking minutes at multilingual phone meetings in the Back Office department