Pablo De Castro Email & Phone Number

Spain

Joined full-time to work at the intersection of Product and Engineering, including:- Lead and coordinate the product development efforts and team through a pivot of the startup focus from a voluntary carbon market marketplace to an enterprise data and software platform.- Successfully plan and deploy frequent product iterations from start to finish, including integrations with customers and external data sources.- Contribute to the product and engineering efforts at many different levels (customer inteviews/reseach, product design, software engineering, cloud infrastructure, etc).- Provide advice and support for the founding team through the strategic shift of the business direction.

As one of the founding engineers of this startup, my part-time role in the company included:- Co-designing the strategy and approach for a forest monitoring, verification and reporting system for reforestation and conservation projects, that supports one of the core valuepropositions of the startup (i.e. transparency).- Building a prototype of such monitoring system for large forest conservation projects based onthe use of machine and deep learning on satellite imagery.- Co-designing, executing and validating a plan for integrating a monitoring system for the projectin the production web application of the carbon credit marketplace.- Supporting and advising the startup in various other technical domains such as software, dataarchitecture and cloud infrastructure.

Technical leadership for a cross-disciplinary chapter focussed on designing, building and improving solutions, products and processes with data science, machine learning and computer vision technologies both in the context of commercial clients and European R&D projects.Responsibilities (other than specific individual contributions) include: technical design and coordination of projects and proposals, co-definition of technological stack and methodologies, ensure and promote technical excellence and technology transfer, support and mentorship for other chapter members and collaboration in organization-wide initiatives.Highlighted projects (majority in a technical lead role):- Industry Sector: analyse, design and plan solutions for improving productivity andexisting processes in several industry sectors.- Education Sector: integrate and analyze automatic transcriptions using cloud services fordifferent video-conference providers and provide search capabilities.- DECODER H2020 R&D: integrate natural language processing models for codesummarization and variable misuse as services within a web application.- Internal Project: iteratively improve the data, machine learning and softwaredevelopment methodologies and infrastructure in order to make technical teams moreautonomous and productive.

Worked on a diverse set of projects that heavily rely on data science, machine learning andcomputer vision technologies, both in the context of commercial clients that want innovative solutions and European R&D projects.Highlighted projects (majority in a technical lead role):- Education Sector: design, build and deploy into production a system for advanced videoanalytics using deep learning technologies and fully integrated with their cloud infrastructure.- Education Sector: design, build and integrate heterogeneous business data sources andprovide a custom flexible solution to provide insights and visualizations to stakeholders.- Finance Sector: evaluate the viability of a system for public companies default predictionusing machine learning technologies.- Electric Power Sector: design and build feasibility demonstrator of an end-to-end platformfor the automatic detection of anomalies in electrical lines and towers using deep learning.- Robotics H2020 R&D: design and advise in core data and machine and deep learningcompetencies in the projects, mainly in the context of the visual perception module.

Padova Area, Italy

Within the AMVA4NewPhysics H2020 project, whose aim is to develop and apply state of the art machine learning techniques for High Energy Physics data analyses.Main projects:- New machine learning technique to construct inference-aware summary statistics.- Non-resonant Higgs pair production analysis at the LHC with the CMS detector.- Integration of TensorFlow-based multi-class jet tagger model DeepJet in CMS software.

Orange County, California Area

Collaboration with researches at the UCI Center of Machine Learning on differentiable approximations of histograms to build inference-aware losses for neural networks and the role of new deep learning techniques on jet quark-gluon tagging.

Milan Area, Italy

Worked on possible applications topological data analysis and developed a open-source package re-implementing the MAPPER algorithm with a scikit-learn-like API

Santander Area, Spain

Collaborating in data analyses within the CMS Collaboration, mainly related with b-tagging and top quark pair production.

Providence, Rhode Island Area

Carry out part of Master’s thesis with the Experimental Particle Physics research group.

Geneva Area, Switzerland

Working with an experimental research team on characterising silicon detectors using lasers. Developed an open-source simulator of the of drift dynamics of carrier distributions in complex semiconductor detectors

Santander Area, Spain

Focussed on the use of ontologies, knowledge bases and semantic web technologies to design a system for data preservation in High Energy Physics.

Doctor Of Philosophy - Phd, Physics, Cum Laude

PhD Thesis: "Statistical Learning and Inference in Particle Collider Experiments"

Master'S Degree, Physics, Average Grade: 9.7/10.0

Specialty in Advanced Physics Master’s thesis: " Measurement of CMS b-tagging efficiencies using the Flavour-tag Consistency Method.

Exchange Student, Physics

Bachelor'S Degree, Physics, Average Grade: 8.6/10.0

Mention in Fundamental Physics Final Year Project: " Measurement of the W+W- production cross section in pp collisions at a center-of-mass.