Francisco Pereira
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Director of the Machine Learning Core at the National Institute of Mental Health (NIMH)
My main interest is the use of artificial intelligence and machine learning to augment human capability, in domains such as scientific discovery and decision making. I have extensive research experience in machine learning, and have led multiple interdisciplinary teams working on psychology, psychiatry, and neuroscience. At present, my focus is on demonstrating how a machine learning core facility embedded within a scientific research organization can help transform the way it fulfills its mission. For more information about that work, please see the web page for the Machine Learning Core: https://cmn.nimh.nih.gov/mlt For more information about me, please see: http://www.franciscopereira.org https://scholar.google.com/citations?user=HpbSzssAAAAJ&hl=en
Carnegie Mellon University
Ph.D., Computer Science and Neural Basis of Cognition
January 1, 2007 – Present
Santa Fe Institute
Complex Systems Summer School
N/A – Present
Universidade do Porto
Bachelor of Science - BS, Computer Science
N/A – Present
National Institute of Mental Health (NIMH)
Director of the Machine Learning Core
June 1, 2024 – Present
Center for Responsible AI
Member of the Scientific Board
April 1, 2023 – Present
Lisbon, Portugal
National Institute of Mental Health (NIMH)
Head of the Machine Learning Team
January 1, 2018 – June 1, 2024
Siemens Healthcare
Program Manager (Computational Neuroscience)
January 1, 2016 – December 1, 2017
Princeton, NJ
Siemens Healthcare
Staff Scientist
December 1, 2014 – January 1, 2016
Princeton, NJ
Siemens Corporate Technology
Research Scientist
October 1, 2011 – November 1, 2014
Princeton, NJ
Princeton University
Research Associate
August 1, 2007 – September 1, 2011
Princeton, NJ
IARPA Knowledge Representation in Neural Systems
December 1, 2013 – December 1, 2017
The main goal of the project is to build a model of how semantic knowledge is represented in the brain and used to assemble a mental representation while a sentence is being read. The project takes place within the IARPA Knowledge Representation in Neural Systems program (http://www.iarpa.gov/index.php/research-programs/krns), and is being carried out by my team, which comprises 12 people across five institutions (Siemens, Princeton University, MIT, MGH and Harvard University). Our models are based on learning distributed representations of individual words from text corpora, as well as resources such as FrameNet and WordNet, and using recursive neural network approaches and other techniques to assemble them into the representation of a sentence. The models are validated by decoding mental content from brain imaging data acquired with our own experiments, using custom machine learning methods.
Cultural Fit Analysis
The candidate's background is heavily rooted in academic research and government institutions, with a strong emphasis on scientific inquiry and method development. While this demonstrates a deep analytical mindset, the transition to a potentially more business-oriented or product-focused Data Analyst role might require adaptation. The diversity of projects, particularly the IARPA program and various NIH/NSF projects, shows adaptability to different research contexts. The role as a Member of the Scientific Board for the Center for Responsible AI indicates an interest in ethical considerations, which is a positive cultural fit for many organizations. However, the resume lacks explicit mention of experience in typical business intelligence tools or commercial data analysis environments, which could be a gap depending on the target company's culture.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and organizational skills through establishing and directing the Machine Learning Core at NIMH. Their experience in multi-institutional collaborations (IARPA project) indicates strong teamwork and communication abilities. The focus on research and method development suggests a proactive and problem-solving mindset. However, the provided data does not offer direct insights into stress handling or specific work attitude beyond professional achievements.