Anibal Sólon Heinsfeld

https://anibalsolon.com

https://github.com/anibalsolon

https://resume.anibalsolon.com/scholar

Work & Research Experience

Pestilli Lab - University of Texas at Austin

Graduate Research Assistant – 09/2021-Present

Optimization of diffusion MRI sparse models, to improve state-of-the-art tractography and the

assessment of structural connectivity of the brain. Management of the brainlife.io infrastructure and

development team.

● Python, Bash, Javascript, Rust

● Infrastructure planning

● Neuroimaging preprocessing

Whole Communities–Whole Health @ Bridging Barriers - University of Texas at

Austin

Graduate Research Assistant – 08/2020-09/2021

Development of a mobile app for COVID-related procedures for the University (reaching 75k students)

and mobile app to perform studies, via remote sensing of the participants' physical activities and surveys.

Design and implementation of scalable API using serverless technology. Analyses of actigraphy data for

behavior assessment during the pandemic.

● Python, Bash, C, R, Javascript, React + Redux + Sagas, React-Native.

● AWS API Gateway, Lambda, Cognito, Aurora Serverless, KMS, Systems Manager.

● API design and documentation. Data privacy and security. Data visualization.

● Complete planning and implementation of a secure infrastructure in AWS, using Terraform.

Computational Neuroimaging Lab @ Dell Medical School - University of Texas at

Austin

Graduate Research Assistant – 09/2019-09/2021

Development of high-throughput and extensible preprocessing pipelines for medical data, mainly

focusing on brain MRI imaging. Hypothesis validation of cerebral blood ﬂow estimation using arterial

spin labeling images.

● Python, Bash, C, R, Javascript, React + Redux + Sagas.

● AWS Batch, Containers (Docker & Singularity), HCP (SLURM @ TACC).

● Data visualization.

Child Mind Institute

Assistant Research Scientist – 02/2018-08/2019

Focus on the maintenance of the Conﬁgurable Pipeline for the Analysis of Connectomes (C-PAC) project,

by helping other researchers to augment their capabilities on preprocessing and analysis of resting-state

fMRI data. Technical support for researchers, enabling them to focus on the research questions rather

than on technical details.

Planejei

CTO, Chief Data Scientist – 10/2015-04/2018

Research and management of technologies used in the company. Creation of Marvin, the robot-advisor

of Planejei. Focus on Machine Learning and recommendation systems. Large use of containerization,

using Docker and Kubernetes on Google Cloud Platform, Amazon Web Services and IBM BlueMix. Focus

on scalability and continuous integration. Optimization of learning algorithms and messaging methods.

Intuitivus Data Processing

CTO – 05/2012-08/2014

Research and management of technologies used in the company. Analyze, develop, and deploy

high-performance Business Intelligence (BI) systems to facilitate critical decision making for managers of

customer companies, such as Everything But Water. Focus on analytical information visualization and

optimization.

Calc Management System

Java/Javascript Developer – 04/2012-08/2013

Development of a tax calculator for high-trading volume investors. Test-driven programming of scalable

web-portal for thousands of customers, computing millions of stock transactions per day. Management

of load balancing, scaling, and general dev-ops of the startup. Integration with Brazilian investments

system, to retrieve user transactions automatically in an end-to-end service.

Compasso Technology

Java/Javascript Developer – 09/2011-04/2012

Development of a large web portal in Vivo, the largest telecommunications company in Brazil. Using the

Oracle technology stack, my team and I developed a support center, where the user could retrieve

information about mobile plans, support tickets and online chat.

University of Passo Fundo

PHP/Javascript/Delphi Developer – 02/2011-08/2011

Development of internal systems to the university processes and students portal. Individually, I worked

on an employee scale management system through work orders. By creating an innovative interface for

managers to control the scales, we were able to optimize the maintenance processes of the university.

Educational Experience

PhD in Computer Science

University of Texas at Austin / US – 2019-present

Research in Machine Learning method applied in Neuroscience. Development of accurate models for

white matter tracts diffusion prediction, using sparse group linear models and multiple tissue

compartments.

Advisors: Franco Pestilli PhD, Alexander Huth PhD

MSc in Computer Science

Pontifícia Universidade Católica do Rio Grande do Sul / Brazil – 2014-2016

Thesis: Deep Learning for Autism identiﬁcation in Neurological data

Research in Artiﬁcial Intelligence and Machine Learning focusing on Neuroscience. Cloud conﬁguration

for parallel computing with GPUs. Usage of modern deep learning frameworks, such as Tensorﬂow and

Theano.

Advisors: Felipe Rech Meneguzzi PhD, Alexandre Rosa Franco PhD

Evaluation committee: R. Cameron Craddock PhD, Paulo Martins Engel PhD, Rodrigo Barros PhD

BSc in Computer Science

Universidade de Passo Fundo / Brazil – 2008-2013

Thesis: Artiﬁcial Intelligence and the Stock Market: Using neural networks to predict trends

Use of a mathematical model inspired by biological brain functioning to recognize patterns within the

time series obtained from the evolution of a certain stock in BMF & Bovespa.

Advisor: Roberto dos Santos Rabello PhD

Evaluation committee: Carlos Amaral Hölbig PhD

Publications and Conferences

LEVITAS, Daniel; HAYASHI, Soichi; VINCI-BOOHER, Sophia; HEINSFELD, Anibal; BHATIA, Dheeraj;

LEE, Nicholas; GALASSI, Anthony; NISO, Guiomar; PESTILLI, Franco. ezBIDS: Guided standardization of

neuroimaging data interoperable with major data archives and platforms. In press, 2023. Pre-print:

arXiv:2311.04912.

HAYASHI, Soichi; CARON, Bradley; HEINSFELD, Anibal S.; [+60 authors]; PESTILLI, Franco. brainlife.

io: A decentralized and open source cloud platform to support neuroscience research. In press, 2023.

Pre-print: arXiv:2306.02183.

HEINSFELD, Anibal Sólon; MCDONALD, Daniel J.; PESTILLI, Franco. (2023). Improving the accuracy

of models for the evaluation of tractography algorithms. Research for Y’all Graduate Showcase,

University of Texas at Austin, 2023.

HEINSFELD, Anibal Sólon; MCDONALD, Daniel J.; PESTILLI, Franco. (2023). Improving the accuracy

of models for the evaluation of structural brain connectomes. Organization for Human Brain Mapping

2023 Annual Meeting, 2023.

HEINSFELD, Anibal Sólon; MCDONALD, Daniel J.; PESTILLI, Franco. (2022). Improving structural

brain connectomes through informed forward modeling. Neuroscience 2022, Society for Neuroscience,

2022.

LIANG, Xiaoxuan; COHEN, Aaron; HEINSFELD, Anibal Sólon; PESTILLI, Franco; MCDONALD, Daniel

J. sparsegl: An R Package for Estimating Sparse Group Lasso. In press, 2022.

Pre-print: arXiv:2208.02942.

LI, Xinhui; AI, Lei; GIAVASIS, Steve; JIN, Hecheng; FECZKO, Eric; XU, Ting; CLUCAS, Jon; FRANCO,

Alexandre; HEINSFELD, Anibal Sólon; ADEBIMPE, Azeez; VOGELSTEIN, Joshua T.; YAN, Chao-Gan;

ESTEBAN, Oscar; POLDRACK, Russell A.; CRADDOCK, Cameron; FAIR, Damien; SATTERTHWAITE,

Theodore; KIAR, Gregory; MILHAM, Michael P. Moving Beyond Processing and Analysis-Related

Variation in Neuroscience. In press, 2022.

Pre-print: https://doi.org/10.1101/2021.12.01.470790

GAU, Rémi; [+36 authors]; HEINSFELD, Anibal S; [+101 authors]. Brainhack: Developing a culture of

open, inclusive, community-driven neuroscience. Neuron, 2021.

DOI: https://doi.org/10.1016/j.neuron.2021.04.001. Authors omitted for brevity.

GIAVASIS, Steve; CLUCAS, Jon; LI, Xinhui; Jin; HECHENG; AI, Lei; SÓLON, Anibal; CRADDOCK,

Cameron; MILHAM, Michael. (2021). The Conﬁgurable Pipeline for the Analysis of Connectomes

(C-PAC) 2020-2021: Transitioning Out of Beta. Organization for Human Brain Mapping 2021 Annual

Meeting, 2021.

WENG, Timothy; VELA, Ruben; WEBER, Wade; DODLA, Manwitha; HEINSFELD, Anibal Solon;

PARKER, Samuel; SIMON, Blake; DEMETER, Damion; NUGIEL, Tehila; WHITMORE, Lucy; MILLS,

Kathryn; CHURCH, Jessica; HABERMAN, Michael; CRADDOCK, Cameron. The impact of customized

head molds on motion and motion-related artifacts from structural and functional MRI scans in

children. 2021. DOI: https://doi.org/10.1101/2021.03.24.21253213

LI, Xinhui; GIAVASIS, Steve, Jin; HECHENG; AI, Lei; SÓLON, Anibal; ADEBIMPE, Azeez; FRANCO,

Alexandre Rosa; POLDRACK, Russell Alan; VOGELSTEIN, Joshua Tzvi; XU, Ting; SATTERTHWAITE,

Theodore; CRADDOCK, Cameron; MILHAM, Michael. Evaluating and Improving Cross-Pipeline

Reproducibility in Functional Connectomics: A Case Study. Organization for Human Brain Mapping

2020 Annual Meeting, 2020.

JIN; Hecheng; GIAVASIS, Steve; LI, Xinhui; SÓLON, Anibal; AI, Lei; FRANCO, Alexandre Rosa;

RAMIREZ, Julian; WANG, Xindi; GOZZI, Alessandro; PAGANI, Marco; FOX, Andrew; MESSINGER,

Adam; FAIR, Damien; KEILHOLZ, Shella; RUSS, Brian; XU, Ting; CRADDOCK, Cameron; MILHAM,

Michael. A Uniﬁed, End-to-End Pipeline Solution for Human and Nonhuman Functional Connectomics.

Organization for Human Brain Mapping 2020 Annual Meeting, 2020.

NIKOLAIDIS, Aki; HEINSFELD, Anibal Solon; XU, Ting; BELLEC, Pierre; VOGELSTEIN, Joshua;

MILHAM, Michael. Bagging improves reproducibility of functional parcellation of the human brain.

NeuroImage, 2020. DOI: https://doi.org/10.1016/j.neuroimage.2020.116678

HEINSFELD, Anibal Solon; FRANCO, Alexandre Rosa; MILHAM, Michael; Towards sparse

hierarchical graph classiﬁers for autism spectrum disorder identiﬁcation. Poster presentation on the

Montreal Intelligence Artiﬁcielle & Neuroscience; Montreal, Canada. Dez 2018.

One of the 10 winners of the poster competition.

HEINSFELD, Anibal Solon; Enhancing classiﬁer model robustness with variational auto-encoders

and semi-supervised learning for autism spectrum disorder identiﬁcation. Poster presentation on the

Sixth Biennial Conference on Resting-State and Brain Connectivity; Montreal, Canada. Set 2018.

Selected talk and one of the 5 winners of the poster competition.

HEINSFELD, Anibal Solon; FRANCO, Alexandre Rosa; CRADDOCK, R. Cameron; BUCHWEITZ,

Augusto; and MENEGUZZI, Felipe. Identiﬁcation of autism spectrum disorder using deep learning and

the ABIDE dataset. Neuroimage: Clinical, 2017. DOI: 10.1016/j.nicl.2017.08.017

XAVIER, Laura de Lima; HEINSFELD, Anibal Solon; AGUZZOLI, Cristiano; SOLDATELLI, Matheus;

FRANCO, Alexandre Rosa; MENEGUZZI, Felipe Rech; and BUCHWEITZ, Augusto. Classifying brain

states during cognitive tasks: a functional magnetic resonance study in children at reading acquisition

stage. World Congress on Brain, Behavior and Emotions, Buenos Aires, Argentina, 2016.

CRADDOCK, R. Cameron; [+18 authors]; HEINSFELD, Anibal Solon; [+26 authors]. Brainhack: a

collaborative workshop for the open neuroscience community, in GigaScience, Vol. 5, 2016. DOI:

10.1186/s13742-016-0121-x. Authors omitted for brevity.

PEREIRA, Ramon F.; MAGNAGUAGNO, Maurício C.; HEINSFELD, Anibal Solon; and MENEGUZZI,

Felipe. LOCUS: An environment description language for JASON, 9th Software Agents, Environments

and Applications School (WESAAC), Niteroi, Brazil, 2015. Proceedings: https://goo.gl/mz9Yd4

Scholarships, Fellowships, and Awards

Full Master's degree - Administered scholarship

Pontifícia Universidade Católica do Rio Grande do Sul / Brazil – 2014-2016.

Funding Institution: CAPES/PROSUP

Advisor: Felipe Rech Meneguzzi PhD

Scientiﬁc Initiation Scholarship PIBIC/CNPq

Universidade de Passo Fundo / Brazil – 2010

Funding Institution: CNPq

Project: The hypermedia in the creation of learning collectivities in the municipal schools of Passo Fundo

Advisor: Adriano Canabarro Teixeira PhD

Scientiﬁc Initiation Scholarship PIBIC/UPF

Universidade de Passo Fundo / Brazil – 2009

Funding Institution: UPF

Project: The hypermedia in the creation of learning collectivities in the municipal schools of Passo Fundo

Advisor: Adriano Canabarro Teixeira PhD

Winners of the Poster Competition on the Montreal Intelligence Artiﬁcielle &

Neuroscience 2018

http://www.crm.umontreal.ca/2018/MAIN2018/ – 2018

Poster: Towards sparse hierarchical graph classiﬁers for autism spectrum disorder identiﬁcation. One of

the ten winners against ~50 posters.

Winners of the Poster Competition on the Sixth Biennial Conference on

Resting-State and Brain Connectivity

http://www.restingstate.com/ – 2018

Predictive Analytics in Mental Health Competition

http://psymri.org/PAC.html – 2016

In this competition, my team and I developed a model to classify patients suffering from Depression and

healthy individuals based on resting-state fMRI data. PAC 2016 provides a balanced dataset of 436

resting-state fMRIs, obtained at 11 different scanning sites. The rows of the dataset have been shufﬂed

in order to anonymize it. Our solution was based on a previous analysis of voxels, in an attempt to

identify the relevant ones. After selecting 200 voxels, we created a correlation matrix and used it as

features for a linear SVM. By using this pipeline, we achieved second place in the competition.

Multi-Agent Programming Contest

https://multiagentcontest.org/2016/ – 2016

In this competition, my team and I developed a multi-agent system to solve a scenario based on a real city

map, where the goal is to earn as much money as possible, which is rewarded for completing certain jobs.

Our solution is based on JASON to deﬁne the agents behavior and how they coordinate to form

sub-teams for tasks, using the Contract Net Protocol. We achieved ﬁrst place in the competition.

Research / Teaching Experience

Teaching Assistant

Pontifícia Universidade Católica do Rio Grande do Sul – 2015

Assist in practical classes to undergraduate students on Artiﬁcial Intelligence. Teach courses to students

on Artiﬁcial Neural Networks. Develop hands-on activities for students covering topics such as

Automatic Planning, Multi-agent Systems, and Reinforcement Learning.

Neuroimaging of Human Cognition

Pontifícia Universidade Católica do Rio Grande do Sul – 2015

Development of new techniques for neuroimaging analysis and studies of the neural bases of higher

cognitive processes. Part of the ACERTA project (Evaluation of Children at Risk of Learning Disorder).

Contribution to the construction of predictive models for the diagnosis of learning disorders.

Autonomous Systems Group

Pontifícia Universidade Católica do Rio Grande do Sul – 2015

Research on commitment alignment of multi-agent systems. Assistance for undergraduates on their

research on robotics using Gazebo and ROS. General laboratory management.

Volunteer Activities

OpenNeuro: Collaborations on the open-source project, by implementing oAuth2 authentication ﬂow

using ORCID, as an alternative to Google given it is used by academics and is not blocked in China.

Descartaê: Collaborations on the open-source project, by developing a mobile app and a web portal to

employ mechanisms for indexation of waste collection centers.

Women in Neuroscience: Board member. Improvements in the website to enable easier maintenance of

registered proﬁles and recommendations. General technology advising.

Brainhack Global: Continuous support for the +4000 community, organizing synchronous and

asynchronous events worldwide, and welcoming newcomers.

OHBM Brainhack 2023: Co-chair and designer of the 2023 edition of the OHBM Hackathon.

UniFavela: Technological support for project advertising and conducting online classes during the

pandemics.

Skills

Not a comprehensive list of technologies. Please refer to Github for (real-world) projects and examples.

Some projects are private, but I am happy to discuss and showcase them.

Programming: Python, Tensorﬂow, Pytorch, JavaScript, TypeScript, PL/SQL, Rust, C, C#, C++, CUDA,

Bash, R, Octave, PHP, Java, Kotlin;

Databases: PostgreSQL, MySQL, Oracle, SQLite, MongoDB, AWS RDS;

Server-side: Web protocols and ﬂows, Apache HTTP, Apache Tomcat, Nginx, Prometheus, LDAP, Amazon

Web Services, Google Cloud, Microsoft Azure, IBM Cloud, Terraform, Docker, Kubernetes, Linux

management;

Security: System security, system, and infrastructure design, conﬁguration hardening, deobfuscation,

and reverse engineering, pen-testing.