Jose Luis Silva, Ph.D.

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Jose Luis Silva, Ph.D.
Researcher in AI at LiU
Founder Aicavity Analytics
  • Researcher in AI:
    LiU 🇸🇪
  • Founder:
    Aicavity Analytics 🇸🇪
  • Life:
    Brazilian-Swedish 🇧🇷 🇸🇪
Research Interests:
  • Artificial Intelligence & Machine Learning
  • Graphs, Computer Vision & NLP
  • Deep Learning & Reinforcement Learning
  • Autonomous Systems & Decision Making
  • Multiscale Simulations & Materials Science
Professional Resume
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Our paper in pattern recognition and complexity is under review:

I’m Jose Luis Silva, Postdoctoral Researcher in Artificial Intelligence at Linköping University (Sweden) and Founder at Aicavity Analytics. Aicavity Analytics raised its first open-call seed with top Researchers from Brazil to build an AI-based software for Exploration Geophysics. I’m also a reviewer for the NeurIPS, Journal Vacuum IF: 3.67 (Elsevier) and Sensors (MDPI) covering AI, Materials Science & Machine Learning.  I hold a Ph.D. in Physics from Uppsala University, where I have worked with Modeling and Simulation of Materials for Energy Applications. Do not hesitate in contacting me if you have any questions (NO SPAM).
 
I hope you can get some interesting tips here!

GitHub & Other Projects

Optimize ML Models and Deploy Human-in-the-Loop Pipelines
May 13, 2022
Optimize ML Models and Deploy Human-in-the-Loop Pipelines

Optimize ML Models and Deploy Human-in-the-Loop Pipelines 3 Projects – Description: When training ML models, hyperparameter tuning is a step…

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Build, Train & Deploy Machine Learning Pipelines using BERT, RoBERTa and Amazon Sagemaker
May 13, 2022
Build, Train & Deploy Machine Learning Pipelines using BERT, RoBERTa and Amazon Sagemaker

Build and Deploy Machine Learning Pipelines using BERT and RoBERTa and Amazon Sagemaker 3 Projects Description: Automate a natural language…

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Analyze Datasets and Train ML Models using AutoML
May 13, 2022
Analyze Datasets and Train ML Models using AutoML

4 Projects Description: Perform a multiclass classification for sentiment analysis by first ingesting product reviews data into a central repository,…

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Backtesting
May 2, 2022
Backtesting

Backtesting Project Description: Build a fairly realistic backtester that uses the Barra data. The backtester will perform portfolio optimization that…

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Combining Signals for Enhanced Alpha
May 2, 2022
Combining Signals for Enhanced Alpha

Combining Signals for Enhanced Alpha Project Description: Combine signals on a random forest for enhanced alpha, and solve the problem…

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Sentiment Analysis with Neural Networks
May 2, 2022
Sentiment Analysis with Neural Networks

Sentiment Analysis with Neural Networks Project Description: Here you will build your own deep learning model to classify the sentiment…

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Natural Language Processing on Financial Statements
May 2, 2022
Natural Language Processing on Financial Statements

Natural Language Processing on Financial Statements Project Description: NLP Analysis on 10-k financial statements to generate an alpha factor. For…

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Alpha Research and Factor Modeling
May 2, 2022
Alpha Research and Factor Modeling

Alpha Research and Factor Modeling Project Description: Build a statistical risk model using PCA. You’ll use this model to build…

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Smart Beta and Portfolio Optimization
May 2, 2022
Smart Beta and Portfolio Optimization

Smart Beta and Portifolio Optimization Project Description: Build a smart beta portfolio and compare it to a benchmark index. To…

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Breakout Strategy
May 2, 2022
Breakout Strategy

Breakout Strategy Project Description: Implement the breakout strategy, find and remove any outliers, test to see if it has the…

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Artificial Intelligence for Trading
May 2, 2022
Artificial Intelligence for Trading

Aritificial Intelligence for Trading. Udacity and WorldQuant Asset Management – My Certificate –  My Solutions & Projects – Artificial Intelligence…

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Trading with Momentum
May 2, 2022
Trading with Momentum

Trading with Momentum Project Description: Implement a trading strategy and test to see if it has the potential to be…

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Lane Detection with Hough Transformation
May 1, 2022
Lane Detection with Hough Transformation

Lane detection with Hough Transformation Project Description: How to Find Lane Lines on the Road using Hough transformation Lane line…

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My Timeline & Experience:

Education & Academia

PostDoc in Artificial Intelligence
Linköping University, Sweden
Mar 2021 - Present

Development of Artificial Intelligence models.

where to find me?
Steering Committee Advisory Board Member
Junior Faculty, Linköping University, Sweden
June 2021 - Sept 2022
National Junior Faculty
Licenciate and Ph.D. in Physics
Uppsala University, Sweden
Mar 2016 - Sep 2020

My Thesis: Modelling and Simulation of Electro-catalysts for Green Energy: From Solvated Complexes to Solid-Liquid Interfaces

• Teaching Experience: Mekanik Baskurs (2 years)

• Administrative Experience: Responsible for the Materials Theory Division Seminars.

• Resources: My Ph.D. was financed by Uppsala University, and the projects/travels were mixed - Supervisor Dr. Moyses Araujo, and Co-Supervisors Dr. Olle Björnholm, and Dr. Barbara Brena (i.e. STINT-CAPES Brazil-Sweden, Knut and Alice Wallenberg Foundation, and Vetenskapsrådet).

• Computational Resources: KTH Beskow HPC, Tetralith SNIC, and Kebnekaise HPC. These projects involved approximately 300,000 cores*hours/month. I have written the project that was approved by the HPC Facility SNIC (JPCL 2019 Published).

• Experience: I have led the computational simulations of six projects using high-performance computing facilities to design materials for green energy.

•Programming Languages used: C/C++, Python, Matlab, and Shell-script.

• Metrics: 6 high-profile publications in international Journals.

• My Presentations:

STINT-Capes Conference, Rio de Janeiro, Búzios, and Natal, 2017 & 2018, Brazil (Seminar) - Photo1 Photo2

Workshop: Trieste - Uppsala Meeting on Photoelectron Spectroscopy, Uppsala University, Sweden 2018. (Seminar)

CoTXS mini-workshop, Uppsala University, Sweden 2018. (Seminar)

SUNCAT Summer Institute, Fundamentals and Applications of Heterogeneous Catalysis, Stanford University, California, USA 2017 - Poster

European Congress and Exhibition on Advanced Materials and Processes EUROMAT2019,  Stockholm, Sweden 2019 (Seminar) - Photo

Baltic Sea Region Hydrogen Network, Opera Hotel, Riga, Latvia 2017 - Photo

College on Multiscale Computational Modeling of Materials for Energy Applications - ICTP, Trieste, Italy 2016 - Photo

Download My Thesis
BSc and MSc in Physics
Federal University of Bahia, Brazil

Teaching Experience:

• Lecturer in Theoretical and Experimental Physics I and II (UFBA/Devry University)

• Lecturer in Mechanics of Materials I and II (Devry University)

• Assistant Lecturer in Solid State Physics I (UFBA)

Achievements:

• MSc in Physics (UFBA) - Ranked 1st - Group: LaPO (Laboratory of Optical Properties) - Field: Solid State Physics and Computational Simulations. Group Leader: Prof. Antonio Ferreira. Supervisor: Prof. Denis Gilbert Francis David

• BSc in Mining and Petroleum Engineering (UFBA) (Completed 16 Courses in 1 year before moving to Physics) - Ranked 1st

• Marketing Director at Crystal Mining and Petroleum - Junior STARTUP (UFBA)

• BSc in Geophysics (UFBA) (Completed 2 years before moving to Sweden) - Ranked 1st

• Ph.D. in Geophysics (UFBA) (Completed 1 year before moving to Sweden) - Ranked 1st

• Junior and Master Scientific Research Scholarship (2,5 years BSc and 2 years of MSc - National Council for Scientific and Technological Development, CNPq, Brazil)

1 - Project: Simulation of CO2 and water injection in front reservoir using Apollonian Networks as a porous-media to improve oil recovery mechanisms. (Ansys Fluent) - Group: Statistical Physics and Complex Systems, Supervisor: Prof. Roberto Andrade (UFBA)

2 -Project: Study of Magnetic Properties in Paramagnetic Aggregates via First Principles Calculations - Supervisor: Prof. Roberto Rivelino (UFBA)

3 - CV Lattes

LINK TO MEDIA

Certificates before 2015:

Conferences and Events
Presentations, Seminars & Posters
- 2015
  • School on Electronic Structure and Quantum Transport Methods, UNESP, ICTP, SP, Brazil, 2014.
  • V Winter School of Physics - UFBA, BA, Brazil, 2012.
  • Certificate in Thin Films Applied to Solar Energy.
  • Certificate in Study of Semiconductor Materials via DFT.
  • Certificate in Electron and ion accelerators.
  • Certificate in Molecular Orbital theory.
  • IV Winter School of Physics - UFBA, BA, Brazil, 2011.
  • Certificate in Topics in Field Theory.
  • Certificate in Solar energy.
  • Physics Summer School at Aeronautics Institute of Technology (ITA). Seminar: Study of Magnetic Properties in Paramagnetic Aggregates via Calculation of First Principles, ITA, SP, Brazil, 2011.
  • Winter School in Physics Applied to Medicine and Biology - USP, SP. 2011.
  • AMS/SBF First Joint Meeting - IMPA, RJ. 2008.
  • International Symposium of Dynamical Systems -. IMPA, RJ. 2006.
  • V Workshop on Molecular Physics and Spectroscopy - UFBA, BA. 2006.
  • XIV School of Differential Geometry - Honors to Shiing-Shen Chern (IMPA) - UFBA, BA. 2006.
Link

Industry & Non-Profit

Founder
Aicavity Analytics, Sweden
Mar 2022 - Present

Data-Driven Software Consulting

Aicavity Analytics
Head Manager
Stockholm AI (stockholm.ai)
Jan 2021 - Jan 2022

Non-profit Artificial Intelligence community in Stockholm.

Stockholm.ai
Research Engineer (Summer Intern)
Veoneer AB, Sweden
Jun 2019 - Aug 2019

Deep Neural Network Architectures and Markov Decision Processes for tracking multiple objects.

Recent Research Projects

Physics-based animation using Graph Neural Networks
Supervisor of Master Thesis, Linköping University
2021 - 2022
  • Applications of Graph Nets and Graph Neural Networks to simulate physical behavior of real particles and systems.
  • Examiner: Prof. Rickard Armiento
    Opponent: Linda Le
    Plats: Laplace, FysikHuset
  • Defended 29th of August
SUPERVISION OF MASTER THESIS
Projects Approved for Research Development
My Postdoc Fellowship is financed by Knut and Alice Wallenberg Foundation regarding the "2D Materials Frontiers". I have also written two projects entitled AI for Materials Discovery (2021-2022) and AI for Physics and Engineering: Modeling and Simulation (2022-2023) to develop my Research Activities and Applications.
2021 - 2023
  • Development of DL and Graph Neural Network Architectures for high-throughput design and discovery of new molecular and 2D-based Materials with applications in Energy devices & Catalysis. (2021-2022)
  • AI for Physics and Engineering: Modeling and Simulation (2022-2023)
Linköping university
AI & Decision-Making
  • Data-driven Analytics for Decision-Making in Geophysics. (Collaborations: CPRM, Petrobras, and GAIA UFBA - Brazil)
Aicavity Analytics

Computational Resources:

Tetralith, SNIC, Sweden
Projects Approved: 1. AI for Physics and Engineering: Modeling and Simulation (2022-2023); 2. AI for Materials Discovery
2021 - 2023
  • Tetralith consists of 1908 compute nodes each with two Intel Xeon Gold 6130 cpus with 16 CPU cores each, giving a total of 61056 CPU cores.
  • The performance of the complete system is around 3 Pflop/s (LINPACK Rmax).
LInk
Kebnekaise Cluster, Sweden
Projects Approved: 1. AI for Physics and Engineering: Modeling and Simulation (2022-2023); 2. AI for Materials Discovery
2021 -2023
  • 432 nodes with Intel Broadwell E5-2690v4, 2x14 cores, 128 GB/node
  • 20 nodes, 3TB/node, Intel Broadwell E7-8860v4, 4x18 cores
  • 32 nodes with 2x NVIDIA K80; 4 nodes with 4x NVIDIA K80; 128 GB/node 
  • 36 nodes, Intel Knights Landing; 7250 SKU (68 cores, 1.4 Ghz/1.2 Ghz/AVX), 192 GB/node.
  • 52 nodes with Intel Skylake Gold 6132 2x14 cores, 196 GB/node
  • 10 GPU Volta nodes with Intel Skylake Gold 6132 2x14 cores, 2xNvidia V100 (2x5120 CUDA, 2x640 Tensor), 192 GB/node
  • InfiniBand EDR/FDR interconnect
Link
Rackham Cluster, Uppsala University
Projects Approved: 1. AI for Physics and Engineering: Modeling and Simulation (2022-2023); 2. AI for Materials Discovery
2021 - 2022
  • Rackham comprises 9720 cores in the form of 486 nodes with two 10-core Intel Xeon V4 CPU's each. There are "fat" nodes,4 with 1TB memory and 32 with  256 GB memory, with the rest having 128 GB.
  • Rackham's storage system (named Crex) uses the Lustre file system and provides 6.6PB of storage.
  • The interconnect is Infiniband FDR which supports a theoretical bandwidth of 56Gb/s and a latency of 0.7 microseconds.
Link
C3SE Alvis, Chalmers University
Projects Approved: 1. AI for Physics and Engineering: Modeling and Simulation (2022-2023); 2. AI for Materials Discovery
2022 - 2023

Alvis cluster is a national SNIC resource dedicated for Artificial Intelligence and Machine Learning research.

Link

My Scientific Publications / Reviewer

Multi-Fractal Detrended Cross-Correlation Heatmaps for Time Series Analysis

Authors: Paulo Roberto, Kianny Lopes, Vitor Hugo Serravalle, Michell Thompson, Euler Bentes, J. Luis Silva

Journal: Scientific Reports

Publisher: Nature Publishing Group

Publication Date: Under Review

DOI: 10.21203/rs.3.rs-2172772/v1

Cite this: Under Review

Under Review
g-C3N4/WTe2 Hybrid Electrocatalyst for Efficient Hydrogen Evolution Reaction

Authors: J. Luis Silva et. al.

Journal: The Journal of Physical Chemistry C

Publisher: American Chemical Society

Publication Date: 30 March 2020

DOI: 10.1021/acs.jpcc.9b11982

Cite this: J. Phys. Chem. C 2020, 124, 16, 8726–8735

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X‑ray Photoelectron Fingerprints of High-Valence Ruthenium−Oxo Complexes along the Oxidation Reaction Pathway in an Aqueous Environment

Authors: J. Luis Silva et al.

Journal: The Journal of Physical Chemistry Letters

Publisher: American Chemical Society

Publication Date: 20 November 2019

DOI:10.1021/acs.jpclett.9b02756

Cite this: J. Phys. Chem. Lett. 2019, 10, 7636−7643

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Unveiling the Interfacial Effects for Enhanced Hydrogen Evolution Reaction on MoS2/WTe2 Hybrid Structures

Authors: Yu Zhou, Joshua V. Pondick, J. Luis Silva et al.

Journal: Small

Publication Date: 08 April 2019

DOI:10.1002/smll.201900078

Cite this: Small 2019, 15, 1900078

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Spectroscopic Fingerprints of Intermolecular H-Bonding Interactions in Carbon Nitride Model Compounds

Authors: Dr. Valeria Lanzilotto, J. Luis Silva et al.

Journal: Chemistry - A European Journal

Publication Date: 15 July 2018

DOI:10.1002/chem.201802435

Cite this: Chem. Eur. J. 2018, 24, 14198

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Hydrated Electron Generation by Excitation of Copper Localized Surface Plasmon Resonance

Authors: Mariia V. Pavliuk, Sol Gutiérrez Álvarez, Yocefu Hattori, Maria E. Messing, Joanna Czapla-Masztafiak, Jakub Szlachetko, J. Luis Silva et al.

Journal: The Journal of Physical Chemistry Letters

Publication Date: 28 March 2019

DOI:10.1021/acs.jpclett.9b00792

Cite this: J. Phys. Chem. Lett. 2019, 10, 8, 1743–1749

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Revealing the Contribution of Individual Factors to Hydrogen Evolution Reaction Catalytic Activity

Authors: Yu Zhou, J. Luis Silva et. al.

Journal: Advanced Materials

Publication Date: 24 March 2018

DOI: 10.1002/adma.201706076

Cite this: Adv. Mater. 2018, 30, 1706076

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Peer Reviewer

Journal: Vacuum

Publisher: Elsevier

Date: September 2021

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Introduction to Cyber Attacks
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Nov 14, 2022
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Optimize ML Models and Deploy Human-in-the-Loop Pipelines
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Analyze Datasets and Train ML Models using AutoML
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Build, Train and Deploy ML Pipelines using BERT
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AI for Trading Nanodegree
Udacity, Inc. & World Quant Asset Management - Credential ID: KZ9E4ZVH
November 3, 2021
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Deep Learning Specialization
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January 29, 2021
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Natural Language Processing Specialization
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October 2021
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Natural Language Processing with Attention Models
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Natural Language Processing with Classification and Vector Spaces
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Natural Language Processing with Probabilistic Models
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Neural Networks and Deep Learning
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October 27, 2020
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Structuring Machine Learning Projects
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Sequence Models
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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
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Convolutional Neural Networks
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Practical Data Science on the AWS Cloud
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Introduction to Software Product Management
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Software Processes and Agile Practices
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Fundamentals of Reinforcement Learning
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February 9, 2021
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Sample-based Learning Methods
Coursera, University of Alberta - Credential ID: GQB568NJ8L7D
February 24, 2021
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Introduction to Data Science
Uppsala University, Combient, SEB, and Databricks
Fall 2017, 81 hours
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Fundamentals and Applications of Heterogeneous Catalysis
SUNCAT Summer Institute, Stanford University, CA, USA
2017

Poster: Nanodevices as micro-reactors for studying electrocatalytic hydrogen evolution reaction

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Certification in Introduction to High Performance Computing, PDC Summer School.
Royal Institute of Technology, KTH, Sweden
July 2016
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Summer/Winter Schools: KTH High Performance Computing Summer School, Aeronautics Institute of Technology, USP Medical Physics, IMPA etc.
Before 2017
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