Jose Luis Silva, Ph.D.

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Jose Luis Silva, Ph.D.
Researcher in AI at LiU
Founder Aicavity Analytics
Head Manager at Stockholm AI
  • Researcher in AI:
    LiU 🇸🇪
  • Founder:
    Aicavity Analytics 🇸🇪
  • Born:
    Brazil 🇧🇷
  • Life:
    Sweden 🇸🇪
Research Interests:
  • Artificial Intelligence & Machine Learning
  • Graphs, Computer Vision & NLP
  • Deep Learning & Reinforcement Learning
  • Autonomous Systems & Decision Making
  • Multiscale Simulations & Materials Science
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AI, Machine Learning, Data Science
& Analytics, and Decision-Making.

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20 ML
ML
04 DL
Deep Learning
04 AI
AI
00 RL
RL & DRL
10 OP
MLOps
00 DS
DSaaS
00 GN
Graphs
00 CP
CodingPuzzles

My GitCode Repositories (24)

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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More GitCode
I’m Jose Luis Silva, Physicist, Ph.D., and Entrepreneur. I have deep interest in Data-Driven Decision-Making, AI, Modeling & Simulation. I hold a Ph.D. in Physics from Uppsala University, where I have worked with the Design of Materials for Energy Applications. I have published articles in Advanced Materials (IF: 30.849), Small (IF: 13.281 ), The Journal of Physical Chemistry Letters (IF: 6.213), and JPCC (IF: 4.536), The Journal of Physical Chemistry C, and European Journal. Currently, I am a Postdoctoral Researcher in Artificial Intelligence at Linköping University, Sweden, and Member of the Advisory Board at the Junior Faculty Steering Committee (LiU). I have also Founded Aicavity Analytics Consulting, and additionally, I am Head Manager at Stockholm AI, a non-profit organization with AI enthusiasts, professionals, and researchers aiming to establish Stockholm as a global player in AI. I’m also a reviewer for the Journal Vacuum IF: 3.67 (Elsevier) and Sensors (MDPI) covering AI, Materials Science & Machine Learning.

About Me:

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
Jan 2022 - Present
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)

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
Mar 2022 - Present

Data-Driven Software Consulting

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

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

AI for Materials Discovery
My Postdoc Fellowship is financed by Knut and Alice Wallenberg Foundation regarding the "2D Materials Frontiers" project. I have also written and was granted with a small-scale project entitled AI for Materials Discovery.
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.
  • Graph-Nets, Machine Learning and DL-based approaches for tracking possible switching mechanisms of molecular complexes with applications  in Neuromorphic Computing.
  • Discovering new Organo-Metallic coordinated Complexes for efficient Artificial Photosynthesis. Here I use GANs and SMILES to generate a Database. The DL Architectures are being used to track the pKA and reaction-based descriptors that can contribute to the prediction of efficient systems for Hydrogen Production. (Inspired by my Ph.D. Thesis)
Linköping university
AI for Real Simulations
Linköping University
2021 - 2022
  • Applications of Graph Nets and Graph Neural Networks to simulate physical behavior of real particles and systems.
SUPERVISION OF MASTER THESIS
AI & Decision-Making
  • Data-driven Analytics for Decision-Making in Geophysics. (Collaborations: CPRM, Petrobras, and GETA UFBA - Brazil)
Aicavity Analytics

Computational Resources:

Tetralith, SNIC, Sweden
Project Approved: AI for Materials Discovery
2021 - 2022
  • 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
Project Approved: AI for Materials Discovery
2021 -2022
  • 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

Computational Resources:

Rackham Cluster, Uppsala University
Project Approved: 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

Scientific Publications / Reviewer

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

Authors: J. Luis Silva et. al.

Journal: The Journal of Physical Chemistry C

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

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

Certificate

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Optimize ML Models and Deploy Human-in-the-Loop Pipelines
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Build, Train and Deploy ML Pipelines using BERT
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Natural Language Processing Specialization
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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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Neural Networks and Deep Learning
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Structuring Machine Learning Projects
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Sequence Models
Coursera, DeepLearning.AI - Credential ID: XZMQDXUKU9Y6
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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
Coursera, University of Alberta - Credential ID: M58UN4QTX798
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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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Older Certificates
Summer/Winter Schools: KTH High Performance Computing Summer School, Aeronautics Institute of Technology, USP Medical Physics, IMPA etc.
Before 2017
SEE CREDENTIAL

Social Media: Twitter/LinkedIn.

Jose Luis Silva Follow 20 200

Founder @AicavityTech | Researcher in AI @LiU_Universitet | Head Manager @SthlmAi. No Investment Advice. Neutral Zone. My Own Opinions.

jseluisX
jseluisX avatar; Jose Luis Silva @jseluisX ·
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About Me & my Research: https://jseluis.com

Visit http://Aicavity.com for Insights from Data and request early access to Aicavity Academy, Jose's Laboratory.

Check Aicavity Hub -> http://hub.aicavity.com for our released Discourse Platform.

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