In this repo, you will find some of the publications that I have done during my career.
NOTE: This document is automatically generated. I use pandoc to convert the publications from bibtex format to markdown. To see how I do it, take a look at this guide.
More information about my scientific career can be found on my personal page at RoboticsLab research group from Universidad Carlos III de Madrid and ThrishLab research group from King's College London (now at Imperial College).
[1] M. González-Fierro, "Recommenders: Best practices in recommendation systems for gaming", XGS Data & Applied Sciences Summit, 2024.
[2] M. González-Fierro, "Exploring Uses of AI in Gaming", Magneto6 Conference, Redmond, US, 2024.
[3] M. González-Fierro, "Transitioning to a Meaningful Artificial Intelligence Career", AI & ML Community Call, Redmond, US, 2023.
[4] M. González-Fierro, "Tech Entrepreneurship", TechIE Conference, 2023.
[5] M. González-Fierro, "How to Start a Career in Data Science", Sci-Tech Day, European University, 2023.
[6] M. González-Fierro, "Applying Graph Neural Networks to Recommendation Systems", Madrid Machine Learning Meetup, 2023.
[7] F. Zamanian, S. Zhao, P. V. Joshi, D. Anand, M. González-Fierro, S. Antharam, J. Kucera, and L. McGlinn, "How AI can help billions of PlayFab users and game developers to know and retain their players", Machine Learning and Data Science Conference (MLADS) Fall Redmond, 2022.
[8] M. González-Fierro, "Switching Your Career to Data Science", Machine Learning and Data Science Conference (MLADS) Fall Redmond, 2022.
[9] P. V. Joshi, A. Argyriou, and M. González-Fierro, "Implementing a Parallel MLOps Test Pipeline for Open Source Development", MLOps World: Machine Learning in Production, 2022.
[10] P. V. Joshi and M. González-Fierro, "Implementing an Efficient Testing Pipelines for GitHub Repositories with Azure Machine Learning", Microsoft AI and ML Community Call, Redmond, US, 2022.
[11] M. González-Fierro, "Becoming a T-shaped Data Scientist in Recommendation Systems", Universidad de Navarra, 2022.
[12] M. González-Fierro, "How to Create Recommendation Systems with the Help of the Recommenders Open-source Repository", Deeplearning.ai Meetup Amsterdam, 2022. Available online: https://www.eventbrite.com/e/pie-ai-amsterdam-building-recommenders-open-source-repository-tickets-332757866737
[13] M. González-Fierro, "Transitioning to a Data Science Career", AI & ML Community Call, Microsoft UK, 2022.
[14] M. González-Fierro, "Overcoming the challenges to make Artificial Intelligence omnipresent", Summer School CEA (Spanish Commission of Automation), 2021.
[15] M. González-Fierro, "Current Challenges in Artificial Intelligence: Artificial Intelligence in the Industry (in Spanish)", IEEE Spain & CEA (Spanish Commission of Automation), 2021.
[16] M. González-Fierro, "The challenges of artificial intelligence in today’s society (in Spanish)", Universidad Libre de Infantes, Santo Tomás de Villanueva, 2021. Available online: https://www.slideshare.net/MiguelFierro1/los-retos-de-la-inteligencia-artificial-en-la-sociedad-actual
[17] S. Bleik, M. González-Fierro, H. Lu, D. Deng, Y. Chen, H. Spetalnick, T. Wu, and S. Chikkerur, "A Hitchhikers guide to using Transformers for multiple scenarios and languages", AACL-IJCNLP 2020: The 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020. Available online: http://aacl2020.org/program/tutorials/#t5-a-hitchhikers-guide-to-using-transformers-for-multiple-scenarios-and-languages
[18] M. González-Fierro, "Knowledge Graph Recommendation Systems For COVID-19", Toronto Machine Learning Summit, 2020. Available online: https://www2.slideshare.net/MiguelFierro1/knowledge-graph-recommendation-systems-for-covid19
[19] L. Zhang, Z. Shen, J. Lian, C. Wu, M. González-Fierro, A. Argyriou, and T. Wu, "In Search for A Cure: Recommendation with Knowledge Graph on CORD-19", ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2020 (KDD 2020), 2020. Available online: https://dl.acm.org/doi/10.1145/3394486.3406711
[20] A. Argyriou, M. González-Fierro, and L. Zhang, "Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems", WWW 2020: International World Wide Web Conference Taipei, 2020. Available online: https://dl.acm.org/doi/abs/10.1145/3366424.3382692
[21] M. González-Fierro and A. Argyriou, "Taking Recommendation Systems to The Masses", Open Data Science Conference ODSC London 2019, 2019.
[22] S. Bleik, Y. Chen, E. Awa, M. González-Fierro, and D. Deng, "Deep Learning for Natural Language Processing: From 0 to 100", Machine Learning and Data Science Conference (MLADS) Fall Redmond 2019, 2019.
[23] L. Shao, H. Lu, A. Eswaran, and M. González-Fierro, "Distributed Training of BERT and XLNet Models for Question Answering Using Azure Machine Learning", Machine Learning and Data Science Conference (MLADS) Fall Redmond 2019, 2019.
[24] D. Deng, S. Bleik, E. Awa, J. S. Mathew, and M. González-Fierro, "AI Transformers for State of the Art NLP", Machine Learning and Data Science Conference (MLADS) Fall Redmond 2019, 2019.
[25] M. González-Fierro, J. K. Min, C. Pirillo, and A. Umamahesan, "Accelerating recommendation system development with Azure Machine Learning", Microsoft Ignite Conference 2019 Florida, Orlando, 2019.
[26] L. Zhang, T. Wu, X. Xie, A. Argyriou, M. González-Fierro, and J. Lian, "Building Production-Ready Recommendation System at Scale", ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2019 (KDD 2019), 2019. Available online: https://www.kdd.org/kdd2019/hands-on-tutorials
[27] T. Wu, M. González-Fierro, L. Zhang, and N. Joglekar, "Train and operationalize recommender systems on Azure", Machine Learning and Data Science Conference (MLADS) Sprint Redmond 2019, 2019.
[28] M. González-Fierro, "Overcoming Machine Learning Bias through Model Analysis", Data Leadership Summit Conference, 2019. Available online: https://www.slideshare.net/MiguelFierro1/overcoming-machine-learning-bias-through-model-analysis
[29] L. Zhang, G. Williams, T. Wu, M. González-Fierro, and N. Joglekar, "Building and Evaluating a Production-ready Recommendation System", Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) Macau China 2019, 2019.
[30] T. Wu, M. González-Fierro, L. Zhang, and N. Joglekar, "Best Practices for Recommender Systems", Machine Learning and Data Science Conference (MLADS) Fall Redmond 2018, 2018.
[31] N. Joglekar, M. Cozowicz, L. Zhang, A. Argyriou, T. Wu, and M. González-Fierro, "Building and Evaluating a Scalable Recommendation System", Machine Learning and Data Science Conference (MLADS) Fall Redmond 2018, 2018.
[32] G. Iordanescu and M. González-Fierro, "Using Transfer Learning as a Powerful Baseline for Deep Learning", Deep Learning World Berlin 2018, 2018.
[33] M. González-Fierro, D. Dean, M. Salvaris, and I. Karmanov, "Microsoft AI Transformation", 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), 2018.
[34] M. Salvaris, I. Karmanov, and M. González-Fierro, "Distributed Training on Multi-Node Multi-GPU of Deep Neural Networks", Open Data Science Conference ODSC London 2018, 2018. Available online: https://www.slideshare.net/secret/2t5zCccvMndEui
[35] G. Iordanescu and M. González-Fierro, "Using Transfer Learning as a Powerful Baseline for Deep Learning", Predictive Analytics World London 2018, 2018.
[36] M. González-Fierro and A. Taylor, "Spark Made Simple with AZTK", Brisbane UseR! 2018, 2018.
[37] M. Salvaris, I. Karmanov, and M. González-Fierro, "Training Distributed Deep Learning Models", Machine Learning and Data Science Conference (MLADS) Spring Redmond 2018, 2018.
[38] M. Salvaris, I. Karmanov, and M. González-Fierro, "Distributed Training of Deep Learning Models", Strata Data Conference London, 2018. Available online: https://www.slideshare.net/MiguelFierro1/distributed-training-of-deep-learning-models
[39] Y. Xing, M. González-Fierro, P. Xia, and T. Wu, "Transfer Learning and Fine Tuning of Pre-trained DNN Models on Kaggle Airport Passenger Screening Challenge", The Thirty-First Annual Conference on Neural Information Processing Systems NIPS 2017, 2017.
[40] M. González-Fierro, "Running Intelligent Applications inside a Database: Deep Learning with Python Stored Procedures in SQL", Open Data Science Conference ODSC London 2017, 2017. Available online: https://www.slideshare.net/MiguelFierro1/running-intelligent-applications-inside-a-database-deep-learning-with-python-stored-procedures-in-sql
[41] Y. Xing, M. González-Fierro, P. Xia, and T. Wu, "Transfer Learning and Fine Tuning of Pre-trained DNN Models on Kaggle Airport Passenger Screening Challenge Using Azure Machine Learning Workbench", Machine Learning and Data Science Conference (MLADS) Redmond 2017, 2017.
[42] M. González-Fierro, "Deep Learning for Sales Professionals", Intelligent Cloud GBB Ready Lisbon, 2017. Available online: https://www.slideshare.net/MiguelFierro1/deep-learning-for-sales-professionals
[43] A. Taylor and M. González-Fierro, "Deep Learning for Natural Language Processing in R", Brussels UseR! 2017, 2017.
[44] M. González-Fierro, "Mastering Computer Vision Problems with State-of-the-art Deep Learning", Strata Data Conference London, 2017. Available online: https://www.slideshare.net/MiguelFierro1/mastering-computer-vision-problems-with-stateoftheart-deep-learning
[45] M. Salvaris and M. González-Fierro, "Speeding up Machine Learning Applications with the LightGBM Library", Strata Data Conference London, 2017. Available online: https://www.slideshare.net/MiguelFierro1/speeding-up-machinelearning-applications-with-the-lightgbm-library
[46] M. González-Fierro, "Deep Learning for Lung Cancer Detection", AI Immersion Workshop. Microsoft Build Conference 2017, 2017. Available online: https://www.slideshare.net/MiguelFierro1/deep-learning-for-lung-cancer-detection
[47] M. González-Fierro, Y. Xing, and T. Wu, "Getting Started on a Lung Cancer Detection Competition in One Hour Using Cognitive Toolkit and DSVM", The Data Platform Show, 2017.
[48] M. González-Fierro and D. Dean, "Democratizing Intelligence in the World of Predictive, Cognitive and Advanced Analytics", Data 360 - A Virtual Summit on Data. Data Digital Event Bangalore, 2016.
[49] M. González-Fierro, M. Kaznady, and A. Argyriou, "Implementing Large Scale Image Classification with Deep Learning on the Azure Cloud, Microsoft R Server and Spark", Machine Learning and Data Science Conference (MLADS) Redmond 2016, 2016.
[50] T. Delteil and M. González-Fierro, "Deep Learning for Natural Language Processing", Open Data Science Conference ODSC London 2016, 2016. Available online: https://www.slideshare.net/MiguelFierro1/deep-learning-for-nlp-67182819
[51] M. González-Fierro, "Leveraging Deep Learning for Applications", Machine Learning and Data Science Conference (MLADS) Bangalore 2016, 2016.
[52] M. González-Fierro, C. A. Monje, and C. Balaguer, "Robust Control of a Reduced Humanoid Robot Model using Genetic Algorithms and Fractional Calculus", Mathematical Methods in Engineering International Conference MME2013, 2013, pp. 183-194. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2013robust.pdf
[53] M. González-Fierro, M. A. Maldonado, J. G. Víctores, S. Morante, and C. Balaguer, "Object Tagging for Human-Robot Interaction by Recolorization using Gaussian Mixture Models", Proceedings of Robocity2030 12th Workshop: Robótica Cognitiva, 2013, pp. 67-76. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2013object.pdf
[54] M. González-Fierro, C. Balaguer, N. Swann, and T. Nanayakkara, "A Humanoid Robot Standing Up Through Learning from Demonstration Using a Multimodal Reward Function", IEEE-RAS International Conference on Humanoid Robots, 2013. Humanoids 2013, 2013, pp. 74-79. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2013humanoid.pdf
[55] M. González-Fierro, C. Monje, V. González, and C. Balaguer, "Evolutionary Fractional Order Control of a Humanoid Robot Modeled as a Triple Inverted Pendulum", Proceedings of Robocity2030 11th Workshop: Robots Sociales, 2013, pp. 245-263. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2013evolutionary.pdf
[56] M. González-Fierro, J. Bueno, C. Balaguer, and L. Moreno, "A Complete 3D Perception and Path Planning Architecture for a Humanoid", Proceedings of Robocity2030 11th Workshop: Robots Sociales, 2013, pp. 167-184. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2013complete.pdf
[57] J. Bueno, A. Martín, M. González-Fierro, L. Moreno, and C. Balaguer, "Distinguishing between Similar Objects based on Geometrical Features in 3D Perception", Proceedings of Robocity2030 12th Workshop: Robótica Cognitiva, 2013, pp. 77-92. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/bueno2013distinguishing.pdf
[58] M. González-Fierro, D. Hernández, P. Pierro, and C. Balaguer, "Dynamic Modelling of Humanoid Robots Using Spatial Algebra", XXXIII Jornadas de Automática, 2012. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2012dynamic.pdf
[59] J. G. Víctores, S. Morante, M. González-Fierro, and C. Balaguer, "Augmented Reality and Social Interaction platform through Multirobot Design", Proceedings of Robocity2030 11th Workshop: Robots Sociales, 2013, pp. 131-143. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/victores2013augmented.pdf
[60] D. Herrero, P. Pierro, M. González-Fierro, D. Hernández, and C. Balaguer, "Perception System for Working with Humanoid Robots in Unstructured Collaborative Scenarios", Proceedings of the 2012 International IEEE Intelligent Vehicles Symposium. Workshops V Perception in Robotics, 2012.
[61] J. G. Bueno, M. González-Fierro, L. Moreno, and C. Balaguer, "Facial Gesture Recognition using Active Appearance Models based on Neural Evolution", 2012 International Conference on Human-Robot Interaction (HRI 2012), 2012, pp. 133-134. Available online: http://doi.acm.org/10.1145/2157689.2157721
[62] C. A. Monje, P. Pierro, T. Ramos, M. González-Fierro, and C. Balaguer, "Modeling and Simulation of the Humanoid Robot HOAP-3 in the OpenHRP3 Platform", Proceedings of Robot 2011. Workshop Robots Humanoides, 2011. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/monje2011modeling.pdf
[63] J. G. Bueno, M. González-Fierro, L. Moreno, and C. Balaguer, "Facial Gesture Recognition and Postural Interaction using Neural Evolution Algorithm and Active Appearance Models", Proceedings of Robocity2030 9th Workshop: Robots Colaborativos e Interacción Humano-Robot, 2011, pp. 145-159. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/bueno2011facial.pdf
[64] M. González-Fierro, A. Jardón, S. Martínez de la Casa, M. F. Stoelen, J. G. Víctores, and C. Balaguer, "Educational Initiatives Related with the CEABOT Contest", Proceedings of SIMPAR, 2010, pp. 649-658. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2010educational.pdf
[65] A. Peña, D. Hernández, M. González-Fierro, P. Pierro, and C. Balaguer, "Sistema de Visión del Humanoide HOAP-3 para la Detección e Identificación de Objetos Mediante Librerías OpenCV", Proceedings of Robocity2030 7th Workshop: Vision en Robótica, 2010. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/pena2010sistema.pdf
[66] A. P. Mateo, M. González-Fierro, D. Hernández, P. Pierro, and C. Balaguer, "Robust Real Time Stabilization: Estabilización de la Imagen con Aplicación en el Robot Humanoide HOAP-3", Proceedings of Robocity2030 7th Workshop: Vision en Robótica, 2010. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/mateo2010robust.pdf
[67] M. González-Fierro, P. Pierro, A. Jardón, D. Herrero, and C. Balaguer, "Realización de Tareas Colaborativas entre Robots Humanoides. Experimentación con Dos Robots Robonova", Proceedings of Robocity2030 5th Workshop: Cooperación en Robótica, 2009. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2009realizacion.pdf
[68] P. Pierro, D. Hernández, M. González-Fierro, L. Blasi, A. Milani, and C. Balaguer, "A Human-Humanoid Interface for Collaborative Tasks", Proceedings on the Second Workshop for Young Researchers on Human-Friendly Robotics, 2009. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/pierro2009human.pdf
[69] P. Pierro, D. Hernández, M. González-Fierro, L. Blasi, A. Milani, and C. Balaguer, "Humanoid Teleoperation System for Space Environments", Advanced Robotics, 2009. ICAR 2009. International Conference on, 2009, pp. 1-6. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/pierro2009humanoid.pdf
[70] P. Pierro, M. González-Fierro, and C. Balaguer, "El Proyecto Europeo ROBOT@CWE: Advanced Robotic Systems in Future Collaborative Working Environments", II Workshop de Robótica (ROBOT 2009), 2009.
[1] M. González-Fierro, C. Monje, and C. Balaguer, "Fractional Control of a Humanoid Robot Reduced Model with Model Disturbances", Journal of Cybernetics and Systems, vol. 47, n.º 6, pp. 445-459, 2016. Available online: http://www.tandfonline.com/doi/abs/10.1080/01969722.2016.1187031
[2] M. González-Fierro, D. Hernández, T. Nanayakkara, and C. Balaguer, "Behavior Sequencing Based on Demonstrations - a Case of a Humanoid Opening a Door While Walking", Advanced Robotics, vol. 29, n.º 5, pp. 315-329, 2015. Available online: http://dx.doi.org/10.1080/01691864.2014.992955
[3] M. González-Fierro, C. Balaguer, N. Swann, and T. Nanayakkara, "Full-Body Postural Control of a Humanoid Robot with Both Imitation Learning and Skill Innovation", International Journal of Humanoid Robotics, vol. 11, n.º 2, p. 1450012, 2014. Available online: http://dx.doi.org/10.1142/S0219843614500121
[4] J. G. Bueno, M. González-Fierro, L. Moreno, and C. Balaguer, "Facial Emotion Recognition and Adaptative Postural Reaction by a Humanoid based on Neural Evolution", International Journal of Advanced Computer Science, vol. 3, n.º 10, pp. 481-493, 2013. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/bueno2013facial.pdf
[5] C. A. Monje, P. Pierro, T. Ramos, M. González-Fierro, and C. Balaguer, "Modeling and Simulation of the Humanoid Robot HOAP-3 in the OpenHRP3 Platform", Cybernetics and Systems, vol. 44, n.º 8, pp. 663-680, 2013. Available online: http://dx.doi.org/10.1080/01969722.2013.832095
[1] M. González-Fierro, "Humanoid Robot Control of Complex Postural Tasks Based on Learning From Demonstrations", Ph.D. Thesis, Universidad Carlos III de Madrid, 2014. Available online: https://github.com/miguelgfierro/publications/blob/main/docs/gonzalez-fierro2014thesis.pdf
[2] M. González-Fierro, "Dynamic Modeling of Humanoid Robots through Spatial Algebra (in Spanish)", Master’s Thesis, Universidad Carlos III de Madrid, 2009. Available online: https://github.com/miguelgfierro/publications/blob/main/gonzalez-fierro2009master.pdf
[3] M. González-Fierro, "Execution of Collaborative Tasks on Robonova using FSRs (in Spanish)", Master’s Thesis, Universidad Carlos III de Madrid, 2008.
[1] M. González-Fierro, "ssm library - Image recognition and similarity for the fashion industry: M-008319/2014", 2014.
[1] I. Karmanov and M. González-Fierro, "Recurrent Neural Networks", in Deep Learning with Azure, M. Salvaris, D. Dean, and W. H. Tok, Eds. Apress, 2018, pp. 161-186.
I have my personal blog where I write about artificial intelligence, machine learning, technical business and other random stuff that comes to my mind. The blog has been designed to mimic the appearance of a scientific paper. I did it that way to honor my scientific background. The code is open-sourced and can be found in this repo.
In addition, some of the posts have code supporting the articles. The code is available in this repo.
Here there is the list of posts published on my blog and other blogs:
[1] M. González-Fierro, "Reverse Learning: How To Learn The AI Used Today In The Industry". 2023. Available online: https://miguelgfierro.com/blog/2023/reverse-learning-how-to-learn-the-ai-used-today-in-the-industry/
[2] M. González-Fierro, "From Cloud Solution Architect To Data Scientist In 4 Months". 2023. Available online: https://miguelgfierro.com/blog/2023/from-cloud-solution-architect-to-data-scientist-in-4-months/
[3] M. González-Fierro, "The Story Of How Nikolaos Got A Data Science Job In Just 3 Months". 2023. Available online: https://miguelgfierro.com/blog/2023/the-story-of-how-nikolaos-got-a-data-science-job-in-just-3-months/
[4] M. González-Fierro, "My Most Popular LinkedIn Posts Of 2022". 2023. Available online: https://miguelgfierro.com/blog/2023/my-most-popular-linkedin-posts-of-2022/
[5] M. González-Fierro, "Discover My Day To Day At Microsoft - Doing A Data Science Project". 2022. Available online: https://miguelgfierro.com/blog/2022/discover-my-day-to-day-at-microsoft-doing-a-data-science-project/
[6] M. González-Fierro, "An Analysis Of The Adoption Of Top Deep Learning Frameworks". 2022. Available online: https://miguelgfierro.com/blog/2022/an-analysis-of-the-adoption-of-top-deep-learning-frameworks/
[7] M. González-Fierro, "My Most Popular LinkedIn Posts Of 2021". 2022. Available online: https://miguelgfierro.com/blog/2022/my-most-popular-linkedin-posts-of-2021/
[8] M. González-Fierro, "A Gentle Introduction To Distributed Training With DeepSpeed". 2022. Available online: https://miguelgfierro.com/blog/2022/a-gentle-introduction-to-distributed-training-with-deepspeed/
[9] M. González-Fierro, "A Gentle Introduction To Matrix Factorization For Recommendations". 2021. Available online: https://miguelgfierro.com/blog/2021/a-gentle-introduction-to-matrix-factorization-for-recommendations/
[10] M. González-Fierro, J. Kahnfeld, L. Zhang, and T. Wu, "AI for Retail: Recommendation". 2021. Available online: https://www.linkedin.com/pulse/ai-retail-recommendation-markus-cozowicz
[11] M. González-Fierro, "Understanding The New Project Of Elon Musk, The Tesla Bot". 2021. Available online: https://miguelgfierro.com/blog/2021/understanding-the-new-project-of-elon-musk-the-tesla-bot/
[12] M. González-Fierro, "A Gentle Introduction To Fourier Transformers For NLP". 2021. Available online: https://miguelgfierro.com/blog/2021/a-gentle-introduction-to-fourier-transformers-for-nlp/
[13] A. Meyster and M. González-Fierro, "Three Unique Ways To Source Top Tech Talent". 2021. Available online: https://miguelgfierro.com/blog/2021/three-unique-ways-to-source-top-tech-talent/
[14] M. González-Fierro, "My Personal Quest To Become The Best Version Of Myself". 2021. Available online: https://miguelgfierro.com/blog/2021/my-personal-quest-to-become-the-best-version-of-myself
[15] M. González-Fierro, "Book Review: Influence By Robert Cialdini". 2021. Available online: https://miguelgfierro.com/blog/2021/book-review-influence-by-robert-cialdini/
[16] A. Meyster and M. González-Fierro, "Technology Is Reducing The Cost Of Education". 2021. Available online: https://miguelgfierro.com/blog/2021/technology-is-reducing-the-cost-of-education/
[17] M. González-Fierro, "10 Reasons Why AI Has Developed Faster Than Robotics". 2020. Available online: https://miguelgfierro.com/blog/2020/10-reasons-why-ai-has-developed-faster-than-robotics/
[18] F. Wu, J. Yi, Y. Lei, Y. Qiao, L. Zhang, and M. González-Fierro, "A Step-by-Step Guide to the Microsoft News Recommendation Competition". 2020. Available online: https://towardsdatascience.com/a-step-by-step-guide-to-the-microsoft-news-recommendation-competition-700ab00831a
[19] M. Cozowicz and M. González-Fierro, "A Gentle Introduction to Contextual Bandits". 2020. Available online: https://miguelgfierro.com/blog/2020/a-gentle-introduction-to-contextual-bandits
[20] D. Estévez, J. Isabel, V. G. Pacheco, J. G. Víctores, and M. González-Fierro, "ASROB 10th Anniversary". 2019. Available online: https://miguelgfierro.com/blog/2019/asrob-10th-anniversary/
[21] M. González-Fierro, "Understanding the Sequential Recommender SLi-Rec". 2019. Available online: https://miguelgfierro.com/blog/2019/understanding-the-sequential-recommender-sli-rec/
[22] M. González-Fierro, "Understanding XLNet and its Implications for NLP". 2019. Available online: https://miguelgfierro.com/blog/2019/understanding-xlnet-and-its-implications-for-nlp/
[23] M. González-Fierro, "Revisiting the Revisit of the Unreasonable Effectiveness of Data". 2019. Available online: https://miguelgfierro.com/blog/2019/revisiting-the-revisit-of-the-unreasonable-effectiveness-of-data/
[24] S. Graham, L. Zhan, A. Argyriou, and M. González-Fierro, "Scalable personalization on Azure". 2019. Available online: https://docs.microsoft.com/en-us/azure/architecture/example-scenario/ai/scalable-personalization
[25] H. Spetalnick, L. Zhan, A. Argyriou, N. Joglekar, J. Min, S. Graham, J. Reynolds, T. Wu, and M. González-Fierro, "Building recommender systems with Azure Machine Learning service". 2019. Available online: https://azure.microsoft.com/en-us/blog/building-recommender-systems-with-azure-machine-learning-service/
[26] I. Karmanov and M. González-Fierro, "Cloud-Scale Text Classification With Convolutional Neural Networks". 2019. Available online: https://miguelgfierro.com/blog/2019/cloud-scale-text-classification-with-convolutional-neural-networks/
[27] N. Joglekar, J. K. Min, S. Graham, L. Zhan, and M. González-Fierro, "Movie Recommendations on Azure". 2019. Available online: https://docs.microsoft.com/en-us/azure/architecture/example-scenario/ai/movie-recommendations
[28] J. K. Min, N. Joglekar, S. Graham, L. Zhan, J. Reynolds, and M. González-Fierro, "Build a Real-Time Recommendation API on Azure". 2018. Available online: https://docs.microsoft.com/en-us/azure/architecture/reference-architectures/ai/real-time-recommendation
[29] M. González-Fierro, "Top 35 AI Solutions for Today’s Key Industries". 2018. Available online: https://miguelgfierro.com/blog/2018/top-35-ai-solutions-for-todays-key-industries/
[30] M. González-Fierro, "A Gentle Explanation Of Dimensionality Reduction With T-SNE". 2018. Available online: https://miguelgfierro.com/blog/2018/a-gentle-explanation-of-dimensionality-reduction-with-t-sne/
[31] N. Joglekar and M. González-Fierro, "Evidence-Based Software Design". 2018. Available online: https://miguelgfierro.com/blog/2018/evidence-based-software-design/
[32] M. González-Fierro, "Python Pro Tips: Understanding Explicit Is Better Than Implicit". 2018. Available online: https://miguelgfierro.com/blog/2018/python-pro-tips-understanding-explicit-is-better-than-implicit
[33] M. González-Fierro, "Real-Time Fraud Detection". 2018. Available online: https://miguelgfierro.com/blog/2018/real-time-fraud-detection/
[34] M. González-Fierro, "A Beginner’s Guide To Python Testing". 2018. Available online: https://miguelgfierro.com/blog/2018/a-beginners-guide-to-python-testing/
[35] M. González-Fierro, "Demystifying WebSockets For Real-Time Web Communication". 2018. Available online: https://miguelgfierro.com/blog/2018/demystifying-websockets-for-real-time-web-communication/
[36] M. González-Fierro, "Top Mistakes And Learnings From My Startup: Postmortem Samsamia". 2018. Available online: https://miguelgfierro.com/blog/2018/top-mistakes-and-learnings-from-my-startup-postmortem-samsamia/
[37] M. González-Fierro, "10 Ethical Issues Of Artificial Intelligence And Robotics". 2018. Available online: https://miguelgfierro.com/blog/2018/10-ethical-issues-of-artificial-intelligence-and-robotics/
[38] I. Karmanov, M. Salvaris, M. González-Fierro, and D. Dean, "Comparing Deep Learning Frameworks: A Rosetta Stone Approach". 2018. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/comparing-deep-learning-frameworks-a-rosetta-stone-approach
[39] M. González-Fierro, "Stock Price Prediction With LSTMs". 2018. Available online: https://miguelgfierro.com/blog/2018/stock-price-prediction-with-lstms/
[40] M. González-Fierro, "Introduction To Recommendation Systems With Deep Autoencoders". 2018. Available online: https://miguelgfierro.com/blog/2018/introduction-to-recommendation-systems-with-deep-autoencoders/
[41] M. González-Fierro, "A Gentle Introduction To Transfer Learning For Image Classification". 2017. Available online: https://miguelgfierro.com/blog/2017/a-gentle-introduction-to-transfer-learning-for-image-classification/
[42] M. González-Fierro, M. Salvaris, G. Ke, and T. Wu, "Lessons Learned From Benchmarking Fast Machine Learning Algorithms". 2017. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/lessons-learned-benchmarking-fast-machine-learning-algorithms
[43] M. González-Fierro, "Deep Learning For Entrepreneurs". 2017. Available online: https://miguelgfierro.com/blog/2017/deep-learning-for-entrepreneurs/
[44] M. González-Fierro, "10 Reasons Why You Should Be Using Git In Software Projects". 2017. Available online: https://miguelgfierro.com/blog/2017/10-reasons-why-you-should-be-using-git-in-software-projects/
[45] M. González-Fierro, "Laplace’s Demon And The Scientific Method". 2017. Available online: https://miguelgfierro.com/blog/2017/laplaces-demon-and-the-scientific-method/
[46] I. Karmanov and M. González-Fierro, "How To Deploy An Image Classification API Based On Deep Learning". 2017. Available online: https://miguelgfierro.com/blog/2017/how-to-deploy-an-image-classification-api-based-on-deep-learning/
[47] M. González-Fierro, Y. Xing, and T. Wu, "Quick-Start Guide to the Data Science Bowl Lung Cancer Detection Challenge, Using Deep Learning, Microsoft Cognitive Toolkit and Azure GPU VMs". 2017. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/quick-start-guide-to-the-data-science-bowl-lung-cancer-detection-challenge-using-deep-learning-microsoft-cognitive-toolkit-and-azure-gpu-vms
[48] M. González-Fierro, "The Sorcerer’s Apprentice". 2017. Available online: https://miguelgfierro.com/blog/2017/the-sorcerers-apprentice/
[49] M. González-Fierro, I. Karmanov, T. Delteil, A. Argyriou, and M. Kaznady, "Cloud-Scale Text Classification with Convolutional Neural Networks on Microsoft Azure". 2017. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/cloud-scale-text-classification-with-convolutional-neural-networks-on-microsoft-azure
[50] M. González-Fierro, "A Gentle Introduction To Text Classification And Sentiment Analysis". 2017. Available online: https://miguelgfierro.com/blog/2017/a-gentle-introduction-to-text-classification-and-sentiment-analysis/
[51] A. Argyriou and M. González-Fierro, "Learnings From AI & Machine Learning Conference NIPS 2016". 2016. Available online: https://miguelgfierro.com/blog/2016/learnings-from-ai-machine-learning-conference-nips-2016/
[52] M. González-Fierro, "How To Develop A Data Science Project Using The Lean Startup Method". 2016. Available online: https://miguelgfierro.com/blog/2016/how-to-develop-a-data-science-project-using-the-lean-startup-method/
[53] M. González-Fierro, M. Kaznady, R. Jain, T. Wu, and A. Argyriou, "Training Deep Neural Networks on ImageNet Using Microsoft R Server and Azure GPU VMs". 2016. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/imagenet-deep-neural-network-training-using-microsoft-r-server-and-azure-gpu-vms
[54] M. Kaznady, M. González-Fierro, R. Jain, T. J. Hazen, and T. Wu, "Applying Deep Learning at Cloud Scale, with Microsoft R Server & Azure Data Lake". 2016. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/applying-cloud-deep-learning-at-scale-with-microsoft-r-server-azure-data-lake
[55] M. González-Fierro, "A Gentle Introduction To Convolutional Neural Networks". 2016. Available online: https://miguelgfierro.com/blog/2016/a-gentle-introduction-to-convolutional-neural-networks/
[56] M. Kaznady, R. Jain, T. Wu, M. González-Fierro, and A. Argyriou, "Building Deep Neural Networks in the Cloud with Azure GPU VMs, MXNet and Microsoft R Server". 2016. Available online: https://docs.microsoft.com/en-gb/archive/blogs/machinelearning/building-deep-neural-networks-in-the-cloud-with-azure-gpu-vms-mxnet-and-microsoft-r-server
[57] M. González-Fierro, "When To Use Deep Learning In A Data Science Problem". 2016. Available online: https://miguelgfierro.com/blog/2016/when-to-use-deep-learning-in-a-data-science-problem/
[58] M. González-Fierro, "How Human Intelligence Works And Why That Makes Us Racists". 2016. Available online: https://miguelgfierro.com/blog/2016/how-human-intelligence-works-and-why-that-makes-us-racists/
[59] M. González-Fierro, "A Gentle Introduction To The Basics Of Machine Learning". 2016. Available online: https://miguelgfierro.com/blog/2016/a-gentle-introduction-to-the-basics-of-machine-learning/
[60] M. González-Fierro, "Lessons Learned About Marketing While Building A Startup". 2016. Available online: https://miguelgfierro.com/blog/2016/lessons-learned-about-marketing-while-building-a-startup/
[61] M. González-Fierro, "The Growth Of Artificial Intelligence In The New Economy". 2016. Available online: https://miguelgfierro.com/blog/2016/the-growth-of-artificial-intelligence-in-the-new-economy/
[62] M. González-Fierro, "Is It Possible For A Robot To Have Emotions?" 2016. Available online: https://miguelgfierro.com/blog/2016/is-it-possible-for-a-robot-to-have-emotions/
[63] M. González-Fierro, "Why Math Is So Important In Everyone’s Life". 2016. Available online: https://miguelgfierro.com/blog/2016/why-math-is-so-important-in-everyones-life/
[64] A. Malmierca and M. González-Fierro, "The Science Behind The New Star Wars Robot: BB-8". 2016. Available online: https://miguelgfierro.com/blog/2016/the-science-behind-the-new-star-wars-robot-bb-8/
[65] M. González-Fierro, "A Blog With The Appearance Of A Scientific Paper In Latex". 2015. Available online: https://miguelgfierro.com/blog/2015/a-blog-with-the-appearance-of-a-scientific-paper-in-latex/
[66] M. González-Fierro, "The Spanish Startup Ecosystem Will Be More Technological". 2015. Available online: https://miguelgfierro.com/blog/2015/the-spanish-startup-ecosystem-will-be-more-technological/
[67] M. González-Fierro, "What Color Is This Dress? The Dressgate Explained". 2015. Available online: https://miguelgfierro.com/blog/2015/what-color-is-this-dress-the-dressgate-explained/
[68] M. González-Fierro, T. Nanayakkara, and C. Balaguer, "A Humanoid Robot Ph.D. Thesis Explained To Non Scientists". 2014. Available online: https://miguelgfierro.com/blog/2014/a-humanoid-robot-phd-thesis-explained-to-non-scientists/
[69] M. González-Fierro, "What Is Scrum And How To Apply It To A Startup". 2014. Available online: https://miguelgfierro.com/blog/2014/what-is-scrum-and-how-to-apply-it-to-a-startup/
[70] M. González-Fierro, "What Makes The Difference Is Not The Experience, But Its Derivative". 2014. Available online: https://miguelgfierro.com/blog/2014/what-makes-the-difference-is-not-the-experience-but-its-derivative/
[71] M. González-Fierro, "Dresscovery, The Visual Search App Is Working With Google Glass". 2014. Available online: https://miguelgfierro.com/blog/2014/dresscovery-the-visual-search-app-is-working-with-google-glass/
[72] M. González-Fierro, "Dresscovery App Is Out". 2013. Available online: https://miguelgfierro.com/blog/2013/dresscovery-app-is-out/
[73] M. González-Fierro, "The Best Image Recognition System For Fashion". 2013. Available online: https://miguelgfierro.com/blog/2013/the-best-image-recognition-system-for-fashion/
[74] M. González-Fierro, "Samsamia Is About AI, Pattern Recognition And Machine Learning". 2013. Available online: https://miguelgfierro.com/blog/2013/samsamia-is-about-ai-pattern-recognition-and-machine-learning/
[75] M. González-Fierro, "Samsamia At BBVA OpenTalent Event In Buenos Aires". 2013. Available online: https://miguelgfierro.com/blog/2013/samsamia-at-bbva-opentalent-event-in-buenos-aires/
[76] M. González-Fierro, "Demoday Of 2020 For 2020 Startup Madrid". 2013. Available online: https://miguelgfierro.com/blog/2013/demoday-of-2020-for-2020-startup-madrid/
[1] D. Brinkmann, "From Robotics to Recommender Systems - Miguel Fierro". 2024. Available online: https://www.youtube.com/watch?v=wEmO00ADppw
[2] L. H. Zafer, "Miguel Fierro - AI is the New Normal". 2023. Available online: https://podcasts.apple.com/ch/podcast/miguel-fierro-ai-is-the-new-normal/id1613934397?i=1000623771203
[3] P. Rolfe, "Faculty Spotlight: Miguel González-Fierro". 2023. Available online: https://www.ie.edu/school-science-technology/news/faculty-spotlight-miguel-gonzalez-fierro/
[4] M. Kurovski, "Microsoft Recommenders and LLM-based RecSys with Miguel Fierro". 2023. Available online: https://www.recsperts.com/episodes/17-microsoft-recommenders-and-llm-based-recsys-with-miguel-fierro
[5] A. N. Reganti, "Machine Learning Mastery For Career Growth At Top-Tech Corporations". 2023. Available online: https://miguelgfierro.com/blog/2023/machine-learning-mastery-for-career-growth-at-top-tech-corporations/
[6] N. Leiser, "Start With Transformers". 2023. Available online: https://miguelgfierro.com/blog/2023/start-with-transformers/
[7] S. Juarez, "Building Recommender Systems". 2022. Available online: https://miguelgfierro.com/blog/2022/building-recommender-systems/
[8] D. J. Reji, "Recommendation Systems". 2022. Available online: https://miguelgfierro.com/blog/2022/d4-data-podcast-with-miguel-fierro-recommendation-systems/
[9] J. Baum, "All About Human Series with Miguel González-Fierro". 2022. Available online: https://www.aitimejournal.com/all-about-human-series
[10] S. Nouri, "AI Career Interview Series #7: Miguel Fierro". 2021. Available online: https://www.linkedin.com/video/event/urn:li:ugcPost:6851333494367502336/
[11] A. M. Aditya, "Interview with Miguel González-Fierro, Sr. Data Scientist Lead, Microsoft". 2021. Available online: https://www.aitimejournal.com/@a.m.aditya/interview-with-miguel-gonzalez-fierro-sr-data-scientist-lead-microsoft
[12] T. Scarfe, "Miguel Fierro - Recommendation Systems". 2019. Available online: https://www.youtube.com/watch?v=arcelVdJnck
[13] Madrid+d, "We have to fight to show that a scientist can change the world (in Spanish)". 2014. Available online: http://www.preproduccion.madrimasd.org/notiweb/entrevistas/hay-que-luchar-demostrar-que-un-cientifico-puede-cambiar-mundo