Alejandro Correa Bahnsen, PhD

Alejandro Correa Bahnsen, PhD

Área metropolitana de Ciudad de México
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Hi, I'm Alejandro Correa Bahnsen. At the core, I'm passionate about artificial intelligence, data science, and finding innovative solutions in cybersecurity. I'm proud to have contributed to seven US patents and co-created a few open-source machine learning libraries. But beyond the tech, I'm an avid open-water swimmer, ranking among the top in the world. The discipline I've learned from swimming translates to my work, helping me navigate challenges with determination.

Currently, I'm leading the AI initiatives at AB InBev, aiming to seamlessly weave AI into our operations. Before this, I had the privilege of leading a fantastic team of data scientists at Rappi. My journey has taken me across various sectors and continents, but what remains constant is my love for teaching and mentoring. I've spoken at numerous events and taught at institutions like Universidad de los Andes.

Outside of work, you'll find me in the water, on the tennis court, or enjoying a game of padel. I believe in staying approachable, sharing knowledge, and always being open to learning. Let's connect and share ideas!

Experiencia

  • Gráfico AB InBev

    AB InBev

    Mexico City, Mexico

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    Mexico City, Mexico

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    Bogotá D.C. Area, Colombia

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    Bogotá D.C. Area, Colombia

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    Bogota, Colombia

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    Luxembourg

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    Bogota, Colombia.

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    Bogota, Colombia

Educación

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Patentes

  • DETERMINING CREDIT RISK OF AN ONLINE MERCHANT BASED ON PERFORMANCE OF GOODS/SERVICES OF THE MERCHANT IN AN ONLINE MARKETPLACE

    Presentada el US 0080.004US00

    Online marketplaces present unique opportunities for lenders to consider performance
    information (e.g., popularity/purchaser feedback) of items (i.e., goods and/or services) of a
    merchant.

    Otros inventores
  • Pupil or Iris Tracking for Liveness Detection in Authentication Processes.

    Presentada el US 148857-200400/US

    Examples of the systems and methods disclosed herein for implementing liveliness detection in an authentication process using pupil or iris tracking provide specific technical solutions to at least the technical problems mentioned in the background section and other parts of the application as well as other technical problems not described herein but recognized by those of skill in the art.
    The disclosed techniques can utilize a combination of facial recognition and pupil or iris tracking…

    Examples of the systems and methods disclosed herein for implementing liveliness detection in an authentication process using pupil or iris tracking provide specific technical solutions to at least the technical problems mentioned in the background section and other parts of the application as well as other technical problems not described herein but recognized by those of skill in the art.
    The disclosed techniques can utilize a combination of facial recognition and pupil or iris tracking for liveliness detection in an authentication process to provide an extra layer of security against
    impersonation attacks.

    Otros inventores
  • Location Spoofing Detection Using Round-Trip Times

    Presentada el US 148857-200600/US

    Examples of the systems and methods disclosed herein for implementing location
    spoofing detection using round-trip times (RTTs) provide specific technical solutions to at least
    the technical problems mentioned in the background section and other parts of the application as
    well as other technical problems not described herein but recognized by those of skill in the art.
    The disclosed techniques utilize round-trip times (RTTs) from back-and-forth
    communications with distant…

    Examples of the systems and methods disclosed herein for implementing location
    spoofing detection using round-trip times (RTTs) provide specific technical solutions to at least
    the technical problems mentioned in the background section and other parts of the application as
    well as other technical problems not described herein but recognized by those of skill in the art.
    The disclosed techniques utilize round-trip times (RTTs) from back-and-forth
    communications with distant servers to detect impersonations in a computer network, such as
    impersonations using IP spoofing.

    Otros inventores
  • Anti-Spoofing Techniques Using Device-Context Information and User Behavior Information

    Presentada el US 148857-200900/US

    The disclosed techniques herein combine the capturing of device-context information
    and user behavior information in a session, such as a user authentication session, to increase security
    for user authentication mechanisms and methods. The techniques can use machine learning that
    aims at high accuracy, and only occasionally raises alarms for manual inspection.

    Otros inventores
  • Classification of Transport Layer Security Certificates Using Artificial Neural Networks

    Presentada el US 173694-200200

    Embodiments of the disclosure relate generally to classification of web security certificates using artificial neural networks, and more specifically, relate to, for example, using artificial neural networks to classify transport layer security (TLS) certificates.

    Otros inventores
  • Phishing Detection Enhanced Through Machine Learning Techniques

    Presentada el US 173694-200100

    Disclosed herein are phishing enhancement and phishing detection enhancement technologies. The technologies can include determinations of an effectiveness rate of one or more phishing threat actors. The technologies can also include selection of effective URLs from at least
    one effective phishing threat actor. The technologies can also include generation or adjustment of a phishing system using a machine learning process to identify patterns in the selected effective URLs that enable the…

    Disclosed herein are phishing enhancement and phishing detection enhancement technologies. The technologies can include determinations of an effectiveness rate of one or more phishing threat actors. The technologies can also include selection of effective URLs from at least
    one effective phishing threat actor. The technologies can also include generation or adjustment of a phishing system using a machine learning process to identify patterns in the selected effective URLs that enable the selected effective URLs to avoid detection by the phishing detection system. The technologies can also include generation of synthetic phishing URLs using the phishing system and the identified patterns. The technologies can also include adjustments or training of the phishing system or the phishing detection system according to the synthetic phishing URLs to enhance the systems.

    Otros inventores
  • SYSTEMS AND METHODS RELATING TO A MARKETPLACE SELLER FUTURE FINANCIAL PERFORMANCE SCORE INDEX

    Presentada el US PCT/US2018/029052

    A method, and associated system, for using a financial performance forecast relating to an online marketplace seller, including, under control of one or more processors configured with executable instructions, collecting historical data relating to activities of the online marketplace seller; executing a machine learning component of an adaptive machine learning platform to generate a machine learning component output, where the machine learning component output is generated at least in part…

    A method, and associated system, for using a financial performance forecast relating to an online marketplace seller, including, under control of one or more processors configured with executable instructions, collecting historical data relating to activities of the online marketplace seller; executing a machine learning component of an adaptive machine learning platform to generate a machine learning component output, where the machine learning component output is generated at least in part based on the historical data; generating, based at least in part on the machine learning component output of the machine learning component, a financial performance forecast score; and making a recommendation to provide funding to the online marketplace seller, based at least in part on the financial performance forecast score.

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