Meet the Team
As the Team of the Foundation for Best Practices in Machine Learning, we are the administrators of the FBPML on behalf of the community. Made up of seasoned data scientists, machine learning engineers, AI ethicists and governance experts, we are enthusiastic about lowering the barriers for pragmatic ethical and responsible machine learning.
Jeroen Franse | Chairperson & Board Member
Jeroen has been interested in the relation between statistics, truth-finding and society for a long time. When he realized the wide scale adoption of Big Data and ML could lead to the exponential growth of real consequences due to statistics mistakes, he decided to get into the responsible ML field. He currently works as a ML Engineer at ABN Amro. Before that, Jeroen was a Data Science consultant, and obtained his PhD in astrophysics. At ABN Amro, he focuses on implementing MLOps and responsible ML. Jeroen proposes that in the field of applied ML everything is connected: from how ML is organised to how the algorithms work, from the happiness of ML professionals to the safety of end-users.
Violeta Misheva | Vice-Chairperson & Board Member
Violeta has been interested in understanding the causes of social inequalities and to what extent bad experiences early in life propagate to negative outcomes later. When she realized ML can result in widening already existing social gaps, she became an advocate for the responsible development and deployment of ML. Violeta currently works as a data scientist at ABN Amro. Before that, she worked in consultancy and obtained her PhD in applied econometrics. Violeta likes sharing her knowledge with others by the form of workshops on data science and online courses. Violeta proposes that developers of ML solutions alone cannot ensure their safety but, rather, that the additional efforts of multidisciplinary experts as well as proper regulation is also needed.
Daniel Vale | Vice-Chairperson & Board Member
Daniel has long been interested in the intersection between the law, technology and society. Unsurprisingly, this drew him into the field of data science and law. Daniel currently works as legal counsel for AI & data science at the H&M Group: where his principal focus is on developing and maturing the company’s MLOps (business, governance, and regulatory) capacities. Daniel is also completing his PhD in law, MLOps, & finance at Leiden University. His education is in behavioural science, statistics, and law. Having worked at corporate law firms and as a consultant, Daniel has practical legal and commercial experience in the field. He proposes that responsible ML is centred around two essential themes - (a) a constant appreciation of context, and (b) prudent MLOps & project management.
Lorrie Straka | Board Member
Lorrie is a senior data scientist at Sogeti. She has a Ph.D. in astrophysics and has worked as a postdoctoral researcher at Leiden University. Her expertise lies in cloud platform computing and image recognition. At Sogeti she is driven to improve the way corporate data science and MLOps is done. When approaching machine learning, Lorrie believes spending time building a strong MLOps platform is critical to robust, sustainable projects and products. And you need more data!
Patrick Hall | Board Member
Patrick Hall is principal scientist at bnh.ai, a D.C.-based law firm specializing in AI and data analytics. Patrick also serves as visiting faculty at the George Washington University School of Business. Prior to co-founding bnh.ai, Patrick led responsible AI efforts at the machine learning software firm H2O.ai, where his work resulted in one of the world's first commercial solutions for explainable and fair machine learning.
Masheika Allgood | Board Member
Masheika Allgood is an AI Ethicist and the founder of AllAI Consulting, LLC, a platform for providing AI education across various industries to people with non-tech and non-AI backgrounds. The company's goal is to create an AI literate society, allowing citizens from all walks of life to feel comfortable engaging in discussions on the use of AI technology in their lives and communities. Before founding AllAI Consulting, Masheika founded and led the AI Ethics Workgroup at NVIDIA. She is passionate about purpose-driven design, the role of product management in driving AI ethics, and developing AI education that is accessible for all. Masheika holds an LL.M in Litigation and Dispute Resolution from the George Washington University School of Law, a Juris Doctorate from Florida State University, and a Masters in International Business from Florida International University.
Nicholas Schmidt | Board Member
Nicholas started working in the field of responsible AI through his twenty years of experience working at the intersection of statistics, law, and regulation. He is currently the CEO of SolasAI and the AI practice leader at BLDS, LLC. Before that, Nicholas studied at the University of Chicago. In his work at SolasAI, he leads a team of data scientists and engineers building software that assesses whether there is evidence of bias or discrimination in an algorithm, and then provides alternative models that are both fairer and highly predictive. Nicholas believes that algorithms can be used as a force for good, but that responsible governance is necessary for that to happen.
Joris Krijger | Board Member
Joris Krijger works as an Ethics & AI specialist at the Dutch bank de Volksbank while also holding a PhD position at the Erasmus University Rotterdam on Ethics & AI. In both positions he works on bridging the gap between principle and practice in AI Ethics by studying the operationalization of ethical principles from an academic and practical perspective. Joris believes in a holistic approach to the operationalization of ethics in AI and brings practical and academic expertise on the ethics of AI to the table. Next to his position at FBPML he also holds positions as a.o. Advisory Board Member at the Frankfurt Big Data Lab, Subject Matter Expert for CertNexus’ ‘Certified Ethical Emerging Technologist’ and Founding Editorial Board Member of Springer Nature’s AI and Ethics Journal.
Marjolein Franse | Board Member
Marjolein has been interested in consumer behavior through data analysis since her Masters in Economics at Utrecht University. She currently works as an Insight Strategist at Born05. Before that, she worked in Market Research and at various start-ups. Helping startups to understand their consumers, break through and scale-up is what drives her. Marjolein is excited to use her experience on growing startups to help the FBPML reach its potential.
Jesse Beem | Board Member
Jesse Beem is a service designer, working with, and in several AI product teams. He deep dives into the users- needs, wishes, and context; and aims to centralise those into the design and development process. His current interest is on combining Design Thinking with Machine Learning into “Human Centered Machine Learning”; and how to stay focused on the end-user when designing with ML. Jesse believes that, with the rapid increase of intelligent ML powered products and “seamless experiences”, designing for trust, transparency, and human emotions is more important than ever.
Iris Clever | Board Member
Iris Clever, Ph.D. is a historian of science, medicine, and technology who researches the history of the life sciences and data sciences from 1800 to the present. Her current book project asks how we have come to trust biometric technologies to operate objectively, while in practice they perpetuate historical biases. She received her Ph.D. from UCLA and currently works as a postdoctoral fellow at the Stevanovich Institute for the Formation of Knowledge at the University of Chicago. Iris is excited to be part of this multidisciplinary team and contribute her expertise on rethinking science, data, and equity to the FBPML.
Luc Adrichem | Board Member
Luc is a data scientist, advisor and policy maker. During his career as data scientist in the financial industry, he learned that making a real and sustainable impact with ML heavily depends on the overall adoption and organization of the data science profession. Building a well-performing ML model is one thing, but putting it to use in a complex and regulated business environment is another. He currently works as an Enterprise Advisor for Data Science at ABN Amro, where he is focusing on an enterprise-wide model governance framework, with special dedication to responsible ML. He believes that doing ML responsibly is not just our moral obligation to society, but also foundational for getting true value from it. Luc holds a MSc in Developmental Economics.
Leonoor Tideman | Board Member
Leonoor is a machine learning researcher at the Delft University of Technology. She has a MSc in control engineering. Her work focuses on the development of machine learning methodologies for biomarker discovery in molecular imaging data. She has expertise in explainable artificial intelligence and is passionate about algorithmic fairness. Leonoor believes that research in responsible AI would benefit from more collaboration between academia and industry.
James Curtis | Board Member
James is a quantitative researcher focused on US power markets and renewable asset management. He previously served as a consultant for financial services organizations, insurers, and health care providers in building more equitable ML models. James is excited to contribute to the interdisciplinary team at FBPML and to help practitioners build a holistic understanding of responsible AI/ML use. He has an MS in Mathematics, and a research background in condensed matter physics and probabilistic machine learning.
Chris Stocks | Board Member
Chris is a Data Science Consultant at SolasAI, where he helps clients build fair, highly predictive models using advanced machine learning and explainable AI techniques. Prior to his work with SolasAI and BLDS LLC, Chris analyzed disparities in credit outcomes at the Consumer Financial Protection Bureau to support fair lending actions that resulted in millions of dollars in restitution to consumers. Chris hopes to use his experience on both the regulatory and industry side of fair AI in fields like credit, healthcare, and marketing to help bridge the gap between academic ideals of fairness and how algorithms can be made more equitable in practice. Chris has an MS in Business Analytics.
Himanshi Allahabadi | Board Member
Himanshi is interested in historical bias and fairness in machine learning. During her thesis, she realized the gap between fairML research and present-day data ethics issues. Since then, she is passionate about fairness, explainability and prevention of harmful consequences of ML. Himanshi currently works as a data science consultant at EY. She also contributes to a framework for assessing trust in real-world ML use cases (distributed under the Creative Commons license). Before this, she worked as a software engineer in the life sciences industry and obtained her MSc Data Science in Engineering. Himanshi is enthusiastic about causality and causal representation of data, as a premise for algorithmic explainability and for learning beyond correlations.
Gerry Chng | Board Member
Gerry spent the last two decades in a Big 4 consulting firm advising clients from various industries on Cybersecurity challenges ranging from strategy to operational setups. He is a firm believer that technology - when put towards good and responsible use - can be a force multiplier for social good. The increasing global interest in Artificial Intelligence and Machine Learning brings great opportunities, but it has also demonstrated how a lack of good practices exacerbates the digital divide, privacy, fairness, and erodes the broader institutional trust. He has been dedicating his time in this area to connect the various communities to collectively design solutions to capture the opportunities while navigating the undesired consequences. An avid learner, he holds a Bachelor's degree in Electrical & Electronics Engineering, and continues pursuing a Masters degree in Artificial Intelligence and Sociology.
Help or Volunteer
We are always looking for volunteers to help us with tasks such as the administration of the foundation, community coordination and moderation, improving our platform and content creation. Feel free to send an email to email@example.com if you are interested or if you just want to get in touch.