ADVANCING TRUST
BETWEEN HUMANS AND MACHINES

With over 20 years of digital transformation leadership experience across health industries, Aleksandar has dedicated his entire career to advancing trust between humans and machines. He is a responsible AI industry leader, certified AI Ethics Lead Assessor, AI Ethics trainer and evaluator, startup mentor and entrepreneur.

Under his leadership and vision, a collective of experienced ethics, legal, and technical experts are united in the missions to ensure that everyone who is impacted by an AI recommendation is treated fairly and equally, and that the risks and benefits of automated decision making are transparent and accountable.

Prior to founding TrustVector, Aleksandar held leadership positions at PwC, HighPoint Solutions, IMS Health and Skura Corporation.

As a co-founder and Chief Scientific Officer (CSO), Sonja is responsible for evaluating and setting TrustVector's scientific priorities, envisioning and leading development of scientific capabilities, and building academic partnerships. Sonja is also a Professor in the Department of Applied Mathematics, College of Computing, at Illinois Institute of Technology. She discovers, studies, and models structure in relational data we encounter in our daily lives.

Sonja’s academic research portfolio spans theoretical and applied problems including development of statistical models for discrete relational data, such as social networks, and use of machine learning to predict and improve the behavior of algebraic computations.

Dr. Jamshidi brings nearly a decade of experience in both teaching and developing AI systems. With a mathematical background rooted in geometry and statistics, she approaches AI from an academically rigorous perspective.

Her expertise extends beyond development and implementation, as she is well-suited to assess and mitigate algorithmic bias, determine the feasibility of AI solutions, and test if an AI implementation achieves its aims.

Skilled in both creating AI solutions and training others on how to understand and implement these techniques, Dr. Jamshidi can break down complex concepts into easily digestible terms, making her an ideal partner for businesses looking to responsible AI.

Ben Cooperman is an accomplished management consulting executive with over two decades of experience in the healthcare industry. Ben's focus on evidence-based methodologies derived from high reliability organizations and safety science has led him to excel in enhancing safety and quality in several of the world’s top healthcare delivery systems.

His educational background and extensive professional experience provide him with a unique perspective on the healthcare industry. His outstanding aptitude in safety science and high reliability organizing empowers him to address cultural challenges with astute precision and his extensive knowledge of healthcare enables him to tackle intricate work system problems.

Dr. Vishesh Karwa is an Assistant Professor of Statistical Science at Temple University - Fox School of Business and Management. His research interests include data privacy; causal inference under network interference; social network models; algebraic statistics and computational methods for intractable likelihoods, among others.

Dr. Karwa earned his PhD in Statistics from The Pennsylvania State University, where he also attained a Master of Science in Transportation Engineering. He received a Bachelor of Technology in Civil and Environmental Engineering from the Indian Institute of Technology.

Uroš Injac is a seasoned finance professional with 19+ years of experience in leading financial operations and strategic business consulting across multiple industries.

With a strong entrepreneurial spirit, Uroš has not only held management positions at companies like Renault, Nissan and Deloitte but also founded his own ventures. His expertise spans financial planning, analysis, risk management, and process optimization, allowing him to bring a practical, real-world understanding of business challenges.

Uroš is a certified auditor, member of the Chamber of Authorized Auditors of Serbia, and has successfully managed multimillion-euro operations, supervised cross-functional teams, and implemented innovative strategies in both corporate and entrepreneurial settings.

Andrew is qualified to assess AI systems (IEEE CertifAIEd) and is a Visiting Fellow of AI Practice at the Mohammed bin Rashid School of Government. He is a contributor to the World Economic Forum’s G20 Global Smart City Alliance for urban technology governance. Having led their open data policy work, he is currently producing a model policy to promote whole-of-lifecycle infrastructure management to city administrations and their partners.

With 14 years of leadership experience in two of the world’s most advanced city governments - London and Dubai, Andrew has played a leadership role in the design and launch of the London Office of Technology and Innovation, as well as produced the Middle East’s first set of AI guidelines for the UAE Government and led the development of an AI-ready digital infrastructure strategy in Dubai.

During her doctoral studies Ms. Vaidya has undertaken groundbreaking research in Ethical AI Governance, Data-Driven Decision Making, and effective communication of scientific insights. Her focus on responsible AI implementation in the public sector demonstrates a commitment to addressing critical issues in the field.

Ms. Vaidya’s research project, the Open Explainability Protocol (OEXP), stands as a testament to her dedication to ethical AI and responsible governance. OEXP aims to establish a universally accepted standard for conveying the outputs of autonomous systems, a crucial step in enhancing user interactions with AI-based systems. This initiative, together with Ms. Vaidya’s relevant work experience, reflects Ms. Vaidya’s proactive approach in contributing to industry-wide standards.

Dr. Solus is an assistant professor at KTH Royal Institute of Technology in Stockholm, Sweden. His research is in the area of combinatorics, and it centers around the use of combinatorial methods to learn salient features of probability distributions, such as their symmetries, modality, and factorizations.

Liam is interested in such problems as they arise in a variety of settings, including artificial intelligence, statistics, as well as algebra and geometry. In the former context, Liam is particularly interested in the combinatorics of graphical models and their applications to fields like causality. In the latter context, Liam is working to use a mixture of algebraic and analytic techniques to describe the distributional properties of discrete distributions that arise in algebra and geometry.

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Karen has over 24 years of advisory, consulting, and technology implementation experience across multiple sectors and solution/technology capabilities. She was a leader in the Digital Customer Experience (DCX) practice at Capgemini, specifically focused on solutions leveraging the Salesforce.com suite of technologies. Karen also has experience leading P&L operations for the Manufacturing, Automotive and Life Sciences Market Unit. In that role, Karen managed all aspects of the operations for the market unit including marketing, finance, sales (go to market), capacity (people supply chain) and delivery.

Karen has supported both the top line performance of the unit, driving the sales and revenue of the group as well as implement initiatives and programs to harden the bottom line performance of the unit.