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Mario Brcic
Assistant Professor at FER - Operations Research - AI - Data Science - Machine Learning - Consulting
Mario Brcic is an Assistant Professor at the University of Zagreb Faculty of Electrical Engineering and Computing (FER) since November 2019.12 He is an expert in Artificial Intelligence, Operations Research, and Decision Intelligence, with a focus on digital transformation and business strategy.3
Brcic's research interests include:
- AI (reinforcement learning) and combinatorial optimization
- Supply chain management
- AI Safety and Ethics
- Digital twins
- Digital transformation2
He teaches undergraduate and graduate courses in Operations Research, Advanced Algorithms and Data Structures, and Object-Oriented Programming.2 Brcic is also involved in mentoring students and participating in research projects.2
In addition to his academic role, Brcic holds several other positions:
- Managing Partner at It From Bit, a company providing services in data engineering, AI, and decision science2
- Chair of IEEE Computational Intelligence Society Croatia Chapter (since January 2023)2
- Advisor for Data Science and AI at Huddle (since January 2022)2
Brcic has a Ph.D. in Computer Science from FER, with a doctoral thesis on "Proactive-reactive project scheduling with flexibility and quality requirements".2 He has published numerous research papers in the fields of AI, operations research, and project scheduling.4
His LinkedIn profile (username: mariobrcic) showcases his expertise in AI, decision intelligence, digital transformation strategy, entrepreneurship, and leadership.3
Highlights
Exciting Announcement! I am proud to share our latest preprint, "Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions". This work is a collaborative effort with renowned researchers in the field with whom I greatly enjoyed collaborating: Luca Longo, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Dr. Timo Speith, and Simone Stumpf.
🔍 Our paper dives into the crucial topic of Explainable AI, addressing the pressing need to understand opaque AI systems flourishing in various real-world applications. We explore the advancements in XAI and its practical implications, while also shedding light on the ongoing challenges and complexities within the field.
💡 Through this manifesto, we present 27 open problems in XAI, categorized into nine distinct categories. Our aim is to provide a comprehensive road map for future research, fostering collaborative discussion and interdisciplinary cooperation. We believe that by uniting experts from diverse fields, we can synchronize research agendas and accelerate the practical applications of XAI.
🌍 This paper is more than just an academic exercise; it's a call to action for all stakeholders interested in shaping the future of AI to be more transparent, understandable, and trustworthy.
📖 Dive into our manifesto and join us in propelling XAI forward: https://lnkd.in/dS4a73X3
#ArtificialIntelligence #XAI #Research #Collaboration #Innovation #FutureOfAI
