The ICDSST 2025 Conference is proud to feature invited speakers who will share their expertise on key topics in decision support systems.
Stay tuned as we announce additional speakers in the coming weeks!
Fátima Dargam
REACH Innovation
CEO & Research Managing Director / Co-founder
Honorary Chair and Invited Speaker
Dr. Fátima Dargam is an expert in Decision Support Systems and Artificial Intelligence, with a Ph.D. from Imperial College London and extensive experience as an R&D IT Manager at SimTech in Austria. Her work spans intelligent decision-making, multi-agent systems, and big data analytics, with significant contributions through research, publications, and her role as a founding member and former coordinator of the EURO Working Group on DSS.
Pascale Zaraté
Université Toulouse Capitole- IRIT
Full Professor
Honorary Chair and Invited Speaker
Dr. Pascale Zaraté is a Professor at Toulouse 1 Capitole University in France, where she conducts research at the IRIT Laboratory, focusing on Decision Support Systems (DSS), cooperative decision-making, and recommender systems. She earned her Ph.D. in Computer Science from the LAMSADE laboratory at Paris Dauphine University in 1991. Dr. Zaraté chaired the European Working Group on DSS from 2000 to 2020 and currently serves as Vice-President of the INFORMS Group Decision and Negotiation section. Her research interests encompass distributed and asynchronous decision-making processes, knowledge modeling, and cooperative knowledge-based systems.
Zoran Obradović
Director, Center for Data Analytics and Biomedical Informatics
Temple University
Invited Speaker
Dr. Zoran Obradović is a distinguished professor at Temple University, holding the Laura H. Carnell Professorship of Data Analytics. He serves as the director of the Center for Data Analytics and Biomedical Informatics and holds professorships in both the Department of Computer and Information Sciences and the Department of Statistical Science. His research encompasses data science, machine learning, and biomedical informatics, with a focus on big data analytics, complex systems, and decision support systems. Dr. Obradović has authored over 450 publications, garnering more than 34,000 citations, reflecting his significant impact on the field. He is an elected member of Academia Europaea and a foreign member of the Serbian Academy of Sciences and Arts.
Marko Bohanec
Scientific Councillor
Department for Knowledge Tehnologies, Jožef Stefan Institute.
Dr. Marko Bohanec is a prominent computer scientist specializing in decision support systems and multi-attribute decision modeling. He serves as a Scientific Councillor at the Jožef Stefan Institute’s Department of Knowledge Technologies in Ljubljana and is a Professor of Computer Science at the University of Nova Gorica. He is renowned for developing the DEX (Decision EXpert) methodology, a qualitative multi-attribute decision modeling approach that integrates multi-criteria decision modeling with rule-based expert systems. Throughout his career, Dr. Bohanec has authored numerous publications and has been cited over 6,800 times, reflecting his significant impact on the field. His research interests include decision analysis, artificial intelligence, expert systems, machine learning, and data mining.
Lily Xu
Postdoc at Oxford, (soon Assistant Professor at Columbia)
Invited Speaker
Lily Xu develops methods across machine learning, optimization, and causal inference for planetary health challenges, with a focus on biodiversity conservation. She aims to enable practitioners to make effective decisions in the face of limited data, taking actions that are robust to uncertainty, effective at scale, and future-looking. In her work, Lily partners closely with NGOs to bridge research and practice, serving as AI Lead for the SMART Partnership. Since 2020, she has co-organized the EAAMO research initiative, committed to advancing Equity and Access in Algorithms, Mechanisms, and Optimization. Lily will join Columbia IEOR as an Assistant Professor in July 2025.
Talk:
High-stakes decisions from low-quality data: AI decision-making for planetary health
Abstract:
Planetary health recognizes the inextricable link between human health and the health of our planet. Our planet’s growing crises include biodiversity loss, with animal population sizes declining by an average of 70% since 1970, and maternal mortality, with 1 in 49 girls in low-income countries dying from complications in pregnancy or birth. Overcoming these crises will require effectively allocating and managing our limited resources. My research develops data-driven AI decision-making methods to do so, overcoming the messy data ubiquitous in these settings. Here, I’ll present technical advances in multi-armed bandits, robust reinforcement learning, and causal inference, addressing research questions that emerged from on-the-ground challenges across conservation and maternal health. I’ll also discuss bridging the gap from research and practice, with anti-poaching field tests in Cambodia, field visits in Belize and Uganda, and large-scale deployment with SMART conservation software.