AMOR aims to be a leading research center for curiosity driven, groundbreaking and innovative research at the intersection of applied mathematics, artificial intelligence (AI), statistics, and operational challenges in business and industry.
Reitan Retail has partnered with BI Norwegian Business School to launch a groundbreaking research project aimed at developing solutions to reduce emissions and food waste within the grocery sector.
At the professional day of the festival Langs Akerselva, Professor Fabian Harang from BI Norwegian Business School and Sindre Andreassen, Head of Operations at REMA 1000, engaged in a dialogue on how collaboration between academia, business, and public administration can help address complex and real-world challenges in society and industry.
During Arendalsuka, Professor Fabian Harang from BI Norwegian Business School took part in a panel debate in the DN tent alongside Ole Robert Reitan (CEO and owner of Reitan Retail), Sigrun Gjerløw Aasland (Norwegian Minister of Research and Higher Education) and Alexandra Bech Gjørv (CEO of SINTEF).
BI-AMOR er en av partnerne i senteret «Sustainable, Risk-averse and Ethical AI» som skal forske på hvordan man kan utvikle KI som svarer på bærekraftsmål om energiforbruk, sikkerhet og ansvarlighet.
In the realm of international shipping, the regulatory landscape is complex and diverse, with multiple rules shaping the industry's market conditions
In March, Prof. Fabian Harang, Director of AMOR – Center for Applied Mathematics and Operations Research at BI Norwegian Business School, visited Harvard Business School together with Mr. Tore Høylie from the top management of REMA 1000.
A recent study published in European Management Journal sheds light on a surprising paradox in sustainability reporting: while the Global Reporting Initiative (GRI) standards have become increasingly comprehensive, their growing complexity may be undermining the very transparency they aim to promote.
Pricing complex derivatives remains a key challenge in financial mathematics. These instruments, often used to hedge risk, have intricate, path-dependent payoffs that make traditional pricing methods computationally intensive and analytically complex.