Jacob Kosoff Brings Expertise to QuantU
Regions’ Head of Model Risk Management & Validation speaks to data scientists about the importance of modernizing model risk.
The US government wants to help companies assess AI risk
Sri Krishnamurthy, who founded AI advisory firm QuantUniversity and plans to submit a proposal to the NIST solicitation.
Achieving Responsible AI in Finance With Model Performance Management
How financial institutions are tackling the problems with black box ML
Mathematical Finance & Financial Data Science Seminar
Introduce Algorithmic auditing and discuss why Algorithmic auditing will be a formal process industries using AI will need
Watch Sri Krishnamurthy, CFA, QuantUniversity explain what you should think about before you take a Python course.
GRADUATE BUSINESS PROGRAMS FINTECH ROUNDTABLE
Join Fintech leaders and D’Amore-McKim faculty and alumni as they share their perspectives on tokenization, blockchain, cryptocurrency, payment innovations, and more.
AI in Finance Panel: Accelerating AI Risk Mitigation with XAI and Continuous Monitoring
At the AI in Finance Summit, NY, in December 2020, we had a panel discussion on the state of responsible AI.
Governance in the Day of Data Science and AI
Bring clarity on some of the data and model governance challenges when adopting data science and AI/ML processes in the enterprise.
Emotionally aware technology could help us beat Zoom fatigue
More emotionally intelligent computers could help bridge the gap caused by social distancing.
Investment Decision Making in an AI world
An interview covering some of the basic terminologies and charting a map of the AI-driven landscape.
GLOBAL WEBINAR SERIES ON AI IN FINANCE, WITH WAIFC AND WEF
The potential and application bandwidth of AI/ML in Financial Services is breathtaking.
Machine Learning and AI in Risk Management
An overview of the current state of applied machine learning and artificial intelligence for risk modeling and how it can be applied for monitoring risk and building new risk models.
How to survive as a quant AND a trader as Big Data takes over
What do traders, data scientists and tech professionals need to know to get hired, avoid getting fired and get promoted?