3 papers
cs.LG2026
An Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals
Ramin Pishehvar
Retail investors lack access to the kind of personalized, tax-aware portfolio management that institutional clients take for granted -- existing robo-advisors use static, rule-base…
cs.AI2026
A Three-Phase Foundation Model for Tax-Aware Personalized Portfolio Management
Ramin Pishehvar
We present a three-phase deep reinforcement learning system for personalized portfolio management that addresses three limitations shared by all prior financial RL work: 1) ticker…
cs.AI2026
From Intent to Execution: Composing Agentic Workflows with Agent Recommendation
Kishan Athrey, Ramin Pishehvar, Brian Riordan +1
Multi-Agent Systems (MAS) built using AI agents fulfill a variety of user intents that may be used to design and build a family of related applications. However, the creation of su…