Formal Methods with a Touch of Magic. - Parand Alizadeh Alamdari; Guy Avni; Thomas A. Henzinger; Anna Lukina (FMCAD, 2020)

Be Considerate: Objectives, Side Effects, and Deciding How to Act. - Parand Alizadeh Alamdari; Toryn Q. Klassen; Rodrigo Toro Icarte; Sheila A. McIlraith (CoRR, 2021)

Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning. - Parand Alizadeh Alamdari; Toryn Q. Klassen; Rodrigo Toro Icarte; Sheila A. McIlraith (AAMAS, 2022)

Epistemic Side Effects: An AI Safety Problem. - Toryn Q. Klassen; Parand Alizadeh Alamdari; Sheila A. McIlraith (AAMAS, 2023)

Remembering to Be Fair: On Non-Markovian Fairness in Sequential Decision Making (Preliminary Report). - Parand Alizadeh Alamdari; Toryn Q. Klassen; Elliot Creager; Sheila A. McIlraith (CoRR, 2023)

Jump Starting Bandits with LLM-Generated Prior Knowledge. - Parand A. Alamdari; Yanshuai Cao; Kevin H. Wilson (EMNLP, 2024)

Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making. - Parand A. Alamdari; Toryn Q. Klassen; Elliot Creager; Sheila A. McIlraith (ICML, 2024)

Policy Aggregation. - Parand A. Alamdari; Soroush Ebadian; Ariel D. Procaccia (NeurIPS, 2024)

Being Considerate as a Pathway Towards Pluralistic Alignment for Agentic AI. - Parand A. Alamdari; Toryn Q. Klassen; Rodrigo Toro Icarte; Sheila A. McIlraith (CoRR, 2024)

Pluralistic Alignment Over Time. - Toryn Q. Klassen; Parand A. Alamdari; Sheila A. McIlraith (CoRR, 2024)

Ground-Compose-Reinforce: Tasking Reinforcement Learning Agents through Formal Language. - Andrew C. Li; Toryn Q. Klassen; Andrew Wang; Parand A. Alamdari; Sheila A. McIlraith (CoRR, 2025)