activity
20242026
collaborators

14 papers

cs.CL2026

Backtrader-Bench: Benchmarking LLM Agents on Algorithmic Trading with Self-Generated MCQs

Ruoxi Zhao, Maziar Raissi

Evaluating LLM coding agents in algorithmic trading is difficult because static benchmarks risk data contamination and numerical backtest outputs require ground truth from actual c…

eess.SY2026

VeraGrid-Agent: Tool-Augmented LLMs for Distribution Optimal Power Flow at the Grid Edge

Shivanshu Tripathi, Hamed Mohsenian-Rad, Maziar Raissi

Language models have demonstrated remarkable success in solving a wide range of tasks. However, answering complex scientific questions about the power flow often requires solving t…

cs.SD2026

Spectrogram-Based Joint Detection, Localization, and Classification of Events in Continuously Recorded IBR Waveforms

Shivanshu Tripathi, Maziar Raissi, Hamed Mohsenian-Rad

Continuously recorded high-resolution waveform measurements provide rich information about fast power system dynamics. However, they require automated methods to identify events. T…

cs.AI2026

PHREEQC-MCQ-200: A Diagnostic Benchmark for Tool-Augmented Scientific Simulator Agents

Ke Zhang, Sahchit Chundur, Mohammad Javad Qomi +1

Large language model agents are increasingly connected to scientific software, yet it remains unclear when tool access makes scientific computation more reliable rather than merely…

cs.AI2026

Beyond Compilation: Evaluating Faithful Natural-Language-to-Lean Statement Formalization

Ke Zhang, Patricio Gallardo Candela, Sudhir Murthy +3

Theorem-proving benchmarks evaluate proof search against fixed formal statements, but natural-language-to-Lean formalization must generate the formal statement itself. In this sett…

cs.LG2026

NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations

Satish Chandran, Maedeh Makki, Maziar Raissi +2

We introduce NewPINNs, a physics-informing learning framework that couples neural networks with conventional numerical solvers for solving differential equations. Rather than enfor…