ARYAN KARGWAL

[PhD Researcher] AI & Robotics
@ Polytechnique Montréal

[ THE LAB BENCH ]

Systems Engineering & Research Prototypes

Active Development

BenchYard: Edge Device Benchmarking & LLM Inferencing

Edge devices benchmarking and inferencing for LLMs. Optimizing large language model deployment and performance evaluation across edge computing environments.

LLMEdge ComputingBenchmarking

Demo →

Research Prototype

Multi-Robot SLAM: Formal Language Verification

Formal language verification approach for multi-agent SLAM systems. Uses temporal logic specifications to ensure correctness guarantees in decentralized mapping and localization tasks.

RoboticsSLAMFormal Verification

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Archived

Caiman Ice: Semantic Segmentation for Remote Sensing

SLAM-based semantic segmentation for ice and snow classification in remote sensing imagery. Uses SLAM-derived super-segments merged via visual cues to distinguish between water, snow, and ice in ambiguous conditions.

Semantic SegmentationRemote SensingSLAM

Paper →

[ FEATURED WRITING ]

Essays, articles & research talks

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#01

Agent evaluation metrics: how to measure whether an agent works

Arize AI May 2026

Learn how to measure and evaluate AI agent performance effectively with key metrics and methodologies.

Agent Ops

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BETA DISTRIBUTION

#02

Best AI Observability Tools for Autonomous Agents in 2026

Arize AI Feb 2026

A comparative look at leading observability tools for autonomous AI agents, with evaluation criteria for production deployment in 2026.

Tools & Platforms

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GAUSSIAN DISTRIBUTION

#03

Understanding Latency in AI Model Deployment

Pipeshift Feb 2026

A practical breakdown of where latency comes from in deployed AI systems and how teams can reduce bottlenecks across the inference path.

Engineering

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EXPONENTIAL DECAY

#04

Rented AI and Hidden Costs

Pipeshift Feb 2026

An analysis of the hidden operational and business costs teams face when relying on rented AI stacks without strong infrastructure ownership.

Strategy

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EXPONENTIAL DECAY

#05

Why AI Agents Break: A Field Analysis of Production Failures

Arize AI Jan 2026

A comprehensive field analysis of production failures in AI agents. Explores the root causes and failure patterns that occur when AI agents break in real-world deployments.

Analysis

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BINOMIAL DISTRIBUTION

#06

Observability-Driven Sandboxing

Arize AI Jan 2026

Securing AI agents through observability-driven sandboxing: techniques for monitoring and controlling agent behavior.

Security

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EXPONENTIAL DECAY