Skip to content
Abstract neural vascular network visualization
All Research

Research Program

Embodied AI

Research across the full scale spectrum — from planetary systems to molecular machines. Bridging lab prototypes to production reality.

Publications

4 publications in Embodied AI

2026Embodied AIMESORehabilitation RoboticsExoskeletonsReinforcement LearningStroke RecoveryGait TrainingAdaptive Control

Reinforcement Learning-Adaptive Rehabilitation Exoskeletons for Post-Stroke Gait Recovery

Sim-to-Real Transfer and Human-in-the-Loop Optimization for Personalized Lower-Limb Assistance

Hass Dhia — Smart Technology Investments Research Institute

Market opportunity analysis for reinforcement learning-adaptive rehabilitation exoskeletons targeting post-stroke gait recovery. Four independent research groups have demonstrated metabolic cost reductions of 24.2% (Zhang et al., Science 2017), 23% (Slade et al., Nature 2022), 24.3% (Luo et al., Nature 2024), and 5.3-19.7% across ten activities (Molinaro et al., Nature 2024) using human-in-the-loop optimization, Bayesian optimization, and sim-to-real RL transfer on hip and ankle exoskeletons tested on human subjects. Zero commercial rehabilitation exoskeletons use RL-adaptive closed-loop control — all FDA-cleared devices (ReWalk, Ekso Bionics, Indego) operate with fixed, pre-programmed gait trajectories. Bottom-up TAM of $3.2B annually for US post-stroke gait rehabilitation, cross-checked against the $1.5B rehabilitation robotics market growing at 12.5% CAGR (Verified Market Reports, 2024). The gap between demonstrated RL-adaptive control and clinical deployment — personalization for neurological impairment profiles, manufacturing of sensor-integrated exoskeletons at rehabilitation facility volumes, and regulatory strategy for adaptive AI-controlled Class II medical devices — represents a first-mover opportunity in a device class where reimbursement pathways already exist (HCPCS K1007, CPT 97116).

2026Embodied AIMESOSurgical RoboticsAutonomous SurgeryImitation LearningLaparoscopic SurgerySoft Tissue

Autonomous Soft Tissue Surgical Systems with Learned Dexterity

Imitation Learning and Hierarchical Control for Surgeon-Independent Laparoscopic Procedures

Hass Dhia — Smart Technology Investments Research Institute

Market opportunity analysis for autonomous soft tissue surgical systems operating at Level 4 surgical autonomy. Three landmark studies — autonomous intestinal anastomosis in live porcine models (Science Translational Medicine, 2016; Science Robotics, 2022) and autonomous cholecystectomy clipping-and-cutting in ex vivo porcine gallbladders with 100% task completion across 8 unseen specimens (Science Robotics, 2025) — establish that AI-driven surgical robots can match or exceed expert surgeon consistency in soft tissue procedures. Zero commercial products exist at Level 4 autonomy; all FDA-cleared surgical robots operate at Level 1-3. ARPA-H committed $12M to the ALISS program (2024) for autonomous surgical development. Bottom-up TAM of $4.1B annually for US laparoscopic cholecystectomy alone, cross-checked against the $12.8B surgical robotics market (Mordor Intelligence, 2025). The gap between demonstrated autonomous capability and clinical deployment — regulatory strategy for AI-controlled surgical instruments, manufacturing of sensor-rich end-effectors at clinical volumes, and validated safety architectures for human-supervised autonomous operation — represents a first-mover opportunity in a device class with no commercial precedent.

2026Embodied AIMICROBioelectronic MedicineVagus Nerve StimulationNeuroimmune ModulationReinforcement LearningAutoimmune Disease

Closed-Loop Adaptive Bioelectronic Implants for Chronic Inflammatory Disease

Reinforcement Learning-Optimized Vagus Nerve Stimulation for Autoimmune Conditions

Hass Dhia — Smart Technology Investments Research Institute

Market opportunity analysis for closed-loop adaptive bioelectronic implants targeting chronic inflammatory disease. The biological mechanism — vagus nerve-mediated neuroimmune modulation — received FDA approval in July 2025 via SetPoint Medical's open-loop device for rheumatoid arthritis (Nature Medicine, 2025). Zero commercial products exist for closed-loop adaptive stimulation, where reinforcement learning algorithms optimize stimulation parameters in real time based on physiological biomarkers. Computational studies demonstrate 67% power reduction versus open-loop while preserving therapeutic efficacy (IEEE TNSRE, 2024). Bottom-up TAM of $6.2B annually for US treatment-resistant moderate-to-severe RA, cross-checked against the $25.8B bioelectronic medicine market (Grand View Research, 2023). The gap between FDA-validated biology and AI-optimized delivery — adaptive control algorithms, miniaturized closed-loop hardware, and manufacturing at clinical volumes — represents a first-mover opportunity in a device class with established regulatory precedent.

2026Embodied AIMICRODrug DeliveryMicroroboticsTargeted TherapyOncology

Magnetically Guided Microrobots for Targeted Intravascular Drug Delivery

Sub-Millimeter Autonomous Navigation for Precision Chemotherapy

Hass Dhia — Smart Technology Investments Research Institute

Market opportunity analysis for magnetically guided microrobotic drug delivery platforms. Foundational research validated in large animal models (Science 2025) demonstrates sub-millimeter capsule navigation against physiological blood flow under clinical fluoroscopy. Zero commercial products exist at the sub-millimeter intravascular scale. Bottom-up TAM of $2.5B annually for US oncology applications alone, cross-checked against the $10.7B targeted drug delivery market (Coherent Market Insights, 2025). The gap between laboratory validation and clinical deployment — AI-driven autonomous navigation, batch manufacturing, and regulatory strategy — represents a first-mover opportunity in a space where academic labs lack commercialization infrastructure.

4

Publications

22

Domains

0

Open-Source Repos

0

Published Packages

Collaborate with us

We welcome research collaborations, dataset contributions, and open-source partnerships across any discipline. Reach out to discuss.