Ph.D. Candidate · University of Ottawa
Kamran
Gholizadeh
HamlAbadi
I build AI systems that reason, act, and adapt inside physical and virtual worlds, bridging agentic LLM reasoning, physics simulation, and multimodal sensing to create reliable embodied intelligence.
MCRLab, School of EECS · Supervised by Prof. Abdulmotaleb El Saddik (IEEE / ACM / EIC Fellow)
Building AI at the Edge of
the Physical and Virtual
I am a Ph.D. candidate at the Multimedia Communications Research Laboratory (MCRLab), University of Ottawa, working at the frontier of agentic AI, physical simulation, and human–AI interaction. My research produces AI systems that operate reliably in the real world, not just in benchmarks.
My doctoral work spans two connected threads: CARE-AI, an emotion-aware Digital Twin framework for personalized coaching, and NemoForge, a simulator-in-the-loop agentic system that rehabilitates physics violations in neural 3D reconstructions for simulation-ready environments.
I have published at ACM Multimedia (CORE A*), ACM TOMM (CORE A), ACM IMX, and IEEE MeMeA, received two international best paper awards, and serve on the editorial boards of the IEEE Metaverse Newsletter and ACM SIGMM Record.
Education
Ph.D. · Electrical & Computer Engineering
University of Ottawa, Canada · 2022–Present
Dissertation: CARE-AI: Coordinated, Agentic, Robust, Emotion-Aware AI
M.Sc. · Information Technology Engineering
Islamic Azad University, Qazvin · 2011–2015
B.Sc. · Computer Engineering – Software
Mazandaran Institute of Technology · 2007–2009
Research Interests
Meta-Review on Brain-Computer Interface (BCI) in the Metaverse
First PRISMA meta-review on BCI–Metaverse integration. 42 papers analyzed. Two novel integration frameworks proposed.
A Framework for Cognitive Internet of Things Based on Blockchain
Research in Action
CARE-AI
Coordinated, Agentic, Robust, Emotion-Aware AI
Emotion-aware Digital Twin coaching framework integrating multimodal sensing, A2A/MCP multi-agent protocols, NVIDIA Omniverse avatars, and LLM-driven adaptive feedback via CrewAI and NVIDIA AgentIQ.
ACM MM '25 (A*) · ACM IMX '25
NemoForge
Post-Reconstruction Physical Rehabilitation of Neural 3D Scenes
Simulator-in-the-loop RAR agentic system correcting physics violations in NeRF/3DGS/DUSt3R reconstructions. Introduces a learned stopping policy via behavioural cloning and the novel RFPCR metric.
Target submission: CVPR / ICCV / ICML 2027
BCI × Metaverse
First PRISMA Meta-Review on Brain-Computer Interfaces
Analyzed 42 peer-reviewed papers on BCI–Metaverse integration. Proposed two novel frameworks covering VR, AR, XR, Digital Twins, and haptics.
Olfactory VR
Multisensory Well-Being in Immersive Environments
Randomized study (N=30) showing olfactory stimuli significantly enhance physiological stress reduction (ECG-HRV analysis) in VR environments.
LiDAR to USD Pipeline
iPhone LiDAR to NVIDIA Omniverse
End-to-end pipeline converting iPhone LiDAR point clouds to simulation-ready USD scenes via NeRF/Nerfacto for robot learning and XR environments.
Omniverse Kit Extension
Live Webcam to USD Viewport
Custom NVIDIA Omniverse Kit extension streaming live webcam into a 3D USD viewport, supporting embodied AI and avatar perception pipelines.
Academic & Professional Roles
Research Assistant & PhD Researcher
MCRLab, University of Ottawa
CARE-AI, NemoForge, multimodal AI, Digital Twins, NVIDIA Omniverse/Isaac Sim
Part-Time Professor
University of Ottawa
Introduction to Computing II (Java)
Teaching Assistant
University of Ottawa
Real-Time Systems · Computer Architecture · Cloud Technologies · Project Management · SE Capstone
Software Developer & Blockchain Engineer (R&D)
Sadad Informatics Corp. (SIC), Tehran
Open banking · Ethereum/Stellar smart contracts · KYC · Microservices (Java Spring Boot)
Technical Skills
AI & ML
Agentic Systems
Simulation & 3D
Programming
Tools
Awards & Honors
MSMA '25 · ACM Multimedia · Dublin, 2025
IEEE ICWR · Tehran, 2018
University of Ottawa · 2022–Present
University of Ottawa · 2022
Academic Service
Toward AI That Understands
the Physical World
The next decade of AI will be defined by systems that don't just process language or images but that act in physical and virtual environments with reliability and awareness. My research builds toward that future: agents that reason about geometry, correct their own physics errors, sense human emotion, and adapt their behavior accordingly.
From real-to-sim pipelines for robot learning, to emotion-aware Digital Twin coaches, to simulator-in-the-loop agentic correction, I am building the infrastructure for physically grounded, human-centered AI.
Open to Academic and
Industry Opportunities
I am actively seeking postdoctoral positions at top research universities in the United States and Canada, with particular interest in groups working on embodied AI, physical simulation, agentic systems, sim-to-real transfer, or multimodal human–AI interaction.
I am equally interested in industry research and engineering roles at AI labs, robotics companies, and technology organizations working on agentic AI systems, Digital Twin platforms, autonomous simulation, LLM reasoning and tool use, or multimodal AI products. I bring both strong research depth and hands-on engineering experience in production-grade systems.
I welcome conversations about collaborations, research partnerships, and visiting positions.