Irene Pu

Contest of Comments

Mad Titan’s Wrath

Sentinel of the Spaceways

5th Anniversary Trailer

Aether Revolt Trailer

Ahmonket Trailer

Hour of Devastation Trailer

Ixalan Trailer

Dominaria Trailer

Ixalan Trailer

Core Set 2019 Trailer

Guilds of Ravnica Trailer

Ravnica Allegiance Trailer

Driving R&D integrating muscle simulation, ML deformers, and facial tools into DNEG’s rigging/CFX pipeline for real-time and film.

Developing automated face/body rigging workflows using 4D scans, simulation, and custom internal tools.

Built a simulation-driven character transfer pipeline to accelerate rig creation for new assets.

Worked with ML teams to build game/VFX-ready ML deformers trained on cloth and muscle simulations, including data prep and pipeline alignment.

Acted as consulting TD for show teams—advising on modeling, deformation, topology, muscle workflows, and facial rigging.

Authored training documentation and taught Supervisors/Leads to adopt new Ziva face/muscle tech.

Explored R&D areas such as audio-driven facial animation, ML tracking, and deepfake-style render analysis.

Built automated retargeting systems to transfer archetype rigs to new characters at scale.

Core contributor to Ziva Face Trainer, combining ML deformers, 4D scan processing, and muscle simulation to enhance facial rigs.

Designed a corrective-shape workflow improving accuracy and expressiveness of face deformations.

Collaborated with ML teams to integrate audio-to-face rig driving inside Unity.

Adapted detailed 4D scan sequences to varied character models, converting data into rig-friendly controls (sticky lips, blink localization).

Created a machine-learned tongue rig for real-time demos.

Automated face transfer and rig build pipelines using Python.

Proposed ML implementation paths based on research papers; collaborated across Tech Art, Product, and R&D.

Built demos in Unreal and Unity: state machines, locomotion, animation import, and performance profiling.

Helped define a baseline character skeleton standard for Ziva/Unity.

Presented Ziva technology at SIGGRAPH and supported hiring for tech art and ML roles.

Developed real-time rigs, state machines, and gameplay logic to bring characters to life across platforms.

Researched ML applications for locomotion and deformation enhancement in game production.

Built auto-rigging systems, animation tools, and Maya↔Unreal pipeline automation.

Created gameplay prototypes for two new IPs, including rig systems, tools, and Unreal integration.

Interviewed TA, engineering, and animation candidates to help build out the team.

Worked with Epic on hair groom R&D; managed animation imports, IK, PHAT collisions, and blueprint integration.

Trained technical artists on custom rigging/animation tools.

Led rigging/CFX teams delivering body, face, prop, vehicle, and FX rigs, and simulation shotwork.

Prepared rigs for mocap shoots and supervised mocap shoots to ensure successful rig retargeting and mocap capture

Built pipelines for hair grooming, Ziva muscle creation, and asset publishing (Shotgun integrated). Developed cross-promotion relationship for Ziva work.

Created tools including: pick-walking systems, auto-car rigging, and FBX export pipelines (Maya → Unreal/Unity)

Maintained & upgraded pipelines across Maya, Houdini, and Houdini Farm.

Rigged creatures, vehicles, and props; executed cloth/hair simulation using nCloth/nHair.

Cleaned + hand-keyed mocap for cinematics; ensured compatibility with Unity playback systems.