Philippe Teichmann Projects/Experience

• Delivered an end-to-end real-time demolition system in the Vortex core engine, validated in two public simulator demos, by implementing collision detection, fracture generation, debris simulation, and graphics rendering.

• Reduced worst-case frame times 60% by caching collision and mesh data, batching, object pooling, reducing heap allocations, and tuning object sleeping within a data-oriented architecture.

• Built two rendering pipelines for demolition, ensuring stability in stress tests and public demos, by implementing a product-ready Vulkan graphics integration and a real-time Unity streaming rendering solution.

Pioneered a high-performance agent-based model for multi-pathogen spread (SARS-CoV-2, Influenza, RSV, etc.), adopted by researchers at Oxford and McGill, by designing and implementing highly optimized pathogen–pathogen interaction dynamics in synthetic populations.

Co-authored an academic paper under submission to PLOS ONE based on the model I developed, demonstrating research impact, by integrating theoretical design, software implementation, and validation into a publishable scientific study.

Accelerated simulations 7× in Python via data-oriented design and Numba/NumPy/SciPy optimization (vectorization, memory layout, JIT). 

Developed an MLP to classify the MNIST handwritten digits dataset, achieving competitive accuracy.

Designed and evaluated a TensorFlow CNN with varying layer configurations and hyperparameters, comparing performance against the MLP.

Leveraged scikit-learn and pandas for efficient data pre-processing.​​

Code: https://colab.research.google.com/drive/1GpBi0tNFXLun23fmwVl0OOOuhx_RAiRI?usp=sharing

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Results, Analysis and Discussion: https://drive.google.com/file/d/1Ztk0BQLzslB4E88bka__gWVv93E1I4kM/view?usp=sharing

• A turn-based strategy digital board game. Developed in Unity entirely by me (art, game design, programming), apart from the use of some VFX assets and SFX assets. ​

• Local and Online Multiplayer (P2P)

• Singleplayer against AI (minimax, pruning)

• Level editor/creator (play and share levels you make), competitive mode, tutorial mode, steam achievements etc..

• Iterative development with a testing QA team (same as with Roman Triumph)​

• https://store.steampowered.com/app/1517240/CHESS_with_LASERS​​

• Started as a baseline functionality prototype for a stealth FPS hitman game​.​

• FPS controller with realistic weapon animations done by a contracted artist, sounds and visual effects.​

• Weapon customization system with realistic attachments​ which modify behavior of the weapon.

• Focus on creating good game feel​ and realistic gunplay through detailed player feedback (shell casings, smoke etc.)​

• Enemy active ragdoll for realistic hit response with realistic blood visual effects.​​

Founded a profitable studio with $1M+ in revenue, a 6-figure publishing deal, and 70k+ players by shipping Roman Triumph end-to-end as solo founder/developer, with 100k+ lines of code across gameplay and systems.

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• Maintained 88% positive reviews on Steam by rapidly iterating on >2,000 player reports and fixing critical bugs quickly.

• Achieved real-time simulation for 5k+ of agents by implementing multithreaded A* pathfinding, spatial hash-grids, time-slicing, and object pooling with supporting systems including an asynchronous serialization pipeline.

• Scaled content with procedural biome/world generation algorithms, enabling large content variety without handcrafted levels.

Extended a high-timeframe, single-asset DQN trading agent with binary action space to support multi-asset environments and dynamic/variable portfolio allocation.

Designed and conducted experiments to evaluate performance.

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Code, Results, Analysis and Discussion: https://drive.google.com/file/d/1ZlpIJ6kDp1oywYVGyc_KMkkRObDJRGsO/view

• 10 weeks game development competition in an 8-person team.

• Built multiplayer networking for player interactions.

• Developed the AI, animation, UI and gameplay mechanics.​

• Our game was nominated by Ubisoft for one of the awards. ​

• Video: https://www.youtube.com/watch?v=ue97fEyqtLw​

• Note: the team has proceeded to building the game fully without me. The linked video was filmed using the competition's build.

• A simulation and visually representation of the spread of SARS-COV-2 in a store, according to user-specified simulation parameters. A general mathematical framework for estimating risk of airborne transmission of SARS-COV-2 given by the American Institute of Physics was implemented in a 3D real-time virtual setting populated with artificially intelligent shoppers.

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• Developed in Unity entirely by me.

• Makes use techniques such as pooling, cpu time slicing, A* pathfinding, hash grids, finite state machines and more.

• Explanation of  model [link]