I am a researcher specializing in machine learning for gaming, on-device AI, and ML model optimization. Currently at Qualcomm working on ML on edge for gaming (2025–present), previously at Activision on ML-based anti-cheat systems (2022–2025). I hold an MS in Electrical Engineering from the University of Washington and an MS in Data Science from Plaksha University.
| Platform | ID / Link | Purpose |
|---|---|---|
| Google Scholar | PH5u7jIAAAAJ | Publications & citations |
| ORCID | 0009-0002-1103-3441 | Researcher identifier |
| OpenReview | ~Mathew_Varghese1 | ML/AI conference reviews & submissions |
| Microsoft CMT | mathewvarghesemanu@gmail.com | Conference management & paper submissions |
Full publication list: Google Scholar profile.
AI Level of Detail (AI LOD): using distance-aware neural-network quantization as a level-of-detail axis for real-time NPC motion prediction. FP32/FP16/INT8 ONNX tiers routed by camera distance — up to 9.79x faster inference with no perceptible quality loss.
In association with HRS
In association with UC Berkeley
A smart home automation system with the solar inverter presented as the final thesis at engineering college