tags:
- machine-learning
- ml-systems
- robust-ml
- llm-inference
- computer-vision
Aman Singh
ML Systems Engineer · Robust ML · GPU Inference · LLM Systems
I build reliable machine-learning systems across training, evaluation, inference, and secure deployment.
Hub highlights
| Type | Resource | What it shows |
|---|---|---|
| Space | Viyog OOD-vs-ADV Leaderboard | Interactive evaluation for separating adversarial and out-of-distribution inputs |
| Dataset | viyog-adversarial | Adversarial/OOD evaluation data for reproducible robustness experiments |
| Model | Cifar100_Finetuned | Fine-tuned vision model checkpoint and evaluation artifacts |
| Model | viyog-weights | Viyog research weights for robust input-separation experiments |
| Model | ViT-Base checkpoint | Vision Transformer checkpoint for downstream experiments |
Research
Viyog: Separating Adversarial and Out-of-Distribution
Accepted at ESWEEK CODES 2026.
Viyog studies how intermediate-representation geometry can separate adversarial inputs from out-of-distribution inputs. This Hub profile contains the accompanying models, dataset, and live evaluation Space.
Engineering focus
- Robust ML: adversarial evaluation, out-of-distribution detection, representation geometry, and reproducible PyTorch experiments.
- GPU systems: H100 training with DDP and FP16/BF16, FSDP checkpointing, and sub-10 ms A6000 inference.
- LLM infrastructure: model integration, streaming tool calls, bounded concurrency, vLLM rollout networking, and evaluation.
- Secure execution: Rust sandboxing, Windows AppContainer/LPAC confinement, and Linux filesystem isolation.
Open-source systems work
Contributions across SGLang, VERL, Megatron-LM, PyTorch AO, LLVM/MLIR, and arapuca, including KV/radix-cache correctness, FSDP checkpoint integrity, pipeline-parallel execution, FP8/quantization, compiler correctness, and sandbox isolation.
Background
- Arizona State University, MPS Lab — Graduate Researcher · Tempe, Arizona
- Amazon — Software Development Engineer · Bangalore, India
Education
- M.S. in Computer Engineering — Arizona State University, 2024–2026
- B.Tech in Electrical and Electronics Engineering — National Institute of Technology Karnataka, 2018–2022
Toolkit
PyTorch · CUDA · DDP/FSDP · SGLang · vLLM · Transformers · Python · C++ · Rust · Go · Linux · Docker · Kubernetes · AWS · Google Cloud
Connect
For robust ML, GPU systems, LLM infrastructure, or research engineering: email me or connect on LinkedIn.