cs @ johns hopkins.
interested in efficient llm inference, rag, preference optimization, and ml systems.

co-first author on conformal thinking, accepted at icml 2026.

currently thinking about compute-aware reasoning, temporal rag, and data quality for post-training.

making llms lazy in a good way
conformal thinking — risk control for reasoning on a compute budget.
accepted at icml 2026.
arxiv

retrieval that remembers time
temporal-aware rag over non-stationary document collections.
time-aware indexing, retrieval freshness, and hallucination detection.

teaching a toxicity filter using reddit votes
preference optimization for context-dependent toxicity classification.

conformal thinking: risk control for reasoning on a compute budget
accepted at icml 2026 · arxiv

privacy-preserving video analytics through gan-based face de-identification
nmitcon 2024 · paper

toxic comment detection using bidirectional sequence classifiers
idciot 2024 · paper

harnessing insights from streams: unlocking real-time data flow with docker and cassandra in the apache ecosystem
raics 2024 · paper

prism: predictive resource inference and spot instance management
iconat 2024 · paper

a streamlined approach towards monkeypox detection
preprint · paper

preserving privacy in video analytics: a comprehensive review of face de-identification and background blurring techniques
preprint · paper

a lightweight approach towards speaker authentication systems
preprint / work in progress · paper

python · pytorch · tensorflow · hugging face · langchain · vllm
rag · inference optimization · preference optimization · calibration
docker · kubernetes · aws · spark · airflow
postgresql · mongodb · cassandra

jhu dsai
graduate research assistant — compute-aware reasoning and post-training data quality.

jhu clsp
graduate researcher — temporal rag and hallucination detection.

mastek
ml engineer intern — voice authentication and production inference.

website · google scholar · linkedin ·