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layout: about title: About permalink: / subtitle: ML Systems Engineer @ Google Cloud
profile: align: right image: prof_pic.jpg image_circular: false # crops the image to make it circular more_info: > <p>Mountain View, CA</p> <p> Email</p> <p> Resume / CV</p>
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I am an ML Systems Engineer & Researcher at Google Cloud, specializing in hardware-software co-design, distributed accelerator systems, and high-performance inference.
At Google Cloud, I focus on inference optimization of Gemini models across GPUs and TPUs, and previously drove accelerator enablement and scaling analyses for TPU v7 (Ironwood) (Google Cloud Tech Impact Award, 2026).
Earlier, I was an Applied Scientist at AWS architecting GenAI root-cause analysis for Apache Spark at hyperscale (Amazon Q), completed my Ph.D. in Electrical & Computer Engineering at Carnegie Mellon University (CyLab, CIT Dean’s Fellow), and conducted systems research at Microsoft Research (FarmBeats, DeepEdge).
My work spans 15+ publications in top systems and security venues (SIGCOMM, NSDI, USENIX Security), 2 US patents, and systems recognized by GatesNotes, Satya Nadella, and the front page of Hacker News.
(SIGCOMM, NSDI, Security)
(Distributed AI & Sensors)
Features by Tech CEOs
Tech Impact Award
Core Focus
- LLM Inference Optimization: Gemini model serving across GPUs and TPUs, KV-cache optimization, model parallelism, and low-latency runtimes.
- Accelerator Infrastructure & Scaling: TPU v7 (Ironwood) cluster scaling, collective communication, and interconnect bottleneck modeling.
- Systems & Network Security: Active network testing at hyperscale, ML-driven telemetry, and wireless sensing.
555 your office number
123 your address street
Your City, State 12345
layout: about title: About permalink: / subtitle: ML Systems Engineer @ Google Cloud
profile: align: right image: prof_pic.jpg image_circular: false # crops the image to make it circular more_info: > <p>Mountain View, CA</p> <p> Email</p> <p> Resume / CV</p>
news: false # includes a list of news items selected_papers: true # includes a list of papers marked as “selected={true}” social: true # includes social icons at the bottom of the page
announcements: enabled: false # includes a list of news items scrollable: true # adds a vertical scroll bar if there are more than 3 news items limit: # leave blank to include all the news in the _news folder
latest_posts: enabled: false scrollable: true # adds a vertical scroll bar if there are more than 3 new posts items limit: # leave blank to include all the blog posts —
I am an ML Systems Engineer & Researcher at Google Cloud, specializing in hardware-software co-design, distributed accelerator systems, and high-performance inference.
At Google Cloud, I focus on inference optimization of Gemini models across GPUs and TPUs, and previously drove accelerator enablement and scaling analyses for TPU v7 (Ironwood) (Google Cloud Tech Impact Award, 2026).
Earlier, I was an Applied Scientist at AWS architecting GenAI root-cause analysis for Apache Spark at hyperscale (Amazon Q), completed my Ph.D. in Electrical & Computer Engineering at Carnegie Mellon University (CyLab, CIT Dean’s Fellow), and conducted systems research at Microsoft Research (FarmBeats, DeepEdge).
My work spans 15+ publications in top systems and security venues (SIGCOMM, NSDI, USENIX Security), 2 US patents, and systems recognized by GatesNotes, Satya Nadella, and the front page of Hacker News.
(SIGCOMM, NSDI, Security)
(Distributed AI & Sensors)
Features by Tech CEOs
Tech Impact Award
Core Focus
- LLM Inference Optimization: Gemini model serving across GPUs and TPUs, KV-cache optimization, model parallelism, and low-latency runtimes.
- Accelerator Infrastructure & Scaling: TPU v7 (Ironwood) cluster scaling, collective communication, and interconnect bottleneck modeling.
- Systems & Network Security: Active network testing at hyperscale, ML-driven telemetry, and wireless sensing.