Aakash Kaku
I'm a Senior Software Engineer at Google DeepMind and a Ph.D. graduate from the NYU Center for Data Science at the Courant Institute of Mathematical Sciences, where I was co-advised by Prof. Carlos Fernandez Granda, Prof. Narges Razavian, and Prof. Heidi Schambra. My research and engineering focus lies in developing cutting-edge machine learning systems, particularly in healthcare and multilingual LLMs.
At Google, I contributed to Bard, Google Assistant, and Gemini LLMs. At NYU, my doctoral research focused on using deep learning and wearable sensors to quantify and optimize neuro-rehabilitation for stroke patients.
Contact: ark576[at]nyu.edu. Google Scholar | Resume
Work Experience
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Senior Software Engineer, Google DeepMind
Nov 2024 – Present- Led Gemini for education visual learning initiative; boosted student engagement with novel visual learning tools.
- Built a multilingual tool-routing system; increased API success and reduced TPU costs.
- Developed RAG-based multilingual query generation for Search to mitigate LLM hallucinations.
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Software Engineer, Google
Dec 2023 – Nov 2024- Advanced RLHF post-training for non-English LLMs (RLXF, IPO methods).
- Built scalable reward model pipelines and auto-eval systems for international LLM deployment.
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Research Intern, Google Research
Jun 2023 – Aug 2023- Improved multilingual reward models (for Bard) and semantic parsing of LLMs (for Assistant).
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Intern, Philips Research NA
May 2022 – Aug 2022- Detected acoustic shadows in ultrasound using weak supervision segmentation models; reduced radiologist burden by 85%.
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Strategy Analyst, Accenture Consulting
May 2016 – Aug 2017- Saved $3M for a Fortune 100 client with a custom NLP automation tool.
- Advised chemical sector M&A execution during due diligence.
Education
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New York University - Center for Data Science (Courant)
Ph.D. in Data Science (Sept 2019 – Dec 2023) -
New York University - Center for Data Science (Courant)
MS in Data Science (Sept 2017 – May 2019) -
Indian Institute of Management Bangalore
PGDM (equivalent to MBA), Top 5% (Jun 2014 – Mar 2016) -
Institute of Chemical Technology, Mumbai
B.Tech in Chemical Engineering, Top 10% (Aug 2010 – May 2014)
Research / Publications
- Gemini: A Family of Multimodal Models – Contributed to Google's flagship multimodal system [ArXiv]
- Stroke Rehabilitation with Wearables – Developed ML methods to quantify rehab for stroke patients [Nature npj Digital Medicine]
- Brain Segmentation and Cartilage Detection – Pioneered techniques in MR segmentation at NYU [ArXiv]
- Intermediate Layers in Contrastive SSL – Published at NeurIPS 2021 [ArXiv]
- COVID-19 Prediction in ER – Developed calibrated probablistic curves for patient triage [Nature npj Digital Medicine]
Teaching
- Mathematical Tools for Data Science – NYU CDS (TA & Grader, Spring 2021)
- Deep Learning for Medicine – NYU Med School (TA, Spring 2019)
- Quantitative Methods 2 – IIM Bangalore (TA, 2015)