About me

I'm a Machine Learning Engineer and Data Scientist with over 4 years of experience building impactful AI solutions. As a Computer Science graduate from USC specializing in AI, I've developed deep expertise in natural language processing, computer vision, and AI infrastructure development. Throughout my career spanning startups, research labs, and industry, I've focused on translating complex technical concepts into practical solutions that drive business value. My passion for innovation and research has led to more than 20 publications in top-tier conferences and journals, garnering over 700 citations on Google Scholar. I thrive on tackling challenging problems at the intersection of cutting-edge AI technology and real-world applications.
Conferences/Workshops: ICLR, ACL, NeurIPS, WACV, ECML, KCap, CODS-COMAD, GLOBECOM, MOBICOM, etc. Journals: IEEE Internet of Things, Elsevier Future Generation Computer Systems, IEEE Transactions on Network and Service Management, etc.
I am deeply passionate about advancing the frontiers of Artificial Intelligence and Machine Learning, constantly exploring cutting-edge developments and innovative approaches. This intellectual curiosity drives me to not only master new technologies but also effectively bridge gaps between technical and business domains. My strong communication skills and collaborative mindset have enabled me to successfully lead cross-functional teams and deliver high-impact projects. I take pride in fostering an inclusive environment that encourages knowledge sharing and collective growth, having mentored junior engineers and contributed to building robust AI solutions that directly address business challenges.
To give back to the community, I write articles detailing things I have learned and post them on Medium. If you are a data science aspirant, please check out my Medium account.
Skills
- Programming Languages: Python, C++, R, Matlab, SQL
- Development Tools: HTML, CSS, Javascript, Angular, NodeJS, SwiftUI
- Machine Learning & Deep Learning Frameworks: PyTorch, Tensorflow, Keras, ONNX, HuggingFace, NLTK, OpenCV, Spacy, LangChain, Scikit-learn, Flask, PySpark, MLFlow
- Tools: Databricks, Weights & Biases (wandb), Jenkins, Gradio, Git, Docker, OpenVINO, SonarQube, Postman, Google Analytics
- Cloud Platforms: AWS (EC2, S3, Lambda, SageMaker, RDS) and GCP (Compute Engine, Cloud Storage, Cloud Functions, BigQuery)
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