Sercan O. Arik
Sercan Arik is a Research Scientist at Google Cloud AI. Motivated by the mission of democratizing AI and bringing it to the most impactful use cases (from Healthcare, Finance, Retail, Media, Education, Communications and many other industries), he works on making AI high-performance for the most-demanded data types, interpretable, fair, data-efficient, robust and reliable.
Before joining Google, he was a Research Scientist at Baidu Silicon Valley AI Lab. At Baidu, he focused on deep learning research, particularly for applications in human-technology interfaces. He co-developed state-of-the-art speech synthesis, keyword spotting, voice cloning, and neural architecture search systems. Prior to Baidu, he completed a PhD degree in Electrical Engineering at Stanford University in 2016. He has co-authored more than 50 journal and conference publications.
Authored Publications
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Google
From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation
Han Zhou
Ke Jiang
International Conference on Learning Representations (ICLR) (2025) (to appear)
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction
Somesh Jha
Transactions on Machine Learning Research (TMLR) (2024)
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL
Satya Gundabathula
Hanjun Dai
TMLR (2024)
Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
Advances in Neural Information Processing Systems (NeurIPS) (2024)
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch
Chun-Liang Li
Kihyuk Sohn
Transactions on Machine Learning Research (TMLR) (2023)
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs
Somesh Jha
Findings of the Association for Computational Linguistics: EMNLP (2023)
