Machine Learning Researcher at Apple

Yancheng Wang

I work on LLM reasoning and agents, LLM post-training, multimodal learning (image, text, and audio), efficient and robust deep learning, model compression, generative models, and graph learning.

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News

  • [2026/6]Two papers accepted to UAI 2026.
  • [2026/5]Awarded Gold Reviewer at ICML 2026.
  • [2026/5]Started as a Machine Learning Researcher at Apple.
  • [2026/5]One paper accepted to ICML 2026.
  • [2026/4]One paper accepted to ACL 2026.
  • [2026/2]Two papers accepted to ICLR 2026.

Biography

Yancheng Wang is a Machine Learning Researcher at Apple, where he works on multimodal LLMs and reasoning agents. He recently completed his Ph.D. in Computer Science at School of Computing and Augmented Intelligence, Arizona State University. His research focuses on LLM reasoning and agents, LLM post-training, multimodal learning (image, text, and audio), efficient and robust deep learning, and generative models. He has research experience at Meta Superintelligence Labs, Amazon AWS AI, Amazon Alexa AI, and Kuaishou U.S. R&D Center. His work has been published in leading venues including ICML, ICLR, NeurIPS, ACL, TPAMI, IJCV, UAI, NAACL, and AAAI.

Research Interests

  • LLM Reasoning & Agents
  • LLM Post-Training
  • Multimodal Learning (Image, Text, and Audio)
  • Computer Vision
  • Efficient & Robust Deep Learning
  • Model Compression
  • Deep Generative Models
  • Graph Learning

Industrial Experience

  • Apple logoApple · Machine Learning Researcher 2026 May - Now

    Working on reasoning and post-training of multimodal LLMs.

  • Meta logoMeta Superintelligence Labs (MSL) · Research Scientist Intern 2025 May - 2025 Aug

    Worked on LLM post-training and multimodal learning.

  • Amazon logoAmazon AWS AI · Applied Scientist Intern 2024 May - 2024 Aug

    Worked on automatic evaluation of LLM-powered agents in conventional scenarios.

  • Alexa logoAmazon Alexa AI · Applied Scientist Intern 2023 May - 2023 Aug

    Worked on LLM-powered autonomous agents for general-purpose recommendation.

  • Kuaishou logoKuaiShou U.S. R&D Center · Research Intern 2021 May - 2021 Aug

    Worked on neural architecture search for image reconstruction.

Publications

2026
Preprint
GSRM: Generative Speech Reward Model for Speech RLHF

Maohao Shen, Tejas Jayashankar, Osama Hanna, Naoyuki Kanda, Yancheng Wang, Kateřina Žmolíková, Ruiming Xie, Niko Moritz, Anfeng Xu, Yashesh Gaur, Gregory Wornell, Qing He, Jilong Wu

arXiv preprint arXiv:2602.13891, 2026

2025
DASFAA
Declarative Privacy-Preserving Inference Queries

Hong Guan, Ansh Tiwari, Summer Gautier, Rajan Hari Ambrish, Lixi Zhou, Deepti Gupta, Yancheng Wang, Yingzhen Yang, Chaowei Xiao, Kanchan Chowdhury, Jia Zou

International Conference on Database Systems for Advanced Applications (DASFAA) Demo, 2025

2024
2023

Service

Program Committee & Reviewer

ICML 2023 - 2026 (Awarded Gold Reviewer for ICML 2026)

NeurIPS 2023 - 2026

ICLR 2023 - 2026

NeurIPS 2022, SIGKDD 2022, AAAI 2022, ICML 2022, IJCAI 2022

TPAMI, IJCV