ZAC Y.-C. LIU

Causal Reasoning | RL Agents | Data-Centric AI | MLOps | Data Science

About

I’m Zac, a ML researcher and engineer, currently building RL agents with causal reasoning, established causal reflection framework with Abi Aryan (NeurIPS 2025).

Recently I built a ML system to detect supply chain disruption at BrainChain AI. I was also selected as a VC fellow with Laconia Capital.

I previously led R&D and product development, as Head of AI, for an AI delivery and MLOps platform (A360 AI) that abstracts the infrastructure complexity from data scientists.

I ran an open source project AutoDC (automated data-centric processing) that is complimentary to AutoML (see 2021 NeurIPS DCAI).

I have built, led, managed, and mentored multiple cross-functional teams in data science (DS), ML/ software engineering, and product development, providing technical leadership in generative AI, LLM (Large Language Model), MLOps, data-centric AI, innovative use of DS/ ML from ideation to production at scale, mostly with open-ended projects.

I have been serving as an advisor for multiple early stage startups (mostly pre-seed and seed stage), guiding their AI/ ML practices.

I am also holding a research associate position at Stanford University, managing and mentoring for applied ML projects in marina biology, disease ecology, deforestation/ climate change, and remote sensing.

Previously, I built custom ML solutions at Hypergiant, QuantumScape, Driscoll’s, and Monterey Bay Aquarium, in multiple industries, such as commercial space, real-time CRM, solid-state battery manufacturing, supply chain operation, public health, and marine conservation. I also built Kubeflow pipelines on computer vision and NLP components for Google’s AI Hub (now under Vertex AI umbrella).

I have 8+ peer-reviewed applied ML publications and regularly present at top ML conferences (NeurIPS, ICLR, TensorFlow World etc).

My previous research life was in geophysics, earthquake dynamics, and planetary sciences. I built numerical models to simulate ice mountain formation on Saturn's moon Titan and climate patterns inferred from sand dunes on Mars, as well as tsunami propagation caused by mega-earthquakes. My image processing tooling was used to support NASA Cassini Mission, and an improved tsunami simulation code I built has been used to model more tsunami events.

Timeline

12/2024-now: Co-Founder @ Abide AI

11/2017-now: Researcher (ML) @ Stanford University

05/2023-05/2025: Venture Fellow @ Laconia Capital

03/2023-11/2024: Founding ML Engineer @ BrainChain AI

05/2020-03/2023: Senior Data Scientist/ Chief Data Scientist @ A360 AI | Hypergiant

06/2019-05/2020: Data Scientist @ Driscoll's

10/2018-06/2019: ML Engineer @ Google Cloud

05/2017-02/2019: Data Scientist @ Monterey Bay Aquarium

08/2013-06/2016: Research Scientist @ Smithsonian | NASA joint contract

08/2010-08/2014: Researcher @ NASA Cassini RADAR Team

Talks

Press Coverage

ML Research

Github and Google Scholar.

My current work focus on building a new type of neurosymbolic architecture that can solve out-of-distribution (OOD) problem in agentic systems, utilizing dynamic RL environment to train agents to be adaptive and capable of self-reflection (see Abide AI blog posts).

Recent/ Past Works

I built an open source data-centric AI tooling, AutoDC (Automated data-centric processing) that aims to automate dataset improvement process. We tested the framework on image data and AutoDC is estimated to reduce roughly 80% of the manual time for data improvement tasks, at the same time, improve the model accuracy by 10-15% with the fixed ML code. We want to expand to NLP and tabular data, open for contributors; check our NeurIPS paper.

Enterprise product development

ML pipeline/ Kubeflow component contributions

Applied ML | Data science

I led DS teams to build custom ML solutions and data science use cases to support industry partners and clients as well as academic institutions.

Industry

Domain supported: commercial space, CRM, manufacturing sensory and imagery, supply chain operation, oil and gas, sustainable agriculture.

Academia

Domain supported: remote sensing, marine biology and conservation, disease ecology, deforestation/ climate change, and geophysics/ planetary science.

Peer-reviewed Publications

ML (Applied ML, AI Research)

  1. Aryan, A. Liu, Z.Y.-C. Causal Reflection with Language Models. NeurIPS (2025), arXiv:2508.04495.
  2. Chamberlin, A.J., Liu, Z.Y.-C., Cross, C.G.L., Pourtois, J. et al. High-Resolution Canopy Height Mapping in Tropical Rainforests Using Deep Learning and Multi-Source Remote Sensing Data. Remote Sensing (2025), doi: 10.3390/rs17213592.
  3. Jerette, J., Liu, Z.Y.-C., Chimote, P., Hastie, T., Fox, E., and Ferretti, F. Shark detection and classification with machine learning. Ecological Informatics (2022), doi: 10.1016/j.ecoinf.2022.101473.
  4. Liu, Z.Y.-C., Chamberlain, A.J., Tallam, K., Jones, I.J., Lamore, L.L., Bauer, J. et al. Deep Learning Segmentation of Satellite Imagery Identifies Aquatic Vegetation Associated with Snail Intermediate Hosts of Schistosomiasis in Senegal, Africa. Remote Sensing, SI: Remote Sensing and Infectious Diseases (2022), 10.3390/rs14061345b.
  5. Liu, Z.Y.-C., Roychowdhury, S., Tarlow, S., Nair, A., Badhe, S., and Shah, T. AutoDC: Automated data-centric processing. NeurIPS (2021), arXiv:2111.12.
  6. Liu, Z.Y.-C., Tarlow, S., Akbar, M., Donnellan, Q., and Senkow, D. Improved orbital propagator integrated with SGP4 and machine learning. SmallSat 2021, paper link.
  7. Tallam, K., Liu, Z.Y.-C., Chamberlin, A.J., Jones, I.J., Shome, P., Riveau, G., Ndione, R.A. et al. Identification of Snails and Schistosoma of Medical Importance via Convolutional Neural Networks: A Proof-of-Concept Application for Human Schistosomiasis. Frontiers in Public Health (2021): 900, doi: 10.3389/fpubh.2021.642895.
  8. Liu, Z.Y.-C., Moxley, J.H., Kanive, P., Gleiss, A.C., Maughan, M., Bird, L., Jewell, O. et al. Deep learning accurately predicts white shark locomotor activity from depth data. Animal Biotelemetry 7, no. 1 (2019): 1-13, doi: 10.1186/s40317-019-0175-5.

Science (Geophysics, Planetary Science, Climate Change)

  1. Jones, I.J., MacDonald, A.J., Hopkins, S.R., Lund, A.J., Liu, Z.Y.C., Fawzi, N.I., Purba, M.P., Fankhauser, K., Chamberlin, A.J., Nirmala, M. and Blundell, A.G. Improving rural health care reduces illegal logging and conserves carbon in a tropical forest. Proceedings of the National Academy of Sciences (2022), 117(45), pp.28515-28524, doi.org/10.1073/pnas.2009240117.
  2. Liu, Z.Y.-C., Radebaugh J., Harris, R., Christiansen, E.H, and Rupper, S. Role of fluids in the tectonic evolution of Titan. Icarus (2016) (SI: Titan's Surface and Atmosphere), 270, 2-13, doi: 10.1016/j.icarus.201_6.02.016.
  3. Radebaugh, J., Ventra, D., Lorenz, R.D., Farr, T. Kirk, R.L., Hayes, A., Malaska, M., Birch, S., Liu, Z.Y.-C., Lunine, J., Barnes, J., Le Gall, A., Lopes, R.M.C., Stofan, E., Wall, S., Paillou, P., and Wood, C.A. Alluvial and fluvial fans on Saturn’s moon Titan reveal processes, materials and regional geology. In, Ventra, D. & Clarke, L. E. (eds) Geology and Geomorphology of Alluvial and Fluvial Fans: Terrestrial and Planetary Perspectives. Geological Society, London, Special Publications (2016), 440, doi: 10.1144/SP440.6.
  4. Liu, Z.Y.-C., Radebaugh J., Harris, R., Christiansen, E.H, Kirk, R.L., Neish, C.D.,Lorenz, R.D., and the Cassini Radar Team. The tectonics of Titan: Global structural mapping from Cassini radar. Icarus (2016) (SI: Titan's Surface and Atmosphere), 270, 14-29, doi: 10.1016/j.icarus.2015.11.021.
  5. Liu, Z.Y.-C. and Zimbelman, J.R. Recent near-surface wind directions inferred from mapping sand ripples on Martian dunes. Icarus (2015), 261, 169-181, doi: 10.1016/j.icarus.2015.08.022.
  6. Liu, Z.Y.-C. and Hargitai H. Mountain (Titan). (2014) In: A. Kereszturi and H. Hargitai (Eds), Encyclopedia of Planetary Landforms, Springer-Verlag Berlin Heidelberg, Germany, doi: 10.1007/978-1-4614-9213-9_508-1.
  7. Liu, Z.Y.-C. and Harris, R. Discovery of Possible Mega-Thrust Earthquake along the Seram Trough from Records of 1629 Tsunami in Eastern Indonesian Region. Natural Hazards (2013) (SI: Extreme Geohazards), 72(3), 1311-1328, doi: 10.1007/s11069-013-0597-y.

Get In Touch

I’m best reached via email (zacqoo at gmail dot com) and open to interesting collaboration.