For the last year, I have been working on building a library of multimodal biological datasets that follows FAIR (findable, accessible, interoperable, reusable) data standards. This project brought up interesting questions about how to set standards for inconsistently labeled data, how to ensure that all data was of high enough quality for analysis, and what levels of abstraction would be helpful for dataset modularity. High quality curation of the raw data, clinical metadata tags, and annotations enables it to be a trustworthy source for ground truth in AI/ML algorithm development as well as serve as a basis for a truly reusable, publicly accessible library.

I also worked on developing image processing tools for large (>500GB) images in Python and performed spatial proteomic analysis on a variety of different tissue types and disease indications for client projects in R.

My academic work was focused on two themes: interactive biotechnology and molecular motor-based active self-assembly/self-organization.

I have worked on systems involving the unicellular protist, Euglena gracilis, as well as systems of E. coli. I have also worked with the molecular protein motor, kinesin-1, and its associated cytoskeletal filament, the microtubule.

I have experience with building optical setups, fluorescence microscopy (TIRF and epifluorescence), microfluidic device fabrication, cell culturing, and genetic transformation of E. coli.

I used these tools to engineer systems of cells or other active components (for example, molecular motors or microrobots), aiming to recreate functions commonly found in natural systems, like filtration, self-assembly, healing, and learning. I found exploring questions about system limits and trade-offs, often as defined by thermodynamics and statistical mechanics, to be the most interesting part of this work.

1. "Spatial proteomics of human diabetic kidney disease, from health to class III." A. Kondo, M. McGrady, D. Nallapothula, H. Ali, A. E. Trevino, A. T. Lam, R. Preska, H. B. D'Angio, Z. Wu, L. N. Lopez, H. K. Badhesha, C. R. Vargas, A. Ramesh, N. Wiegley, S. S. Han, M. Dall'Era, K.-Y. Jen, A. T. Mayer, M. Afkarian, Diabetologia, (2024). [doi]
2. "emObject: domain specific data abstraction for spatial omics." E. A. G. Baker, M. Y. Huang, A. T. Lam, M. K. Rahim, M. H. Bieniosek, B. Wang, N. R. Zhang, A. T. Mayer, A. E. Trevino, bioRxiv, (2023). [doi]
3. "3D Imaging for Cleared Tissues and Thicker Samples on Confocal and Light-Sheet Microscopes." S. L. White, A. T. Lam, H. D. Buck, in Methods in Molecular Biology, 143-161 (2022). [doi]
4. DIY liquid handling robots for integrated STEM education and life science research. E. Li*, A. T. Lam*, T. Fuhrmann, L. Erikson, M. Wirth, M. L. Miller, P. Blikstein, I. H. Riedel-Kruse, PLoS One, 17(11), e0275688 (2022). [doi]
5. Scientific Inquiry in Middle Schools by combining Computational Thinking, Wet Lab Experiments, and Liquid Handling Robots. T. Fuhrmann, D. I. Ahmed, L.Arikson, M. Wirth, M. L. Miller, E. Li, A. T. Lam, P. Blikstein, I. H. Riedel-Kruse, Interaction Design and Children, 444-449 (2021). [doi]
6. Pac-Euglena: A Living Cellular Pac-Man Meets Virtual Ghosts. A. T. Lam, J. Griffin, M. Loeun, N. Cira, S. A. Lee, I. H. Riedel-Kruse, Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-13 (2020). [doi]
7. First-hand, immersive full-body experiences with living cells through interactive museum exhibits. A. T. Lam, J. Ma, C. Barr, S. A. Lee, A. K. White, K. Yu, I. H. Riedel-Kruse, Nature Biotechnology 37(10), 1238-1241 (2019). [doi]
8. Polygonal motion and adaptable phototaxis via flagellar beat switching in the microswimmer Euglena gracilis. A. Tsang, A. T. Lam, I. H. Riedel-Kruse, Nature Physics 14(12), 1216-1222 (2018). [doi]
9. Adaptive non-equilibrium molecular-scale systems with reversibly-bound molecular building blocks. A. T. Lam, S. Tsitkov, Y. Zhang, H. Hess, Nano Letters 18(2), 1530-1534 (2018). [doi]
10. Device and programming abstractions for spatiotemporal control of active micro-particle swarms. A. T. Lam, K. G. Samuel-Gama, J. Griffin, M. Loeun, L. C. Gerber, Z. Hossain, N. J. Cira, S. A. Lee, I. H. Riedel-Kruse, Lab on a Chip 17(8), 1442-1451 (2017). [doi]
    • Listed as a "HOT" article (top 10% score during peer-review)
11. Cytoskeletal motor-driven active self-assembly in in vitro systems. A. T. Lam, V. VanDelinder, A. M. R. Kabir, H. Hess, G. D. Bachand, A. Kakugo, Soft Matter 12(4), 988-997 (2016). [doi]
12. Controlling self-assembly of microtubule spools via kinesin motor density. A. T. Lam, C. Curschellas, D. Krovvidi, H. Hess, Soft Matter 10(43), 8731-8736 (2014). [doi]
13. Modeling negative cooperativity in streptavidin adsorption onto biotinylated microtubules. S. He‡, A. T. Lam‡, Y. Jeune-Smith‡, H. Hess, ‡ indicates equal contribution, Langmuir 28(29), 10635-10639 (2012). [doi]
14. Nanoscale transport enables active self-assembly of millimeter-scale structures. O. Idan, A. T. Lam, J. Kamcev, J. Gonzales, A. Agarwal, H. Hess, Nano Letters 12(1), 240-245 (2012). [doi]

I worked as a postdoctoral scholar in the Riedel-Kruse lab at Stanford University for about 4 years, developing hardware and software platforms for manipulating swarms of unicellular protists. We use these platforms to study programmability of microbial swarms as well as cell behaviors. One of these platforms has even been prototyped as an exhibit at the San Francisco Exploratorium!

For my doctoral studies, I worked in the Laboratory for Nanobiotechnology and Synthetic Biology under the direction of Professor Henry Hess at Columbia University. There, I studied and engineered systems involving the molecular motor kinesin and its associated cytoskeletal filament, the microtubule. In my studies, I use a gliding assay in which kinesin motors are adsorbed to the surface of a glass coverslip and propel microtubules along the surface. Using this system, I explored self-assembly of active systems.