Preprint Publications

A. S. Benjamin*, K. Daruwalla*, C. Pehle*, A. Zekri, A. M. Zador, Walking the Weight Manifold: a Topological Approach to Conditioning Inspired by Neuromodulation, preprint, May, 2025. [ pdf ]

K. Daruwalla*, I. N. Martin*, L. Zhang, D. Naglič, A. Frankel, C. Rasgaitis, X. Zhang, Z. Ahmad, J. Borniger, X. H. Hou, Cheese3D: Sensitive Detection and Analysis of WholeFace Movement in Mice, preprint, May, 2025. [ pdf ]

R. S. Raju, K. Daruwalla, M. Lipasti, Accelerating Deep Learning with Dynamic Data Pruning, preprint, November, 2021. [ pdf ]

Conference Publications

Spotlight paper 🔦
A. S. Benjamin, C. Pehle, K. Daruwalla, Continual learning with the neural tangent ensemble, NeurIPS, December, 2024. [ pdf ]

K. Daruwalla, H. Zhuo, C. Schulz, M. Lipasti, BitBench: A Benchmark for Bitstream Computing, Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES '19), June 23, 2019. [ pdf ]

Journal Publications

K. Daruwalla, M. Lipasti, Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates, Frontiers in Computational Neuroscience, May, 2024.
[ link ]

S. Khoram, K. Daruwalla, M. Lipasti, Energy-Efficient Bayesian Inference Using Bitstream Computing, IEEE Computer Architecture Letters, February 2023.

K. Daruwalla, H. Zhuo, R. Shukla, M. Lipasti, BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing, ACM Transcations on Architecture and Code Optimization (TACO), Vol. 16, Iss. 4, No. 43. November 2019. [ pdf ]

K. Daruwalla, N. Olivero, A. Pluger, S. Rao, D.W. Chang, M. Simoni, A quantitative analysis of the performance of computing architectures used in neural simulations, Journal of Neuroscience Methods, Vol. 311. 2019, Pg. 57-66. [ link ]

Workshop Publications

X. Zheng, K. Daruwalla, A. S. Benjamin, D. Klindt, Delays in generalization match delayed changes in representational geometry, UniReps: 2nd Edition of the Workshop on Unifying Representations in Neural Models, December 2024. [ pdf ]

N. Joshi, K. Daruwalla, M. Lipasti, BitFit: Bitstream-Aware Training for Stochastic Neural Networks, Second Workshop on Unary Computing (WUC), April 2024. [ pdf ]

K. Daruwalla, H. Zhuo, M. Lipasti, BitSAD: A Domain-Specific Language for Bitstream Computing, First ISCA Workshop on Unary Computing, June 2019. [ pdf | slides ]

K. Daruwalla, M. Lipasti, Resource Efficient Navigation Using Bitstream Computing, First ISCA Workshop on Unary Computing, June 2019. [ pdf ]

Oral Presentations

Exploiting structure in brains and machines
Invited talk: CSHL Annual Postdoc Retreat, Long Island, NY. Sep. 2025.

Intro. to FluxML and Machine Learning in Julia
Data Umbrella Seminar Series, Online. Jun. 2023. [ YouTube ]

Building Energy-Efficient Computers,
Invited talk: Cold Spring Harbor Lab NeuroAI Seminar, Long Island, NY. Feb. 2022. [ slides ]

BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing,
High-performance Embedded Architecture and Compilation Conference, Bologna, Italy. Jan. 2020.
[ slides ]

Resource Efficient Navigation Using Bitstream Computing,
First ISCA Workshop on Unary Computing, Phoenix, AZ. Jun. 2019. [ slides ]

BitBench: A Benchmark for Bitstream Computing,
Languages, Compilers, and Tools for Embedded Systems, Phoenix, AZ. Jun. 2019. [ slides ]

Seeing Through the FoG: A Biologically Inspired Navigation System,
Industry Affiliates Meeting, Madison, WI. Oct. 2017.

Poster Presentations

Neuromodulation implies a manifold of model weights,
NeuroAI in Seattle 2025, Seattle, WA. Jul. 2025.

Cheese3D: Sensitive Detection and Analysis of Whole-Face Movement in Mice,
Computational and Systems Neuroscience (COSYNE 2025), Montreal, QC. Mar. 2025.

Generative modeling of trained networks as an analogy for neuronal development,
From Neuroscience to Artificial Intelligence (NAISys 2024), Long Island, NY. Sep. 2024.

The dynamics of interpretable 3D facial features reflect hidden neural and physiological states in mice,
Neuronal Circuits, Long Island, NY. Mar. 2024.

A Biologically-Plausible Learning Rule Based on the Information Bottleneck,
Spiking Neural networks as Universal Function Approximators (SNUFA '21). Nov. 2021. [ poster ]

BitBench: A Benchmark for Bitstream Computing,
Languages, Compilers, and Tools for Embedded Systems (LCTES '19), Phoenix, AZ. Jun. 2019.

Seeing Through the FoG: A Biologically Inspired Navigation System,
Industry Affiliates Meeting, Madison, WI. Oct. 2017.

Drone Control with Map-Seeking Circuits,
Industry Affiliates Meeting, Madison WI. Nov. 2016.