Simi Kang

About

Simrat Anne Kaur Kang is an Assistant Professor in Asian American Studies at the University of Illinois. Her research focuses on themes such as political ecology, violence, feminist and collaborative methodologies, and environmental entanglements within Asian American contexts. Kang's scholarly work explores complex forms of reckoning and the intersections of arts and humanities with ecological and social justice issues. She has contributed to the academic discourse through various peer-reviewed articles, chapters, and editorial work, including editing a special issue on Environmental Entanglements in Asian America for the Journal of Asian American Studies. Kang's research also engages with topics of refugee resilience, mutual aid, abolition, and transnational feminisms, reflecting a commitment to antiracist and decolonizing feminist praxis. Her interdisciplinary approach integrates cultural, environmental, and political dimensions to address pressing social issues affecting Asian American communities.

Research topics

• Computer Science
• Artificial Intelligence
• Metallurgy
• Chemistry
• Inorganic chemistry
• Organic chemistry
• Materials science
• Nanotechnology
• Physical chemistry
• Botany

Selected publications

• Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays

  arXiv (Cornell University) · 2022-06-26 · 3 citations

  preprintOpen accessSenior author

  We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger naturally arising voltage spikes. These spikes emitted by memristive dynamics are analog in nature, and thus fully differentiable, which eliminates the need for surrogate gradient methods that are prevalent in the spiking neural network (SNN) literature. Memristive neural networks typically either integrate memristors a…

  PublisherOA PDFDOI

• A Fully Memristive Spiking Neural Network with Unsupervised Learning

  arXiv (Cornell University) · 2022-03-02 · 1 citations

  preprintOpen accessSenior author

  We present a fully memristive spiking neural network (MSNN) consisting of physically-realizable memristive neurons and memristive synapses to implement an unsupervised Spiking Time Dependent Plasticity (STDP) learning rule. The system is fully memristive in that both neuronal and synaptic dynamics can be realized by using memristors. The neuron is implemented using the SPICE-level memristive integrate-and-fire (MIF) model, which consists of a minimal number of circuit elements necessary to achie…

  PublisherOA PDFDOI

• SPICEprop: Backpropagating Errors Through Memristive Spiking Neural Networks

  arXiv (Cornell University) · 2022-03-02 · 1 citations

  preprintOpen accessSenior author

  We present a fully memristive spiking neural network (MSNN) consisting of novel memristive neurons trained using the backpropagation through time (BPTT) learning rule. Gradient descent is applied directly to the memristive integrated-and-fire (MIF) neuron designed using analog SPICE circuit models, which generates distinct depolarization, hyperpolarization, and repolarization voltage waveforms. Synaptic weights are trained by BPTT using the membrane potential of the MIF neuron model and can be p…

  PublisherOA PDFDOI

• The rectangle condition does not detect the strong irreducibility

  ArXiv.org · 2025-09-15

  preprintOpen access

  The rectangle condition for a genus $g$ Heegaard splitting of a 3-manifold, defined by Casson and Gordon, provides a sufficient criterion for the Heegaard splitting to be strongly irreducible. However it is unknown whether there exists a strongly irreducible Heegaard splitting which does not satisfy the rectangle condition. In this paper we provide a counterexample of a genus 2 Heegaard splitting of a 3-manifold which is strongly irreducible but fails to satisfy the rectangle condition. The way…

  PublisherOA PDFDOI

• Design Optimization to Secure Multiple Arcing Time Interruption Performance of Self-Blast Gas Circuit Breakers

  The Transactions of The Korean Institute of Electrical Engineers · 2024-06-18

  article

  Recently, the focus has been on the development of self-blast gas circuit breakers with low operating force and compact design. The self-blast gas circuit breaker uses the high-temperature energy from the arc to nozzle ablation and increase the pressure in the heating chamber. In order to predict the interruption performance of a developed product, heat gas flow analysis is essential and must be accompanied by judgment criteria according to test type. In this paper, based on short line fault (SL…

  PublisherDOI

Frequent coauthors

• Yusuf Leblebici

  Sabancı Üniversitesi

  24 shared

• Yongmo Kim

  Hanyang University

  17 shared

• J.J. Morikuni

  University of Illinois Urbana-Champaign

  14 shared

• K. W. Kim

  Daegu Gyeongbuk Institute of Science and Technology

  13 shared

• Chin-Chi Teng

  Cadence Design Systems (United States)

  11 shared

• C.H. Diaz

  Taiwan Semiconductor Manufacturing Company (United States)

  11 shared

• Sachin S. Sapatnekar

  11 shared

• Seong‐Ook Jung

  Yonsei University

  10 shared

Awards & honors

• Doctoral Dissertation Fellowship, Graduate School, Universit…
• Global Food Security Fellowship, Interdisciplinary Center fo…
• Excellence in Teaching Faculty Award recipient, Bard Early C…
• Multicultural Research Award recipient, Institute for Divers…
• Graduate Research Partnership Fellow, Dept. of Gender, Women…

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