Fitness Tracking Using Machine Vision
Machine vision project with $10000 in venture capital. 
Posts by Collection
portfolio
Off-Grid Compressed Sensing for mmWave Channel Estimation
Sparse signal processing, but without quantization noise! 
Convolutional Encoder - From Theory to Layout
Designing a convolutional encoder from the ground up. 
Working at Intel
One year internship at Intel. 
(Smooth) Fictitious Play in Repeated Games
Numercially and theoretically studying the differences between Fictitious Play and Smooth Fictitious Play. 
Quantum Simulations for Phase Change Memories
Simulations to study new materials for application in phase change memories 
publications
Minimum Feedback for Collision-Free Random Access
Published in IEEE Int. Symp. Inf. Theory (ISIT), 2020
Recommended citation: Kang, J., Yu, W. (2020). " Minimum Feedback for Collision-Free Random Access." IEEE Int. Symp. Inf. Theory.
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Minimum Feedback for Collision-Free Scheduling in Massive Random Access
Published in IEEE Transactions on Information Theory, 2021
Recommended citation: Kang, J., Yu, W. (2021). " Minimum Feedback for Collision-Free Scheduling in Massive Random Access.".
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Scheduling Versus Contention for Massive Random Access in Massive MIMO Systems
Published in IEEE Transactions on Communications, 2022
Recommended citation: Kang, J., Yu, W. (2021). "Scheduling Versus Contention for Massive Random Access in Massive MIMO Systems.".
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Efficiently Computing Sparse Fourier Transforms of q-ary Functions
Published in IEEE Int. Symp. Inf. Theory (ISIT), 2023
Recommended citation: Kang, J., Erginbas*, Y. E., Agzazadeh, A., Ramchandran, K. (2023). "Efficiently Computing Sparse Fourier Transforms of q-ary Functions".
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The Fair Value of Data Under Heterogeneous Privacy Constraints
Published in TMLR, 2024
Recommended citation: Kang, J., Pedarsani, R., Ramchandran, K.. "The Fair Value of Data Under Heterogeneous Privacy Constraints". Transactions on Machine Learning Research, 2024.
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Learning to Understand: Identifying Interactions via the Mobius Transform
Published in Advances in Neural Information Processing Systems (NeurIPS), 2024
Recommended citation: Kang, J.S., Erginbas, Y.E., Butler, L., Pedarsani, R., Ramchandran, K. "Learning to Understand: Identifying Interactions via the Mobius Transform". NeurIPS, 2024.
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SPEX: Scaling Feature Interaction Explanations for LLMs
Published in ICML 2025, 2025
Recommended citation: Kang, J.S., Agarwal, A., Erginbas, Y.E., Butler, L., Pedarsani, R., Ramchandran, K. " SPEX: Scaling Feature Interaction Explanations for LLMs". ICML, 2025.
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ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs
Published in NeurIPS 2025 (Spotlight), 2025
Recommended citation: Butler, L., Agarwal, A., Kang, J.S., Erginbas, Y.E., Yu, B., Ramchandran, K. "ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs". NeurIPS, 2025.
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An Odd Estimator for Shapley Values
Published in Preprint, 2026
Recommended citation: Fumagalli, F., Butler, L., Kang, J.S., Ramchandran, K., Witter, R.T. "An Odd Estimator for Shapley Values". arXiv preprint arXiv:2602.01399, 2026.
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A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior
Published in Preprint, 2026
Recommended citation: Mayne, H., Kang, J.S., Gould, D., Ramchandran, K., Mahdi, A., Siegel, N.Y. "A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior". arXiv preprint arXiv:2602.02639, 2026.
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Adaptive Sparse Möbius Transforms for Learning Polynomials
Published in Preprint, 2026
Recommended citation: Erginbas, Y.E., Kang, J.S., Polito, E., Ramchandran, K. "Adaptive Sparse Möbius Transforms for Learning Polynomials". arXiv preprint arXiv:2602.06246, 2026.
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