Hermann Kumbong

I am a Masters in Computer Science student at Stanford University working at the intersection of Machine Learning and Systems. I am supported by the Wade Scholarship and I am fortunate to be advised by Prof. Chris Ré.

Before Stanford, I spent 2 amazing years at Goldman Sachs London, building low-latency trading systems. I completed my BSc. in Computer Engineering from the Kwame Nkrumah University of Science and Technology, where I was supported by the Mastercard Foundation Scholarship and graduated as the University Valedictorian.

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Research

I'm interested in Machine Learning, Systems and anything at their intersection.

FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores
Daniel Y Fu*, Hermann Kumbong*, Eric Nguyen, Christopher Ré
Under Review at ICLR 2024
Third Workshop on Efficient Natural Language and Speech Processing @ NEURIPS, 2023 (Oral)
Improving Linear Attention via Softmax Mimicry
Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré
Under Review at ICLR 2024
Third Workshop on Efficient Natural Language and Speech Processing @ NEURIPS, 2023 (Oral)
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
Stefano Massaroli*, Michael Poli*, Daniel Y Fu*, Hermann Kumbong, Rom Nishijima Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
Advances in Neural Information Processing Systems (NEURIPS), 2023
GPT-Zip: Deep Compression of Finetuned Large Language Models
Berivan Isik*, Hermann Kumbong*, Wanyi Ning*, Xiaozhe Yao*, Sanmi Koyejo, Ce Zhang
ICML Efficient Systems for Foundation Models Workshop, 2023
On the design and implementation of efficient antennas for high frequency‐radio frequency identification read/write devices
Ernest Ofosu Addo, Benjamin Kommey, Andrew Selasi Agbemenu, Hermann Kumbong,
Engineering Reports, Wiley, 2021

Teaching
Head TA, Systems for Machine Learning (CS 229S), Stanford, Fall 2023
TA, Machine Learning (CS 229), Stanford, Winter 2024
Course Grader: Microprocessors (COE 381) KNUST

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