Kishan K C

PhD Student in Machine Learning

Rochester Institute of Technology (RIT)

About me

I am a fifth-year Ph.D. candidate in the GCCIS program at the Rochester Institute of Technology (RIT). I am a Graduate Research Assistant at the Lab of Use-Inspired Computational Intelligence (LUCI) under the supervision of Dr. Anne Haake and Dr. Rui Li.

Research
My broad research interests include probabilistic machine learning, network representation learning, link prediction and machine learning for scientific benefit.

Interests

Data Science
Network Representation Learning
Deep Learning
Machine Learning

Education

B.E. in Computer Engineering, 2014

Institute of Engineering, Tribhuvan University

Recent Publications

Joint Inference for Neural Network Depth and Dropout Regularization

Neural Information Processing Systems (NeurIPS) 2021

Kishan KC, Rui Li, Mahdi Gilany

Paper Code

Machine learning predicts nucleosome binding modes of transcription factors

BMC Bioinformatics, 2021

Kishan KC+, Sridevi K. Subramanya+, Rui Li, Feng Cui, (+ indicates equal contribution)

Paper Code

Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021

Kishan KC, Rui Li, Feng Cui, Anne Haake

Paper Code

Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction

25th International Conference on Pattern Recognition, 2021

Kishan KC, Feng Cui, Anne Haake, Rui Li

Paper Code

Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches

BMC Medical Informatics and Decision Making, 2020

Peng-Nien Yin, Kishan KC, Weishi Shi, Qi Yu, Rui Li, Anne R Haake, Hiroshi Miyamoto

Paper

GNE: A deep learning framework for gene network inference by aggregating biological information

BMC Systems Biology, 2019

Kishan KC, Rui Li, Feng Cui, Qi Yu, Anne Haake

Code Poster Paper

Learning topology-preserving embedding for gene interaction networks

17th European Conference on Computational Biology (ECCB) (Poster), 2018

Kishan KC, Rui Li, Feng Cui, Anne Haake

Poster

Experience

June 2021 – September 2021

Sunnyvale, CA

Applied Scientist Intern

Alexa AI, Amazon

Embedding adaptation via transformer-based architecture in open-set few-shot learning

August 2016 – Present

Rochester, New York

Graduate Research Assistant

Lab of Use-Inspired Computational Intelligence, RIT

Scalable biomedical network inference using Network Representation Learning and Neural architecture inference