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Dr. Brandon Malone

Senior Researcher

Dr. Brandon Malone (male), is a Senior Researcher in the Biomedical AI group at NEC. His research interests are in the intersection of artificial intelligence and biomedical applications, and in particular in the use of Bayesian methods and graph-based machine learning approaches to address questions in precision medicine and immuno-oncology.

Group Involvement, NEC Laboratories Europe

Biomedical AI Group

Publications

Conferences

  • Anjany Sekuboyina, Daniel Onoro-Rubio, Jens Kleesiek, Brandon Malone, “A Relational-learning Perspective to Multi-label Chest X-Ray Classification,” IEEE International Symposium on Biomedical Imaging, April 2021
  • Brandon Malone, Alberto Garcı́a-Durán and Mathias Niepert, “Learning Representations of Missing Data using Graph Neural Networks for Predicting Patient Outcomes,” 5th International Workshop on Deep Learning on Graphs: Methods and Applications (AAAI Workshop), February 2021
  • Brandon Malone, Alberto Garcı́a-Durán and Mathias Niepert, “Knowledge Graph Completion to Predict Polypharmacy Side Effects,” 13th International Conference on Data Integration in the Life Sciences, November 2018
  • Brandon Malone, Matti Järvisalo and Petri Myllymäki. “Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical Evaluation,” 31st Conference on Uncertainty in Artificial Intelligence, Amsterdam, Netherlands, July 2015. Acceptance Rate: 34%, poster
  • Brandon Malone, Florian Aeschimann , Jieyi Xiong , Helge Grosshans and Christoph Dieterich. “Modeling Ribosome Profiling Data with Bayesian Hidden Markov Models,” 23rd International Conference on Intelligent Systems for Molecular Biology, Dublin, Ireland, July 2015
  • Paul Saikko, Brandon Malone and Matti Järvisalo. “MaxSAT-based Cutting Planes for Learning Graphical Models,” 12th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) techniques in Constraint Programming, Barcelona, Spain, May 2015
  • Brandon Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto and Petri Myllymäki. “Predicting the Hardness of Learning Bayesian Networks,” 28th AAAI Conference on Artificial Intelligence, Quebec City, Canada, July 2014. Acceptance Rate: 28%, oral
  • Xiannian Fan, Changhe Yuan and Brandon Malone. “Tightening Bounds for Bayesian Network Structure Learning,” 28th AAAI Conference on Artificial Intelligence, Quebec City, Canada, July 2014. Acceptance Rate: 28%, poster
  • Xiannian Fan, Brandon Malone and Changhe Yuan. “Finding Optimal Bayesian Network Structures with Constraints Learned from Data,” 30th Conference on Uncertainty in Artificial Intelligence, Quebec City, Canada, July 2014. Acceptance Rate: 32%, 8% oral
  • Jeremias Berg, Matti Järvisalo and Brandon Malone. “Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability,” 17th International Conference on Artificial Intelligence and Statistics, Reykjavik, Iceland, April 2014. Acceptance Rate: 36%, 7% oral
  • Brandon Malone and Changhe Yuan. “Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks,” 29th Conference on Uncertainty in Artificial Intelligence, Bellevue, Washington, USA, July 2013. Acceptance Rate: 31%, 11% oral
  • Srishti Srivastava, Brandon Malone, Nitin Sukhija, Ioana Banicescu and Florina Ciorba. “Predicting the Flexiblity of Dynamic Loop Scheduling Using an Artificial Neural Network,” 12th International Symposium on Parallel and Distributed Computing, Bucharest, Romania, June 2013
  • Brandon Malone and Changhe Yuan. “A Bounded Error, Anytime Parallel Algorithm for Exact Bayesian Network Structure Learning,” 6th European Workshop on Probabilistic Graphical Models, Granada, Spain, September 2012
  • Changhe Yuan and Brandon Malone, “An Improved Admissible Heuristic for Finding Optimal Bayesian Networks,” 28th Conference on Uncertainty in Artificial Intelligence, Catalina Island, California, August 2012. Acceptance Rate: 31%, poster
  • Brandon Malone, Changhe Yuan and Eric Hansen. “Memory-Efficient Dynamic Programming for Learning Optimal Bayesian Networks,” 25th AAAI Conference on Artificial Intelligence, San Francisco, California, August 2011. Acceptance Rate: 25%, 5% oral
  • Brandon Malone, Changhe Yuan, Eric Hansen and Susan Bridges. “Improving the Scalability of Optimal Bayesian Network Learning with Frontier Breadth-First Branch and Bound Search,” 27th Conference on Uncertainty in Artificial Intelligence, Barcelona, Spain, July 2011. Acceptance Rate: 34%
  • Changhe Yuan, Brandon Malone and Xiaojian Wu. “Learning Optimal Bayesian Networks Using A* Search,” 22nd International Joint Conference on Artificial Intelligence, Barcelona, Spain, July 2011. Acceptance Rate: 30%, 17% oral
  • Brandon Malone, Travis Atkison, Martha Kosa and Frank Hadlock. “Pedagogically Effective Effortless Algorithm Visualization with a PCIL,” 39th IEEE International Conference on Frontiers in Education, San Antonio, TX, 2009
  • Brandon Malone and Ambareen Siraj. “Tracking Requirements and Threats for Secure Software Development,” 46th Annual ACM Southeast Regional Conference, Auburn, Alabama, March 2008
  • Michael Baldwin and Brandon Malone. “Utilizing Smart Cards for Authentication and Compliance Tracking in a Diabetes Case Management System,” 46th Annual ACM Southeast Regional Conference, Auburn, Alabama, March 2008
  • Frank Hadlock and Brandon Malone. “The Frequency Median Sequence and its Construction,” International Conference on Artificial Intelligence, Las Vegas, Nevada, pp. 509 – 513, June 2006

Journal papers (accepted)

  • Brandon Malone, Boris Simovski, Clément Moliné, Jun Cheng, Marius Gheorghe, Hugues Fontenelle, Ioannis Vardaxis, Simen Tennøe, Jenny-Ann Malmberg, Richard Stratford and Trevor Clancy. “Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs,” Scientific Reports, accepted. 2020
  • Brandon Malone, Caroline Tosch, Benoit Grellier, Kousuke Onoue, Timo Sztyler, Karola Rittner, Yoshiko Yamashita, Eric Quemeneur and Kaidre Bendjama. “Performance of neoantigen prediction for the design of TG4050, a patient specific neoantigen cancer vaccine,” Cancer Research, vol. 80, no. Supplement 16, Abstract number 4566, 2020
  • Aljoscha Kindermann, Ekaterina Stepanova, Hauke Hund, Nicolas Geis, Brandon Malone and Christoph Dieterich. “MedEx - Data Analytics for Medical Domain Experts in Real-Time,” Studies in Health Technology and Informatics, vol. 267, 2019
  • Shirin Doroudgar, Christoph Hofmann, Etienne Boileau, Brandon Malone, Eva Riechert, Agnieszka A. Gorska, Tobias Jakobi, Clara Sandmann, Lonny Jürgensen, Vivien Kmietczyk, Ellen Malovrh, Jana Burghaus, Mandy Rettel, Frank Stein, Fereshteh Younesi, Ulrike A. Friedrich, Victoria Mauz, Johannes Backs, Günter Kramer, Hugo A. Katus, Christoph Dieterich and Mirko Völkers. “Monitoring Cell Type-Specific Gene Expression Using Ribosome Profiling In Vivo During Cardiac Hemodynamic Stress,” Circulation Research, vol. 125, pp. 431-448, 2019
  • Vivien Kmietczyk, Eva Riechert, Laura Kalinski, Etienne Boileau, Ellen Malovrh, Brandon Malone, Agnieszka Gorska, Christoph Hofmann, Eshita Varma, Lonny Jürgensen, Verena Kamuf-Schenk, Janine Altmüller, Rewati Tappu1, Martin Busch, Patrick Most, Hugo A Katus, Christoph Dieterich and Mirko Völkers. “m6A-mRNA methylation regulates cardiac gene expression and cellular growth,” Life Science Alliance, vol. 2, no. 2, e201800233, 2019
  • Brandon Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto and Petri Myllymäki. “as-asl: Algorithm selection with Auto-sklearn,” Proceedings of Machine Learning Research, Open Algorithm Selection Challenge, vol. 79, pp. 19-22, 2017
  • Brandon Malone, Ilian Atannasov, Florian Aeschimann, Xinping Li, Helge Grosshans and Christoph Dieterich. “Bayesian Prediction of RNA Translation from Ribosome Profiling,” Nucleic Acids Research, vol. 45, pp. 2960-2972, 2017
  • Niklas Jahnsson, Brandon Malone and Petri Myllymäki. “Duplicate Detection for Bayesian Network Structure Learning,” New Generation Computing, vol. 35, pp. 47-67, 2017
  • Aravind Sankar, Brandon Malone, Sion Bayliss, Ben Pascoe, Guillaume Meric, Matthew D. Hitchings, Samuel K. Sheppard, Edward J. Fiel, Jukka Coarander and Antti Honkela. “Bayesian Identification of Bacterial Strains from Sequencing Data,” Microbial Genomics, vol. 2, no. e000075, 2016
  • Niklas Jahnsson, Brandon Malone and Petri Myllymäki. “Hashing-based Hybrid Duplicate Detection for Bayesian Network Structure Learning,” Advanced Methodologies for Bayesian Networks, Lecture Notes in Artificial Intelligence, Springer, vol. 9505, pp. 46 – 50, 2015
  • Nitin Sukhija, Brandon Malone, Srishti Srivastava, Ioana Banicescu and Florina Ciorba, “Portfolio-based Selection of Robust Dynamic Loop Scheduling Algorithms using Machine Learning,” IEEE International Parallel & Distributed Processing Symposium Workshops, IEEE, pp. 1638 – 1647, 2014. Best Paper Award
  • Brandon Malone and Changhe Yuan, “A Depth-first Branch and Bound Algorithm for Learning Optimal Bayesian Networks,” Graph Structures for Knowledge Representation and Reasoning, Lecture Notes in Artificial Intelligence, Springer, vol. 8323, pp. 111 – 122, 2014
  • Changhe Yuan and Brandon Malone. “Learning Optimal Bayesian Networks: A Shortest Path Perspective,” Journal of Artificial Intelligence, vol. 49, pp. 23 – 65, 2013
  • Babi Ramesh Reddy Nallamilli, Jian Zhang, Hana Mujahid, Brandon Malone, Susan Bridges and Zhaohua Peng. “Polycomb Group Gene OsFIE2 Regulates Rice (Oryza sativa) Seed Development and Grain Filling via a Mechanism Distinct from Arabidopsis,” PLOS Genetics, 9(3): e1003322, 2013
  • Zhifa Liu, Brandon Malone and Changhe Yuan, “Empirical Evaluation of Scoring Functions for Bayesian Network Model Selection,” BMC Bioinformatics, vol. 13, suppl.15, 2012
  • Brandon Malone, Feng Tan, Susan Bridges and Zhaohua Peng. “Comparison of Four ChIP-Seq Algorithms Using Rice Endosperm H3K27me3 Profiling Data,” PLoS ONE, 6(9): e25260, 2011
  • William Sanders, Nan Wang, Susan Bridges, Brandon Malone, Yoginder Dandass, Fiona McCarthy, Bindu Nanduri, Mark Lawrence and Shane Burgess. “The Proteogenomic Mapping Tool,” BMC Bioinformatics, vol. 12, no. 115, 2011
  • Brandon Malone, Andy Perkins and Susan Bridges. “Integrating Phenotype and Gene Expression Data for Predicting Gene Function,” BMC Bioinformatics, vol. 10, suppl. 11, 2009
  • Frank Hadlock, Robert Fly and Brandon Malone. “A Comprehensive Problem for Algorithm and Paradigm Visualization,” Journal of Computing Sciences in Colleges, vol. 22, no. 2, pp. 189 – 196, 2006

Connections

LinkedIn:           www.linkedin.com/in/brandon-malone-7015301a/
ResearchGate: www.researchgate.net/profile/Brandon_Malone2
GitHub:             github.com/bmmalone

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