Tomasz Arodz, Ph.D.
Associate Professor VCU College of Engineering
- Engineering East Hall, Room E4252, Richmond VA
Dr. Arodz's research focuses on machine learning and bioinformatics
Social
Biography
Industry Expertise
Areas of Expertise
Accomplishments
Researcher of the Year 2020
2020-01-01
VCU Computer Science Department
NSF CAREER Grant Award
2015-01-01
National Science Foundation
Prime Minister of Poland Award
2008-01-01
Laureate of the Award for Ph.D. Dissertation
Foundation for Polish Science Scholarship
2006-01-01
Laureate of the Young Researcher Scholarship
Education
AGH University of Science and Technology
Ph.D.
Computer Science
2007
AGH University of Science and Technology
M.S.
Computer Science
2003
Jagiellonian University
M.S.
Biotechnology
2009
Media Appearances
To Relieve Holiday Stress, Techies Trot Out Artificial Intelligence
Style Weekly print
2017-12-19
By now the journey to 2018 can feel more like a crawl than a mad dash.
There's pressure to entertain family, reconnect with old friends and take that special someone on a memorable date. But a Richmond startup says artificial intelligence can solve the indecision over where to go and what to do. While some experts caution against placing exaggerated faith in artificial intelligence, early adopters are hoping for a more perfect holiday experience.
. . . Just remember, if you're struggling to plan a not-so-silent night, don't give up on your gut, says Tom Arodz, another VCU professor who studies machine learning.
"AI may learn to never recommend a symphony to heavy-metal lovers," Arodz says. "But just like with human instinct, it is often difficult to say why any particular recommendation is made."
Selected Articles
Real-valued group testing for quantitative molecular assays
Conference on Research in Computational Molecular Biology RECOMB'2022We proposed a new group testing approach tailored for scenarios where quantitative measurements are available (e.g. Ct values in PCR tests). It allows using much fewer tests than there are samples to be tested.
The vaginal microbiome and preterm birth
Nature Medicine 25:1012-1021, 2019As part of a large microbiome study by VCU cMEDA team, we created a machine learning model to quantify effects of human microbiome composition on pregnancy outcomes.
Approximation capabilities of Neural ODEs and Invertible Residual Networks
International Conference on Machine Learning ICML'2020We used techniques from topology (embedding of homeomorphisms into flows) to analyze whether two popular recent architectures for creating invertible deep nets, neural ordinary differential equations and invertible ResNets, have the capability to model arbitrary invertible function.
Quantum semi-supervised kernel learning
Quantum Machine Intelligence 3:1-11, 2021We formulated and analyzed a quantum machine learning algorithm for training semi-supervised SVM based on quantum HHL/LMR protocol.
Shapeshifter: a parameter-efficient Transformer using factorized reshaped matrices
Conference on Neural Information Processing Systems NeurIPS'2021We designed a technique for reducing the size of embedding matrices and self-attention weight matrices in deep Transformer-based language models using a much more compact yet expressive representation based on Kronecker/tensor products.
