Ed Rietman
Interests
Hyper-computer architecture, novel computational systems, computational biology, and applications of graph theory.
Research
Dr. Rietman's research is multidisciplinary, focusing on technical areas that advance artificial intelligence through new computer architecture and super-Turing architecture; and research that advances our understanding of systems biology of human diseases including cancer, neurological diseases, and immunological diseases. Research includes:
- Hardware differentiating neuron circuits
- Optical space singularities in phononic crystals
- Protein target selection for treatment of cancer, epilepsy and SLE
- Challenging customer-driven applications of deep networks
- Oscillatory and reservoir computing architectures and applications
Biography
Dr. Rietman has a Ph.D in physics and multiple undergraduate and masters degrees in other sciences. He worked at Bell Labs for 18 years focusing on solid-state physics, neuromorphic hardware, robotics and computer integrated manufacturing. He also worked at military funded think tanks for 9 years focusing on database mining, applied optics, and applied high-frequency ultrasound. Then he worked at Dana-Farber Cancer Institute and Tufts Medical Center for 5 years, before joining the BINDS Lab in 2014. He is author or coauthor on 150+ technical papers, six books and 30+ patents.
Activities & Awards
Among many research grants, he was awarded the Superior Artificial Intelligence, DARPA funded grant in 2016, and the DARPA funded grant on Programmable matter (2020).
Recent Courses:
- Machine Learning in the Real World: Case Studies
- Novel computer hardware
- Bioinformatics
- The Technological Singularity
- Cellular Automata and Artificial Life
Publications:
https://arxiv.org/abs/1910.10067
https://arxiv.org/abs/1907.10035
https://arxiv.org/abs/1808.03357
https://www.biorxiv.org/content/10.1101/559740v1
https://www.biorxiv.org/content/10.1101/527820v1
https://www.biorxiv.org/content/10.1101/498121v1
https://www.biorxiv.org/content/10.1101/547364v1