Sudeshna Das holds a Bachelor of Technology degree from the Indian Institute of Technology at Kharagpur and a Ph.D. in biomedical engineering from Boston University. She has worked in bioinformatics and computational biology for over 10 years. As a graduate student, she developed novel methods for protein domain and function identification using graph-theoretic approaches and prior based profiles. After graduate school, she worked at a leading biopharmaceutical company directing computational and software development projects. There she and her colleagues developed novel approaches for statistical analysis of drug-discovery and pre-clinical data. Her research interests include design of interoperable bioinformatics databases and tools, along with analysis of complex biomedical data using statistical (particularly non-parametric) and data-mining techniques. She also has wide experience in developing large-scale software for drug discovery and development. Currently, she is collaborating with the Harvard Stem Cell Institute to develop a reusable collaboration framework for scientific communities.

Paolo Ciccarese is an Instructor at the Harvard Medical School and Assistant in Neurology at the Mass General Hospital. He holds a M.S. in Computer Science and he started his career as freelance consultant in knowledge management software development. Soon after, Paolo received a PhD in Bioengineering and Bioinformatics from the University of Pavia, Italy, where he was also a teaching assistant for five years in courses on the subjects of artificial intelligence in medicine and object orientation programming. After completing his PhD, he became a research fellow in neurology at the Mass General Hospital/Harvard Medical School as well as a research fellow in medical informatics at the University of Pavia.

Paolo matured a eight year experience in formal representation of computerized clinical practice guidelines. He designed and co-developed a guideline based decision support system named Guide, which combines guideline decision support with the power of clinical workflow management systems. Guide has been implemented for patients suffering from heart failure and several types of cancers. He has been involved in the design and development of data/knowledge management systems for rare pathologies and, in particular, in the first architectural design of the Italian Network for Amyloidosys, which comprehends an electronic patient record shared across the hospitals belonging to the network.

Paolo co-developed the rdf visualizer Welkin for the SIMILE project and founded the JDPF (Java Data Processing Framework) project, a modular and extendable open source infrastructure for processing big quantities of eterogeneus data.