John Vu is the Director of the M.S. in Biotechnology Innovation and Computation program as well as Distinguished Career Professor in the School of Computer Science. John was a Chief Engineer and Technical Fellow (retired) at The Boeing Company where he led several successful programs including the integration of computer design systems for the 777, IT integration into Lean Manufacturing and various company wide software improvement initiatives. John has over 35 years of experience in software and systems development and has managed several large-scale integration programs in which the final products required the integration of in-house components with commercial off-the shelf products and outsourced suppliers.
John has participated in the development of several Capability Maturity Models (CMMIs) at the Software Engineering Institute (SEI) and authored the software e-commerce model and the procurement model. He was a member of the IEEE Software Industry Advisory Board and has written many books and articles on software project and program management.
John received master's degrees from Carnegie Mellon University and the University of Nevada in addition to undergraduate degrees from Ohio University and Seattle Pacific University. He is also a lecturer at Carnegie Mellon Silicon Valley, Seattle University, the Korean Advanced Institute of Science and Technology and Tsinghua University.
Ravi Starzl, Program Co-Director
Dr. Ravi Starzl specializes in the computational analysis and modeling of
complex information-driven systems, with experience in such diverse domains
as biotechnology, financial systems, and Internet topologies. His core
competencies include software engineering, machine learning, mathematical
modeling, Big Data systems, and several areas of biology.
Dr. Starzl has extensive experience with the computational and mathematical
methods integral to the effective acquisition, management, and utilization
of large amounts of information. Having led several massive data analysis
projects - with data sets as large as 100+TB - Dr. Starzl is fluent in the
methods of Big Data analytics, and is an active researcher in the area of
parallelization of machine learning methods for Big Data. He also has
extensive experience with many biotechnology and industrial technology
quantification platforms, immunological and transplantation methods, as well
as general clinical practices and healthcare management systems. Dr. Starzl
also has direct experience in entrepreneurial biotechnology development and
For example, Dr. Starzl has conducted leading edge research into the
elucidation of patterns of communication and function in the immune system
by adapting and extending analytic techniques that have proven successful in
areas with similar types of complexity, such as human language and finance,
and is further extending his work into areas that can likewise be addressed
by his analytic methodology.
Dr. Starzl's typical investigational methodology is to pursue research
objectives that deliver findings of practical significance as well as
findings that advance fundamental understanding, via a multi-disciplinary
systems approach using mathematics, computer science, domain knowledge, and
empirical experience, yielding an iterative processes where both analytic
findings and empirical observations can quickly infuse each other with
meaning, and which can help guide the direction of investigation. This
process can accelerate the identification and elucidation of key mechanisms,
as well as enabling more effective model bootstrapping by using existing
knowledge of a system. Ultimately, this allows a more rapid development or
validation of new strategies, processes, or products.
Dr. Starzl is a Systems Scientist in the Language Technologies Institute at
Carnegie Mellon University. He received his doctoral degree in Language and
Information Technologies from the School of Computer Science at Carnegie
Mellon University in 2012. At In addition to his research at CMU, Dr. Starzl
develops and teaches classes on the topics of Big Data, biotechnology, and
advanced software development. Prior to his academic work, Dr. Starzl held
positions in private concerns such as University of Pittsburgh Medical
Center and United Therapeutics Corporation. He has also participated in the
founding, growth, and sale of several biotechnology and high-tech startups.
Jaime Carbonell is the Allen Newell Professor in the School of Computer Science. He is the Director of the Language Technologies Institute. Overall, he has published over 250 articles and books. His research includes text and data mining, machine translation, reasoning under uncertainty, and computational proteomics where he investigates machine learning and language technologies to predict proteomic 3D structure (a.k.a. "the folding problem") and function. Dr. Carbonell has served on various advisory committees including the NIH Human Genome Advisory Committee and the National German AI Lab (DFKI) Scientific Advisory Board. He has also served as an advisor for numerous technology startups and companies, and has consulted to large financial institutions such as Citigroup. He received his MS and Ph.D. from Yale University and his BS in Physics from MIT.
Robert Murphy is the Ray and Stephanie Lane Professor of Computational Biology. He co-founded the Computational Biology Ph.D. Program which is jointly administered with the University of Pittsburgh. He helped developed the first formal undergraduate program in computational biology in 1987 and founded the Merck Computational Biology and Chemistry program at Carnegie Mellon in 1999. His research group does both experimental and computational cell biology, with a particular emphasis on developing fully-automated methods to understand the subcellular locations of proteins and how they change during development or disease (location proteomics). Dr. Murphy received his Ph.D. from the California Institute of Technology and his BA from Columbia College.
Eric Nyberg is a Professor in the Language Technologies Institute. He is the co-Director for the M.S. Program in Biotechnology, Innovation, and Computation as well as the MSIT Program in Very Large Information Systems. Dr. Nyberg has made significant research contributions to the fields of automatic text translation, information retrieval and automatic question answering. His research has been funded by global corporations (including IBM, Caterpillar, Daimler-Benz, Hewlett-Packard, Hitachi and Denso), and a variety of U.S. government agencies. Dr. Nyberg received his Ph.D. from Carnegie Mellon University and his BA from Boston University. In 2012, Dr. Nyberg received the Allen Newell Award for Research Excellence for his scientific contributions to the field of question answering and his work on IBM's Watson project.
Dr. Karen Thickman received her PhD from the Johns Hopkins School of Medicine in Molecular Biophysics. There she studied the structure of spliceosomal proteins and the thermodynamics of protein-protein interactions involved in recruiting the spliceosome to the pre-mRNA. During her postdoctoral fellowship at the University of Pittsburgh, she studied the biochemical properties and DNA structure specificity of a gram-positive bacterial helicase, PcrA. Dr. Thickman's teaching focuses on laboratory courses in computational biology and biological sciences. Her interests include automation of biology, protein interaction studies, teaching laboratory and research skills, and science policy.
Dr. Kevin Kai-Min Chang received his Ph.D. and M.S. from Carnegie Mellon
University. His research interests include using mathematical methodologies
and machine learning techniques to investigate and model various human
cognitive processes in the brain. In particular, He has studied semantic
presentation of concepts and multi-words phrases using functional Magnetic
Resonance Imaging and knowledge representation in the context of an
intelligent tutoring system. His current research projects use consumer EEG
devices to help improve intelligent tutoring systems and automatic speech
recognizers in dialog systems by monitoring and recording users' mental
state, such as affection, engagement, etc.
Mark J. Ahn, Ph.D. is President & Chief Executive Officer, and Director of Galena Biopharma (Nasdaq: GALE) and Professor (adjunct), Biosciences, Creighton University. Prior to Galena , Dr. Ahn was Principal at Pukana Partners, Ltd. that provides strategic consulting to life science companies; and Associate Professor, Global Management at Atkinson Graduate School of Management, Willamette University. He previously served as Chair, Science & Technology Management, Victoria University at Wellington, New Zealand. Dr. Ahn was also founder, President, and Chief Executive Officer of Hana Biosciences. Prior to Hana, he served as Vice President, Hematology and corporate officer at Genentech, Inc., as well as held positions of increasing responsibility at Amgen and Bristol-Myers Squibb Company; and served in the US Army. Dr. Ahn also serves on public and venture capital-backed Board of Directors for Access Pharmaceuticals, Mesynthes and Scribes STAT. Dr. Ahn is the author of over 50 peer reviewed journal articles and books including Making the Case for Biotechnology (Logos Press).
Dr. Ahn received a BA and MBA from Chaminade University; and MA from Victoria University. He was a graduate fellow in Economics at Essex University, and obtained a Ph.D. from the University of South Australia. Dr. Ahn is a Henry Crown Fellow at the Aspen Institute.
Dr. James Cai is the Head of Disease and Translational Informatics at Roche
Pharmaceuticals in Nutley, New Jersey. He leads a group of informatics
scientists that provide a wide array of support to scientists in the areas
of data capture, management, analysis and sharing/collaboration. Prior to
his current role, James was Head of Research Statistics and Data Mining, and
later Head of the Biomedical Informatics group, both within the Pharma
Research and Early Development (pRED) Informatics organization at Roche. Dr.
Cai has worked in a wide range of informatics areas including genomic data
analysis, algorithm development, enterprise system development, text
analytics and data mining. He played leading roles in several global
initiatives that helped to shape the Informatics strategies at Roche. He and
his team are also responsible for a number of scientific applications widely
used within the company. Dr. Cai received his Ph.D. in Molecular Biology
from Cornell University and a Master's degree in Biomedical Informatics from
Columbia University. He was a National Library of Medicine postdoctoral
fellow in Biomedical Informatics, with broad training in informatics
practices from basic biological research to clinical medicine.
Richard Chin is currently the CEO of One World Health. He has overseen over 40 Investigational New Drug (IND) Applications for new molecular entities and new indications, as well as eight New Drug Applications (NDAs)/Biologic License Applications (BLAs). Dr. Chin joined One World Health from OXiGENE, where he served as President and CEO. Previously, Dr. Chin served as Senior VP and Head of Global Development for Elan Corporation, where he had worldwide responsibility for Clinical Development, Regulatory, Biostatistics, CMC, QA/Compliance, Safety and Medical Affairs. Dr. Chin has also held various clinical and scientific roles for Genentech, Inc. including Head of Clinical Research for the Biotherapeutics Unit, overseeing approximately half of the drugs at Genentech, and began his career at Procter and Gamble Pharmaceuticals, where he served as Associate Medical Director. He received a B.A. in Biology from Harvard University and the equivalent of a J.D. with honors from Oxford University in England under a Rhodes scholarship. Dr. Chin received his MD from Harvard Medical School.
Madhavi Ganapathiraju, Ph.D., is Assistant Professor at Department of
Biomedical Informatics and Intelligent Systems Program at University of
Pittsburgh and Molecular and Cellular Cancer Biology Program of University
of Pittsburgh Cancer Institute. She is also Faculty of Language Technologies
Institute of Carnegie Mellon University and Joint Carnegie Mellon University
of Pittsburgh Ph.D. Program in Computational Biology. She has a Ph.D. from
School of Computer Science of Carnegie Mellon University and a Masters in
Engineering from Department of Electrical Communications Engineering from
Indian Institute of Science. She is the recipient of the Biobehavioral
Research Awards for Innovative New Scientists (BRAINS) from National
Institute of Mental Health of the National Institutes of Health of USA. In
this award-funded project, her group is discovering the Mental Health and
Inflammation Interactome of Protein-Protein Interactions, by applying
machine learning and graph mining methods.
Dr. Xuong Nguyen-Huu is an Emeritus Professor of Physics, Biology, Chemistry & Biochemistry at the University of California San Diego (UCSD). He is also a Research Professor of Chemistry & Biochemistry at UCSD. His field of research is on the High Resolution Structure of Biological Macromolecules using Protein Crystallography. He has also been working in the field of detectors for 50 years, first with particle detectors (both electronics and Bubble Chambers) for High Energy Particles Physics, then with X ray detectors for Protein Crystallography ( using Multi-wire Proportional Chambers and then Silicon detectors). Last but not least he is one of the pioneers of the field of Direct Detection Device (DDD) that will be used in Electron Microscopy. He has received an MS and Ph D (Physics) from the University of California Berkeley, an MS in Mathematics from the University of Paris and an MS in Electronic Engineering from the Ecole Superieure d’Electricite de Paris.
John Shon is the Director of Disease and Translational Informatics at Johnson & Johnson Pharmaceuticals, where he leads an informatics group that supports and develops systems to enable the discovery and development of new medicines. He is particularly interested in systems that leverage high-dimensional genetics, genomics, pathways, and text data in the context of clinical therapeutics for personalized medicine. Dr. Shon has multidisciplinary background in clinical medicine, biomedical informatics, molecular biology, and drug discovery and development. He received his degree in medicine at Stanford, completed his internship and residency in internal medicine at the University of Chicago, and completed a masters degree and National Library of Medicine post-doctoral fellowship in biomedical informatics at Stanford. He subsequently worked in industry in several biotech and informatics consulting firms prior to joining Johnson & Johnson.