Valeria De Luca
Tuesday, August 8th
Novartis Institutes for BioMedical Research (NIBR)
Armineh Nourbakhsh
Tuesday, August 8th
JP Morgan
Giorgio Quer
Tuesday, August 8th
Giorgio Quer is an Assistant Professor and Director of Artificial Intelligence at the Scripps Research Translational Institute, where he is leading the Data Science and Analytics team working in the All of Us Research Program (NIH) and the Digital Trials Center. His research focuses on artificial intelligence and probabilistic modeling applied to heterogeneous data signals, in order to extract key information and make predictions on future occurrences based on past data. He is involved in several digital medicine initiatives within the Digital Trial Center. In the DETECT study, he is developing algorithms to predict COVID-19 and other viral infections from wearable sensor data. He is responsible for the collaboration with several industrial partners, studying changes in heart rate and sleep data monitored by commercial wearable devices, and with the Halıcıoğlu Data Science Institute at UC San Diego. He is interested in the detection and modeling of atrial fibrillation from single-lead ECG signals. He received his Ph.D. degree in Information Engineering from the University of Padova, Italy, and he continued his studies as a Postdoctoral researcher with the Qualcomm Institute at UC San Diego. He is a Senior Member of the IEEE and a Distinguished Lecturer for the IEEE Communications society.
Aude Hofleitner
Tuesday, August 8th
I am the Director of the GRAph Science & Statistics team on Meta’s Central Applied Science team. My research interests lie in the fields of statistics and AI. In particular, I focus on the development of methodologies and best practices to ensure the trust and quality of AI models. I am also interested in leveraging the structure of graphs and interaction data to make robust predictions at scale.
I received a PhD in electrical engineering and computer science from the University of California, Berkeley under the supervision of Alexandre Bayen and Pieter Abbeel. Before that, I did my undergrad and MS in applied mathematics at the Ecole Polytechnique, France. I also received a PhD and a MS in transportation engineering from Ecole des Ponts ParisTech.
Xiaolin Shi
Tuesday, August 8th
Xiaolin Shi is the Head of Applied Research at Snap Inc., spearheading a team of research scientists and engineers specializing in causal inference, data mining, statistics, and scalable machine learning. Before her current role at Snap, Xiaolin received her PhD in Computer Science and Engineering from the University of Michigan and built her career at Stanford, Microsoft Bing, Microsoft Research, and Yahoo Research. Her research interests include causal inference, user modeling, experimentation, and network science. She has regularly published and presented her work at conferences such as KDD, WSDM, and WWW.
Saurabh Tiwary
Tuesday, August 8th
As Corporate Vice President & Technical Fellow at Microsoft, Saurabh Tiwary leads the Microsoft Turing effort. The team focuses on three areas:
1. Leading the development of Bing Chat experience and other Microsoft CoPilots like Windows Copilot, Office Copilot etc. which are the first global scale conversational search experiences across consumer and enterprise.
2. Training Turing family of large-scale deep learning models. Apart from chat and Copilot experiences, these models also power text-prediction in Word and Edge browser, Image super-resolution in Edge browser, SmartReply in Outlook/Teams and question-answering system on Bing.com amongst other things.
3. Building scalable AI infrastructure called Semantic Fabric to light up experiences like search, QnA, and Viva topics over exabytes of enterprise data from SharePoint, Exchange mailboxes, and 3rd party connector content.
Tiwary started the Microsoft Turing effort from scratch setting up the first non-trivial training cluster at Microsoft and later scaling that effort to help drive development of large-scale training, building state of the art models for NLP and vision, and efficient inferencing across different hardware options including CPU, GPU, FPGAs, and NPUs.
He also advises Microsoft Ventures Fund (M12) in its AI investments. Tiwary earned his PhD in Electrical & Computer Engineering from Carnegie Mellon University. In addition, he holds an M.B.A. from University of California, Berkeley, Haas in Master of Business Administration and an undergraduate degree from IIT Kanpur.
Jessilyn Dunn
Tuesday, August 8th
Dr. Jessilyn Dunn is Assistant Professor of Biomedical Engineering and Biostatistics & Bioinformatics at Duke University, and Director of the BIG IDEAs Laboratory whose goal is to detect, treat, and prevent chronic and acute diseases through digital health innovation. She is PI of the CovIdentify study to detect and monitor infections like flu and COVID-19 using mobile health technologies and leads the DBDP open-source software effort to support digital biomarker development. Dr. Dunn was an NIH Big Data to Knowledge (BD2K) Postdoctoral Fellow at Stanford and an NSF Graduate Research Fellow at Georgia Tech and Emory, as well as a visiting scholar at the US Centers for Disease Control and Prevention and the National Cardiovascular Research Institute in Madrid, Spain. Her work has been internationally recognized with media coverage from the NIH Director’s Blog to Wired, Time, and US News and World Report.
Andrew White
Tuesday, August 8th
Andrew White is an associate professor at the University of Rochester in chemical engineering with affiliate appointments in chemistry, biophysics, materials science, and data science. He has a Ph.D. in chemical engineering from the University of Washington and did postdoc training in chemistry at the University of Chicago. White’s research group studies the deep learning and molecular simulation of peptides and small molecules. He and his group work on the adaptation of deep learning to chemistry and materials, with research on graph neural networks, explaining deep learning models, large language models, and Bayesian optimization. Andrew has won young investigator awards from NSF and NIH, professional society awards in chemical engineering, teaching awards from the University of Rochester, and engineer of the year in Rochester, NY. Andrew’s group is currently funded by the DOE, NSF, and NIH.
