October 25, 2022
October 28 Colloquium: "Great Stories in Computer Science: the case for complexity analysis and empirical testing"
As an instructor of introductory programming courses (007,401 445, 449) at Pitt and similar courses other universities Prof. Hoffman has consistently encountered math hesitancy to the presentation of complexity analysis. In this talk, he will convey an anecdote - a fascinating story in computer science surrounding the binary search algorithm.
September 9, 2022
September 9 colloquium: Thoughts of a Reformed Computer Scientist: On the Nature of Real and Artificial Intelligence -- James Morris
On September 9th, we are hosting a joint Computer Science Colloquium / Research, Ethics and Society Initiative Seminar, entitled Thoughts of a Reformed Computer Scientist: On the Nature of Real and Artificial Intelligence, given by Dr. James Morris, MBA, PhD (Emeritus Professor of Computer Science, Carnegie Mellon University).
April 8, 2022
Manos Athanassoulis is an Assistant Professor of Computer Science at Boston University, Director and Founder of the BU Data-intensive Systems and Computing Laboratory and co-director of the BU Massive Data Algorithms and Systems Group.
April 1, 2022
Dr. Michael White is a Professor in the Department of Linguistics at The Ohio State University. His research has focused on NLG in dialogue with an emphasis on surface realization, extending also to paraphrasing for ambiguity avoidance and data augmentation in the context of Ohio State's virtual patient dialogue system.
March 25, 2022
March 25 Colloquium: Amazon Supply Chain Optimization Technology: The largest decision-making machine in the world-- Tomas Singliar
Tomas Singliar, University of Pittsburgh CS PhD class of 2008, is a business quantitative scientist with experience in forecasting, inventory, pricing and profitability.
March 18, 2022
March 18 Colloquium: Probabilistic Hashing for Scalable and Sustainable Machine Learning -- Sameh Gobriel
Sameh Gobriel is a senior research scientist at Intel Labs where he leads a team to drive research enabling future Intel products to be best-in-class in performance using software and hardware optimizations.
March 15, 2022
Henry Chai is a postdoctoral teaching fellow at Carnegie Mellon University where he teaches an assortment of courses titled "Introduction to Machine Learning" at various levels. He will deliver a faculty recruiting colloquium on Tuesday, March 15th.
March 14, 2022
March 14th Colloquium: AI for Social Impact: Learning and Optimization in Network and Combinatorial Spaces -- Haipeng Chen
Haipeng Chen is a CRCS postdoctoral fellow at Harvard University.
March 8, 2022
Sara Riazi is a visiting assistant professor in the Department of Computer Science at the University of North Carolina-Charlotte. She will deliver a faculty recruiting colloquium talk on Tuesday, March 8th.
March 7, 2022
Lorraine (Xiang Li) is a final-year Ph.D. candidate at UMass Amherst working with Andrew McCallum. She will deliver a faculty recruiting colloquium on Monday, March 7th.
February 25, 2022
February 25th Colloquium: Causal Targeting - It's not Causal Effect Estimation (and Why it Matters) -- Foster Provost
Foster Provost is Ira Rennert Professor of Entrepreneurship, Data Science, and Information Systems and Director, Fubon Center, Data Analytics & AI, at the Stern School of Business at New York University. He will deliver a colloquium talk on Friday, February 25th at 2 p.m.
February 24, 2022
Tiago Januario is a lecturer and researcher at the Department of Computer Science, Institute of Mathematics and Statistics, University of Bahia, Salvador, Brazil. He will deliver a faculty colloquium talk on February 24th.
February 18, 2022
February 18 CS Colloquium: Virtual Reality and Metaverses: Challenges for the next years -- Esteban Clua
Esteban Clua is a professor at Universidade Federal Fluminense (Brazil) and coordinator of UFF Medialab, Scientist of the State of Rio prize in 2019 and Young Scientist of the State of Rio in 2009 and 2013.
February 11, 2022
February 11 CS Colloquium: Collaboration, Context, and Computing Science: Unlocking Next-Generation AI-Solutions for Complex Societal and Environmental Needs -- Kelly Rose
Kelly Rose, PhD, is a Geo-Data Scientist with over 20 years of service and research experience at the U.S. Department of Energy’s National Energy Technology Laboratory (NETL).