Events Archive
Colloquium - Yang Li, Meta, Resource Management: Cloud and AI
Resource management significantly impacts the performance and availability of cloud infrastructure. In the first part of my talk, I will introduce my work on managing memory, cache, and power resources to boost the performance and availability of cloud infrastructure. On memory resources, we propose UH-MEM, a utility-based data placement technique for hybrid memory. Read more about Colloquium - Yang Li, Meta, Resource Management: Cloud and AI
2022 Midwest Big Data Summer School
The Midwest Big Data Summer School will be held May 16th - 19th, 2022 at Iowa State University, on campus. This is an in-person event. More details will be coming soon! Read more about 2022 Midwest Big Data Summer School
Dr. Jia (Kevin) Liu, 'Incentivized Bandit Learning under Self-Reinforcing User Preference for Online Recommender Systems', TADS Lunch-n-Learn
Incentivized Bandit Learning under Self-Reinforcing User Preference for Online Recommender Systems
Robert Stewart Distinguished Lecture: Why is it so hard to make self-driving cars? Trustworthy autonomous systems', with Joseph Sifakis
Why is it so hard to make self-driving cars? Trustworthy autonomous systems
Joseph Sifakis, Verimag Laboratory Read more about Robert Stewart Distinguished Lecture: Why is it so hard to make self-driving cars? Trustworthy autonomous systems', with Joseph Sifakis
Colloquia - Chenglin Miao, 'Exploring the Security Vulnerabilities of Intelligent IoT Systems', Virtual, 4:25 - 5:25 pm
Exploring the Security Vulnerabilities of Intelligent IoT Systems
Dr. Kuldeep Meel, 'Next Gen Automated Reasoning: Beyond “SAT Revolution” to “Beyond SAT” Revolution', TADS Lunch-n-Learn
ECpE Seminar Series with Xuan Wang: 'Automated Scientific Knowledge Extraction from Massive Text Data'
Automated Scientific Knowledge Extraction from Massive Text Data
Read more about ECpE Seminar Series with Xuan Wang: 'Automated Scientific Knowledge Extraction from Massive Text Data'>Colloquia - Meisam Mohammady, Novel Approaches to Preserving Utility in Privacy Enhancing Technologies, Virtual, 4:25 - 5:25 pm
Novel Approaches to Preserving Utility in Privacy Enhancing Technologies
Colloquia - Spyros Mastorakis, Compute-less Networking: Enabling the Operation of Next-Generation Applications, Virtual, 4:25 - 5:25 pm
Compute-less Networking: Enabling the operation of Next-Generation Applications
Colloquia - Jinyuan Jia, Machine Learning Meets Security and Privacy: Opportunities and Challenges, Virtual, 4:25 - 5:25 pm
Machine Learning Meets Security and Privacy: Opportunities and Challenges
Colloquia - Jie Ren, Enabling Big Memory Applications with Memory Heterogeneity, Virtual, 4:25 - 5:25 pm
Enabling Big Memory Applications with Memory Heterogeneity
Colloquia - Stefan Nagy, Advancing and Accelerating Vetting of the Closed-source Software Ecosystem, Virtual, 4:25 - 5:25 pm
Advancing and Accelerating Vetting of the Closed-source Software Ecosystem
Colloquia - Wenbo Guo, Strengthening and Enriching Machine Learning for Cybersecurity, Virtual, 4:25 - 5:25 pm
Strengthening and Enriching Machine Learning for Cybersecurity
Colloquia - Yueqi Chen, Securing Operating System Kernels with Fewer Shots, Virtual, 4:25 - 5:25 pm
Securing Operating System Kernels with Fewer Shots
Colloquia - Victoria Crawford, Multi-Objective Optimization for Big Data Mining, Virtual, 4:25 - 5:25 pm
Multi-Objective Optimization for Big Data Mining
Colloquia - Haohan Wang, Toward Trustworthy Machine Learning to Understand the Genetic Basis of Phenotyped Subtypes of Alzheimer's Disease, Virtual, 4:25 - 5:25 pm
Toward Trustworthy Machine Learning to Understand the Genetic Basis of Phenotyped Subtypes of Alzheimer’s disease
Colloquia - Mengdi Huai, Fostering Trustworthiness in Machine Learning: From Transparence to Robustness, Virtual, 4:25 - 5:25 pm
Fostering Trustworthiness in Machine Learning: From Transparence to Robustness
Colloquia - Lu Cheng, 'Algorithmic Solutions for Socially Responsible AI', Virtual, 4:25 - 5:25 pm
Algorithmic Solutions for Socially Responsible AI
Abstract:
Artificial intelligence (AI) technologies have become increasingly pervasive, offering both promises and perils. In response, researchers and
organizations have been working to publish principles for the responsible use of AI. To bridge from these principles to responsible AI practice, in this talk, I will introduce
Read more about Colloquia - Lu Cheng, 'Algorithmic Solutions for Socially Responsible AI', Virtual, 4:25 - 5:25 pm
Colloquia - Xuhui Fan, Uncertainties, Complexities and Scalable Inference: A Few Peeks at Bayesian Machine Learning, Virtual, 4:25 - 5:25 pm
Uncertainties, Complexities and Scalable Inference: A Few Peeks at Bayesian Machine Learning
Colloquia - Adnan Siraj Rakin, Exploring the Vulnerabilities of Modern Deep Learning Algorithms and System, Virtual, 4:25 - 5:25 pm
AI Security: Exploring the Vulnerabilities of Modern Deep Learning Algorithms and System
Colloquia - Shu Kong, Open-World Visual Perception, Virtual, 4:25 - 5:25 pm
Open-World Visual Perception
Bio: Read more about Colloquia - Shu Kong, Open-World Visual Perception, Virtual, 4:25 - 5:25 pm
Colloquia - Chris Thomas, Revisiting the Role of Visual Media in Understanding a Rich Multimodal World, Virtual, 4:25 - 5:25 pm
'Revisiting the Role of Visual Media in Understanding a Rich Multimodal World'
Colloquia - Nghia Hoang, Collaborative Machine Learning via Model Fusion, Virtual, 4:45 - 5:45 pm
'Collaborative Machine Learning via Model Fusion'
Colloquia: Alan Kuhnle - Scalable and Learned Algorithms for Discrete Optimization, Virtual, 4:25-5:25pm
'Scalable and Learned Algorithms for Discrete Optimization'
Virtual Seminar, Daniela Witten, 'Selective Inference for Trees'
Biography:
Daniela Witten is a coauthor of the popular text Introduction to Statistical Learning by James, Witten, Hastie, and Tibshirani. Since earning her PhD at Stanford in 2010, Professor Witten has had many impressive accomplishments. At the 2018 Women in Data Science Conference, Professor Witten gave a lecture watched by 100,000 via livestream.
Abstract, via Professor Witten: Read more about Virtual Seminar, Daniela Witten, 'Selective Inference for Trees'
D4 Institute Conference on Data Science
The D4 Institute at Iowa State University will host a Data Science conference on October 30th, 2021. Join us virtually to hear a keynote speech from a Research Science Manager at Amazon, to engage in a D4 Institute panel discussion on data science graduate studies, and to participate in a poster session!
*To access the meeting link, please check your email inbox. All registered attendees were sent the Zoom link on 10/29 at 10:00am from mmott@iastate.edu*
Read more about D4 Institute Conference on Data Science>Distinguished Lecture: Michael I. Jordan, UC Berkeley, The Decision-Making Side of Machine Learning
Midwest Big Data Summer School
Dr. Eric Price, 'Instance-Optimal Compressed Sensing via Conditional Resampling', TADS Lunch-n-Learn
Instance-Optimal Compressed Sensing via Conditional Resamplin Read more about Dr. Eric Price, 'Instance-Optimal Compressed Sensing via Conditional Resampling', TADS Lunch-n-Learn
Dr. Liangxiu Han, 'Deep Learning and its Application to Remotely Sensed Data', TADS Lunch-n-Learn
Presenter: Dr. Liangxiu Han
Title: Deep learning and its application to remotely sensed data Read more about Dr. Liangxiu Han, 'Deep Learning and its Application to Remotely Sensed Data', TADS Lunch-n-Learn
Theoretical and Applied Data Science Seminar - Dr. Agus Sudjianto
Presenter: Agus Sudjianto
Title: Managing Machine Learning Risk: Interpretability and Robustness Read more about Theoretical and Applied Data Science Seminar - Dr. Agus Sudjianto
Dr. Cynthia Rudin, 'The Extremes of Interpretability in Machine Learning: Sparse Decision Trees, Scoring Systems and Interpretable Neural Networks', TADS Lunch-n-Learn
Presenter: Dr. Cynthia Rudin
Title: The Extremes of Interpretability in Machine Learning: Sparse Decision Trees, Scoring Systems and Interpretable Neural Networks Read more about Dr. Cynthia Rudin, 'The Extremes of Interpretability in Machine Learning: Sparse Decision Trees, Scoring Systems and Interpretable Neural Networks', TADS Lunch-n-Learn
Theoretical and Applied Data Science Seminar - Dr. Aurore Delaigle
Presenter: Dr. Aurore Delaigle
Title: Estimating a Covariance Function from Fragments of Functional Data Read more about Theoretical and Applied Data Science Seminar - Dr. Aurore Delaigle
Women in Data Science Ames
Colloquia: Baker (Zhengxiong) Li, University at Buffalo - SUNY
Presenter: Baker (Zhengxiong) Li
Title: Wireless Meta-sensing for IoT Security and Beyond Read more about Colloquia: Baker (Zhengxiong) Li, University at Buffalo - SUNY
Dr. Ryan Martin, 'Valid Inferential Models and Conformal Prediction', TADS Lunch-n-Learn
Presenter: Dr. Ryan Martin
Title: Valid inferential models and conformal prediction Read more about Dr. Ryan Martin, 'Valid Inferential Models and Conformal Prediction', TADS Lunch-n-Learn
Colloquia: Dr. Abusayeed Saifullah, Wayne State University
Presenter: Abusayeed Saifullah
Title: The Design of a Low-Power Wide-Area Network over White Spaces Read more about Colloquia: Dr. Abusayeed Saifullah, Wayne State University
Colloquia: Dr. Ali Anwar, IBM Research - Almaden
Presenter: Dr. Ali Anwar
Title: Analyze and rebuild: Redesigning distributed computing systems for the next killer app Read more about Colloquia: Dr. Ali Anwar, IBM Research - Almaden
Colloquia: Dr. Peng Gao, University of California - Berkeley
Presenter: Dr. Peng Gao
Title: Building Trustworthy Systems for Fighting Modern Threats Read more about Colloquia: Dr. Peng Gao, University of California - Berkeley
Colloquia: Dr. Kevin Leach, University of Michigan - Ann Arbor
Presenter: Dr. Kevin Leach
Title: Transparent System Introspection Read more about Colloquia: Dr. Kevin Leach, University of Michigan - Ann Arbor
Industry Lecture: Maria Thompson, Diversity Drives Innovation
Presenter: Maria Thompson
Title: Diversity Drives Innovation
Location: Zoom Read more about Industry Lecture: Maria Thompson, Diversity Drives Innovation
Distinguished Lecture with Ken Goldberg from UC Berkeley
Presenter: Ken Goldberg
Title: The New Wave in Robot Grasping Read more about Distinguished Lecture with Ken Goldberg from UC Berkeley
Envisioning Boa 2.0 Workshop
Boa is a domain-specific language and infrastructure that eases mining software repositories. Boa's infrastructure leverages distributed computing techniques to execute queries against hundreds of thousands of software projects very efficiently. Boa has existed for almost 7 years with a large user base of more than 1,200 users in all over the world. Read more about Envisioning Boa 2.0 Workshop
Dr. Andrew McGregor, 'Recent Results on Cycle Counting in the Data Stream Model', TADS Lunch-n-Learn
Presenter: Dr. Andrew McGregor
Title: Recent Results on Cycle Counting in the Data Stream Model Read more about Dr. Andrew McGregor, 'Recent Results on Cycle Counting in the Data Stream Model', TADS Lunch-n-Learn
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Laura Miller
Presenter: Laura Miller
Title: Integrate structural analysis, isoform diversity, and interferon-inductive propensity of ACE2 to predict SARS-CoV-2 susceptibility in vertebrates Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Laura Miller
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Dan Gianola
Presenter: Dan Gianola
Title: David vs. Goliath: the COVID-19 epidemic in Uruguay in a regional and world context Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Dan Gianola
Dr. Xiaoming Huo, 'A Homotopic Method to Solve the Lasso Problems with an Improved Upper Bound of Convergence Rate', TADS Lunch-n-Learn
Presenter: Dr. Xiaoming Huo
Title: A Homotopic Method to Solve the Lasso Problems with an Improved Upper Bound of Convergence Rate Read more about Dr. Xiaoming Huo, 'A Homotopic Method to Solve the Lasso Problems with an Improved Upper Bound of Convergence Rate', TADS Lunch-n-Learn
Dr. Tianbao Yang, 'Deep AUC Maximization and Applications in Medical Image Classification', TADS Lunch-n-Learn
Presenter: Dr. Tianbao Yang
Title: Deep AUC Maximization and Applications in Medical Image Classification Read more about Dr. Tianbao Yang, 'Deep AUC Maximization and Applications in Medical Image Classification', TADS Lunch-n-Learn
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Eve Wurtele
Presenter: Eve Wurtele
Title: The role of ancestry in COVID-19 infection Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Eve Wurtele
Dr. Hongfeng Yu, 'Exploring and Evaluating Edge Bundling for Large Graph Visualization', TADS Lunch-n-Learn
Presenter: Dr. Hongfeng Yu
Title: Exploring and Evaluating Edge Bundling for Large Graph Visualization Read more about Dr. Hongfeng Yu, 'Exploring and Evaluating Edge Bundling for Large Graph Visualization', TADS Lunch-n-Learn
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Walter Moss
Presenter: Walter Moss
Title: Finding and Folding Functional RNA in SARS-CoV-2
Bio: Walter Moss is an Assistant Professor in the Department of Biochemistry, Biophysics, and Molecular Biology at Iowa State University. Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Walter Moss
Dr. Tamal Dey, 'Computational Topology and Data Analysis: A New Way of Looking at Data', TADS Lunch-n-Learn
Presenter: Dr. Tamal Dey
Title: Computational Topology and Data Analysis: A New Way of Looking at Data Read more about Dr. Tamal Dey, 'Computational Topology and Data Analysis: A New Way of Looking at Data', TADS Lunch-n-Learn
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Yumou Qiu
Presenter: Yumou Qiu
https://www.stat.iastate.edu/people/yumou-qiu
Title: Comparing containment measures by epidemiological effects of COVID-19 Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Yumou Qiu
Theoretical and Applied Data Science Seminar - Ness Shroff
Presenter: Ness Shroff
http://newslab.ece.ohio-state.edu/home/
Title: Delay Optimality in Network Clouds via Load Balancing Read more about Theoretical and Applied Data Science Seminar - Ness Shroff
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Lily Wang
Presenter: Lily Wang
https://faculty.sites.iastate.edu/lilywang/
Title: Nowcasting and Forecasting COVID-19 in the United States Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Lily Wang
Dr. Stephen Wright, 'Second-order Methods for Nonconvex Optimization with Complexity Guarantees', TADS Lunch-n-Learn
Presenter: Dr. Stephen Wright
Title: Second-order Methods for Nonconvex Optimization with Complexity Guarantees Read more about Dr. Stephen Wright, 'Second-order Methods for Nonconvex Optimization with Complexity Guarantees', TADS Lunch-n-Learn
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Dan Jacobson
Presenter: Dan Jacobson
https://www.ornl.gov/staff-profile/daniel-jacobson
Title: A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Dan Jacobson
Dr. In-Ho Cho, 'Parallel Fractional Hot Deck Imputation for Large/Big Missing Data Curing for Improving Machine Learning and Statistical Inference', TADS Lunch-n-Learn
Presenter: Dr. In-Ho Cho
Title: Parallel Fractional Hot Deck Imputation for Large/Big Missing Data Curing for Improving Machine Learning and Statistical Inference Read more about Dr. In-Ho Cho, 'Parallel Fractional Hot Deck Imputation for Large/Big Missing Data Curing for Improving Machine Learning and Statistical Inference', TADS Lunch-n-Learn
Theoretical and Applied Data Science Seminar - Helen Zhang
Presenter: Helen Zhang
https://www.math.arizona.edu/~hzhang/
Title: Sparse and Smooth Function Estimation in Reproducing Kernel Hilbert Spaces Read more about Theoretical and Applied Data Science Seminar - Helen Zhang
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Claus Kadelka
Presenter: Claus Kadelka
https://faculty.sites.iastate.edu/ckadelka/
Title: A model-based evaluation of the efficacy of COVID-19 social distancing, testing and hospital triage policies Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Claus Kadelka
Dr. Lev Reyzin, 'Differential Privacy, Adaptive Data Analysis, and Free Speedups via Sampling', TADS Lunch-n-Learn
Presenter: Dr. Lev Reyzin
Title: Differential Privacy, Adaptive Data Analysis, and Free Speedups via Sampling Read more about Dr. Lev Reyzin, 'Differential Privacy, Adaptive Data Analysis, and Free Speedups via Sampling', TADS Lunch-n-Learn
Dr. Vipin Kumar, 'Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery', TADS Lunch-n-Learn
Presenter: Dr. Vipin Kumar
Title: Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery Read more about Dr. Vipin Kumar, 'Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery', TADS Lunch-n-Learn
Rangeet Pan, 'On Decomposing a Deep Neural Network into Modules', TADS Lunch-n-Learn
Presenter: Rangeet Pan
Title: On Decomposing a Deep Neural Network into Modules Read more about Rangeet Pan, 'On Decomposing a Deep Neural Network into Modules', TADS Lunch-n-Learn
Dr. Vinod Variyam, 'Learning and Sampling of Atomic Interventions from Observations', TADS Lunch-n-Learn
Presenter: Dr. Vinod Variyam
Title: Learning and Sampling of Atomic Interventions from Observations Read more about Dr. Vinod Variyam, 'Learning and Sampling of Atomic Interventions from Observations', TADS Lunch-n-Learn
Yan Wang, 'Wasserstein subsampling: Theory and empirical performance', TADS Lunch-n-Learn
Presenter: Yan Wang
Title: Wasserstein subsampling: Theory and Empirical Performance Read more about Yan Wang, 'Wasserstein subsampling: Theory and empirical performance', TADS Lunch-n-Learn
Dr. Hongyang Gao, 'Graph Neural Networks: A Feature and Structure Learning Approach', TADS Lunch-n-Learn
Presenter: Dr. Hongyang Gao
Title: Graph Neural Networks: A Feature and Structure Learning Approach Read more about Dr. Hongyang Gao, 'Graph Neural Networks: A Feature and Structure Learning Approach', TADS Lunch-n-Learn
Xiaoyun Fu, 'Quantifying attitude of individuals in social networks', TADS Lunch-n-Learn
Presenter: Xiaoyun Fu
Title: Quantifying attitude of individuals in social networks Read more about Xiaoyun Fu, 'Quantifying attitude of individuals in social networks', TADS Lunch-n-Learn
Jiaming Qiu, 'Nonparametric estimates for repeated densities with heterogeneous sample sizes', TADS Lunch-n-Learn
Presenter: Jiaming Qiu
Title: Nonparametric estimates for repeated densities with heterogeneous sample sizes Read more about Jiaming Qiu, 'Nonparametric estimates for repeated densities with heterogeneous sample sizes', TADS Lunch-n-Learn
Seyedehsara Nayer, 'Provable Low Rank Phase Retrieval', TADS Lunch-n-Learn
Presenter: Seyedehsara Nayer
Title: Provable Low Rank Phase Retrieval Read more about Seyedehsara Nayer, 'Provable Low Rank Phase Retrieval', TADS Lunch-n-Learn
Chancellor Johnstone, 'Distribution Free Prediction Intervals', TADS Lunch-n-Learn
Presenter: Chancellor Johnstone
Title: Distribution Free Prediction Intervals Read more about Chancellor Johnstone, 'Distribution Free Prediction Intervals', TADS Lunch-n-Learn
Konstantinos Konstantinidis, 'Speeding Up Distributed Computing via Coding', TADS Lunch-n-Learn
Presenter: Konstantinos Konstantinidis
Title: Speeding Up Distributed Computing via Coding Read more about Konstantinos Konstantinidis, 'Speeding Up Distributed Computing via Coding', TADS Lunch-n-Learn
Sumon Biswas, 'Do the Machine Learning Models on a Crowd-Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness', TADS Lunch-n-Learn
Presenter: Sumon Biswas
Title: Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness Read more about Sumon Biswas, 'Do the Machine Learning Models on a Crowd-Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness', TADS Lunch-n-Learn
Dr. Lily Wang, 'Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States', TADS Lunch-n-Learn
Presenter: Dr. Lily Wang
Title: Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States Read more about Dr. Lily Wang, 'Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States', TADS Lunch-n-Learn
Myungjin Kim, 'Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States', TADS Lunch-n-Learn
Presenter: Myungjin Kim
Title: Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States Read more about Myungjin Kim, 'Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States', TADS Lunch-n-Learn
Dr. Praneeth Narayanamurthy, 'Provable and Efficient Algorithms for Robust Subspace Learning and Tracking', TADS Lunch-n-Learn
Presenter: Dr. Praneeth Narayanamurthy
Title: Provable and Efficient Algorithms for Robust Subspace Learning and Tracking Read more about Dr. Praneeth Narayanamurthy, 'Provable and Efficient Algorithms for Robust Subspace Learning and Tracking', TADS Lunch-n-Learn
Dr. Ardhendu Tripathy, 'Adaptive Algorithms in Machine Learning', TADS Lunch-n-Learn
Presenter: Dr. Ardhendu Tripathy
Title: Adaptive Algorithms in Machine Learning Read more about Dr. Ardhendu Tripathy, 'Adaptive Algorithms in Machine Learning', TADS Lunch-n-Learn
Geoffrey Thompson, 'A k-means Based Image Compression Method', TADS Lunch-n-Learn
Presenter: Geoffrey Thompson
Title: A k-means based image compression method Read more about Geoffrey Thompson, 'A k-means Based Image Compression Method', TADS Lunch-n-Learn
Dr. Steve Sapp, 'Public Opinions About Network Surveillance', TADS Lunch-n-Learn
Presenter: Dr. Steve Sapp
Title: Public Opinions About Network Surveillance Read more about Dr. Steve Sapp, 'Public Opinions About Network Surveillance', TADS Lunch-n-Learn
SERL (Software Engineering Research Laboratory)
Presenter: Gianfranco Ciardo
http://web.cs.iastate.edu/~ciardo/
He will be presenting exciting recent work so please join us! Read more about SERL (Software Engineering Research Laboratory)
Dr. Fan Dai, 'A Matrix-Free Likelihood Method for Exploratory Factor Analysis of High-Dimensional Gaussian Data', TADS Lunch-n-Learn
Presenter: Dr. Fan Dai
Title: A Matrix-Free Likelihood Method for Exploratory Factor Analysis of High-Dimensional Gaussian Data Read more about Dr. Fan Dai, 'A Matrix-Free Likelihood Method for Exploratory Factor Analysis of High-Dimensional Gaussian Data', TADS Lunch-n-Learn
SERL (Software Engineering Research Laboratory)
Presenter: Myra Cohen
https://www.cs.iastate.edu/people/myra-cohen
A discussion about what makes a good research paper. Read more about SERL (Software Engineering Research Laboratory)
Dr. Dan Nettleton, 'Introduction to Uncertainty Quantification for Predictions', TADS Lunch-n-Learn
Presenter: Dr. Daniel Nettleton
Title: Introduction to Uncertainty Quantification for Predictions Read more about Dr. Dan Nettleton, 'Introduction to Uncertainty Quantification for Predictions', TADS Lunch-n-Learn
SERL (Software Engineering Research Laboratory)
Presenter: Mikaela Cashman
Title: The Software Engineer’s Role in Predictive Biology
Abstract: In the age of big data, predictive biology has scaled dramatically creating a community of biologists and bioinformaticians with a need for strong computational power. This talk will introduce a large open-source system aimed to meet these goals known as the Department of Energy’s Systems Biology Knowledgebase (KBase, http://kbase.us). KBase includes over 200 applications in the areas of genome assembly and annotation, sequence alignment, metabolic modeling, expression and more. There is also support for external tool integration through an SDK. KBase is designed to be open and collaborative where users can utilize public datasets, import custom data, create workflows built upon Jupyter notebooks, and share these workflows with others. Read more about SERL (Software Engineering Research Laboratory)
Dr. Eric Weber, 'A Randomized Distributed Linear Solver', TADS Lunch-n-Learn
Presenter: Dr. Eric Weber
Title: A Randomized Distributed Linear Solver Read more about Dr. Eric Weber, 'A Randomized Distributed Linear Solver', TADS Lunch-n-Learn
Peter Dixon, 'Distribution Testing and Complexity', TADS Lunch-n-Learn
Presenter: Peter Dixon
Title: Distribution Testing and Complexity Read more about Peter Dixon, 'Distribution Testing and Complexity', TADS Lunch-n-Learn
Dr. Jia Kevin Liu, 'Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Sensing?', TADS Lunch-n-Learn
Presenter: Dr. Jia (Kevin) Liu
Title: Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Sensing? Read more about Dr. Jia Kevin Liu, 'Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Sensing?', TADS Lunch-n-Learn
Dr. Chris Quinn, 'Sparse Approximations for Time-Series Networks', TADS Lunch-n-Learn
Presenter: Christopher Quinn
https://www.cs.iastate.edu/people/christopher-quinn
Title: Sparse Approximations for Time-Series Networks Read more about Dr. Chris Quinn, 'Sparse Approximations for Time-Series Networks', TADS Lunch-n-Learn
Dr. Chris Quinn, 'Sparse Approximations for Time-Series Networks', TADS Lunch-n-Learn
Presenter: Christopher Quinn
https://www.cs.iastate.edu/people/christopher-quinn
Title: Sparse Approximations for Time-Series Networks Read more about Dr. Chris Quinn, 'Sparse Approximations for Time-Series Networks', TADS Lunch-n-Learn
Dr. Pavan Aduri, 'Distribution Testing and Computation Complexity', TADS Lunch-n-Learn
Presenter: Dr. Pavankumar Aduri
Title: Distribution Testing and Computation Complexity Read more about Dr. Pavan Aduri, 'Distribution Testing and Computation Complexity', TADS Lunch-n-Learn
Human-Drone Partnerships in Emergency Response with Dr. Jane Cleland-Huang
Presenter: Dr. Jane Cleland-Huang
Title: Human-Drone Partnerships in Emergency Response Read more about Human-Drone Partnerships in Emergency Response with Dr. Jane Cleland-Huang
Answer Set Programming and Automatic Optimization Methods in its Realm with Dr. Yuliya Lierler
Presenter: Dr. Yuliya Lierlier
Title: Answer Set Programming and Automatic Optimization Methods in its Realm Read more about Answer Set Programming and Automatic Optimization Methods in its Realm with Dr. Yuliya Lierler
TRIPODS Kick Off Event
Towards Deeper Natural Language Understanding with Eduardo Blanco
Presenter: Eduardo Blanco
Title: Towards Deeper Natural Language Understanding Read more about Towards Deeper Natural Language Understanding with Eduardo Blanco
Dr. Lynna Chu, 'Graph-based Change-point Detection for Non-Euclidean and Multivariate Data', TADS Lunch-n-Learn
Presenter: Lynna Chu
Title: Graph-based Change-point Detection for Non-Euclidean and Multivariate Data
Lee Przybylski and Nate Harding, 'Two Challenge Problems from the Algorithms for Threat Detection Program', TADS Lunch-n-Learn
Presenter: Lee Przybylski and Nate Harding
Title: Two Challenge Problems from the Algorithms for Threat Detection Program
A New Approach to Integrating Graphical Models in Decision-Theoretic Planning with Dr. Eric Hansen
Presenter: Dr. Eric Hansen
Title: A New Approach to Integrating Graphical Models in Decision-Theoretic Planning Read more about A New Approach to Integrating Graphical Models in Decision-Theoretic Planning with Dr. Eric Hansen
Dr. Aditya Ramamoorthy, 'Leveraging Coding for Distributed Computing', TADS Lunch-n-Learn
Presenter: Dr. Aditya Ramamoorthy
Title: Leveraging Coding for Distributed Computing Read more about Dr. Aditya Ramamoorthy, 'Leveraging Coding for Distributed Computing', TADS Lunch-n-Learn
Dr. Xiongtao Dai, 'Modeling Longitudinal Data on Riemannian Manifolds', TADS Lunch-n-Learn
Presenter: Dr. Xiongtao Dai
Title: Modeling Longitudinal Data on Riemannian Manifolds Read more about Dr. Xiongtao Dai, 'Modeling Longitudinal Data on Riemannian Manifolds', TADS Lunch-n-Learn
Dr. Yumou Qiu, 'Large- Scale Inference for Correlation and Partial Correlation', TADS Lunch-n-Learn
Presenter: Dr. Yumou Qiu
Title: Large scale inference for correlation and partial correlation Read more about Dr. Yumou Qiu, 'Large- Scale Inference for Correlation and Partial Correlation', TADS Lunch-n-Learn
Dr. Qi Li, 'Pattern-enhanced Named Entity Recognition in Biomedical Literature', TADS Lunch-n-Learn
Dr. Hailiang Liu, 'Deep Learning and Differential Equations', TADS Lunch-n-Learn
Presenter: Dr. Hailiang Liu
Title: Deep Learning and Differential Equations Read more about Dr. Hailiang Liu, 'Deep Learning and Differential Equations', TADS Lunch-n-Learn
Dr. Matthew G. Panthani, 'The Role of Machine Learning in Materials and Chemical Discovery', TADS Lunch-n-Learn
Title: The Role of Machine Learning in Materials and Chemical Discovery
Presenter: Dr. Matthew G. Panthani
TADS planning meetings
TADS planning and Grant proposal development
TADS planning and Grant proposal development
Presenter: Dr. Carolyn Lawrence-Dill
Title: Computing on Natural Language Descriptions of Phenotypes: Making the language of genetics computable
Abstract: Read more about TADS planning and Grant proposal development
Dr. Max Morris, 'Decomposing Functional Model Inputs for Variance-Based Sensitivity Analysis', TADS Lunch-n-Learn
Presenter: Dr. Max Morris
Title: Decomposing Functional Model Inputs for Variance-Based Sensitivity Analysis Read more about Dr. Max Morris, 'Decomposing Functional Model Inputs for Variance-Based Sensitivity Analysis', TADS Lunch-n-Learn
Dr. Ali Jannesari, 'Shape_DNN: Getting deep neural networks in shape', TADS Lunch-n-Learn
Presenter: Dr. Ali Jannesari
Title: Shape_DNN: Getting deep neural networks in shape
Dr. Sigurdur Olafsson, TADS Lunch-n-Learn
Midwest Big Data Summer School
Durga Paudyal, 'Coupling Materials Physics with Data Science to Predict New Materials and Properties', TADS Lunch-n-Learn
Presenter: Durga Paudyal
Title: Coupling Materials Physics with Data Science to Predict New Materials and Properties
Dr. Guiping Hu, 'Maize Yield and Nitrate Loss Prediction with Optimal Machine Learning Model Ensembles', TADS Lunch-n-Learn
Presenter: Dr. Guiping Hu
Title: Maize Yield and Nitrate Loss Prediction with Optimal Machine Learning Model Ensembles Read more about Dr. Guiping Hu, 'Maize Yield and Nitrate Loss Prediction with Optimal Machine Learning Model Ensembles', TADS Lunch-n-Learn
Gavin Nop, 'Derivative-free Optimization', TADS Lunch-n-Learn
Presenter: Gavin Nop
Title: Derivative-free Optimization Read more about Gavin Nop, 'Derivative-free Optimization', TADS Lunch-n-Learn
Dr. Sarah Ryan, 'The DataFEWSion Traineeship for Innovations at the Nexus of Food Production, Renewable Energy and Water Quality', TADS Lunch-n-Learn
Presenter: Dr. Sarah Ryan
Title: The DataFEWSion Traineeship for Innovations at the Nexus of Food Production, Renewable Energy and Water Quality. Read more about Dr. Sarah Ryan, 'The DataFEWSion Traineeship for Innovations at the Nexus of Food Production, Renewable Energy and Water Quality', TADS Lunch-n-Learn
Midwest Big Data Summer School: Late Registration Open
Dr. Jing Dong, 'Electric Autonomous Taxis Dispatching', TADS Lunch-n-Learn
Presenter: Dr. Jing Dong
Topic: Electric Autonomous Taxis Dispatching Read more about Dr. Jing Dong, 'Electric Autonomous Taxis Dispatching', TADS Lunch-n-Learn
Dr. Ranjan Maitra, 'Three-dimensional Radial Visualization of High-dimensional Continuous or Discrete Datasets', TADS Lunch-n-Learn
Presenter: Dr. Ranjan Maitra
Topic: Three-dimensional Radial Visualization of High-dimensional Continuous or Discrete Datasets
Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Presenter: Dr. Wallapak Tavanapong
Topic: Dealing with class imbalance and a limited labeled dataset with active deep learning Read more about Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Dr. Pavan Aduri, 'Simultaneous Time and Memory Efficient Algorithm for Reachability in Graphs', TADS Lunch-n-Learn
Presenter: Dr. Pavan Aduri
Topic: Simultaneous Time and Memory Efficient Algorithm for Reachability in Graphs Read more about Dr. Pavan Aduri, 'Simultaneous Time and Memory Efficient Algorithm for Reachability in Graphs', TADS Lunch-n-Learn
Midwest Big Data Summer School: Regular Registration Open
Dr. Dan Nettleton, 'Random Forest Prediction Intervals', TADS Lunch-n-Learn
Presenter: Dr. Dan Nettleton
Topic: Random Forest Prediction Intervals Read more about Dr. Dan Nettleton, 'Random Forest Prediction Intervals', TADS Lunch-n-Learn
Dr. Namrata Vaswani, '(Dynamic) Robust PCA and Phaseless PCA', TADS Lunch-n-Learn
Presenter: Dr. Namrata Vaswani
Topic: (Dynamic) Robust PCA and Phaseless PCA Read more about Dr. Namrata Vaswani, '(Dynamic) Robust PCA and Phaseless PCA', TADS Lunch-n-Learn
Dr. Steve Holland, TADS Lunch-n-Learn
Dr. Kevin Liu, 'Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks', TADS Lunch-n-Learn
Presenter: Dr. Kevin Liu
Topic: Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks. Read more about Dr. Kevin Liu, 'Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks', TADS Lunch-n-Learn
Midwest Big Data Summer School: Early Registration Open
Presenter: Dr. Eric Weber
Topic: Distributed Data Analysis using the Kaczmarz Algorithm Read more about Midwest Big Data Summer School: Early Registration Open
Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Dr. Steve Holland, ' Big Data for Nuclear Power Plans and Creating Discoverable Data Repositories for Nondestructive Evaluation', TADS Lunch-n-Learn
Presenter: Dr. Steve Holland
Topic: Big Data for nuclear power plans and creating discoverable data repositories for nondestructive evaluation
Dr. Ranjan Maitra, 'Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering', TADS Lunch-n-Learn
Presenter: Dr. Ranjan Maitra
Topic: Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering Read more about Dr. Ranjan Maitra, 'Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering', TADS Lunch-n-Learn
Dr. Hal Schenck, 'Topological Data Analysis', TADS Lunch-n-Learn
Presenter: Dr. Hal Schenck
Topic: Topological data analysis
Read more about Dr. Hal Schenck, 'Topological Data Analysis', TADS Lunch-n-Learn
Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Dr. Chinmay Hegde, 'Theoretical Aspects of Neural Network Learning TADS', Lunch-n-Learn
Presenter: Dr. Chinmay Hedge
Topic: Theoretical aspects of neural network learning
Bill Gallus, TADS Lunch-n-Learn
Presenter: Bill Gallus Read more about Bill Gallus, TADS Lunch-n-Learn
Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Dr. Zhengyuan Zhu, 'Optimal Design of Experiment and Big Data Analysis', TADS Lunch-n-Learn
Presenter: Dr. Zhengyuan Zhu
Topic: Optimal Design of Experiment and Big Data Analysis
Theoretical and Applied Data Science (TADS) Lunch-n-Learn
Md Johirul Islam, 'MODE: Automated Neural Network Model Debugging via State Differential Analysis and Input Selection', TADS Lunch-n-Learn
Presenter: Md Johirul Islam
Topic: MODE: Automated Neural Network Model Debugging via State Differential Analysis and Input Selection
Dr. Eric Weber, 'Harmonic Analyses of Neural Networks', TADS Lunch-n-Learn
Presenter: Dr. Eric Weber
Topic: Harmonic Analysis of Neural Networks Read more about Dr. Eric Weber, 'Harmonic Analyses of Neural Networks', TADS Lunch-n-Learn
Md Johirul Islam, 'What Do Developers Ask About ML Libraries? A Large-scale Study Using Stack Overflow', TADS Lunch-n-Learn
Presenter: Md Johirul Islam
Topic: What Do Developers Ask About ML Libraries? A Large-scale Study Using Stack Overflow Read more about Md Johirul Islam, 'What Do Developers Ask About ML Libraries? A Large-scale Study Using Stack Overflow', TADS Lunch-n-Learn
Dr. Wei Le, 'Seeking for Machine Learning Approaches to Enable Software Testing in Parallel', TADS Lunch-n-Learn
Presenter: Dr. Wei Le
Topic: Seeking for machine learning approaches to enable software testing in parallel Read more about Dr. Wei Le, 'Seeking for Machine Learning Approaches to Enable Software Testing in Parallel', TADS Lunch-n-Learn
Dr. Jennifer Newman, 'What’s in a Picture: Steganography, Digital Image Forensics, and More', TADS Lunch-n-Learn
Presenter: Dr. Jennifer Newman
Topic: What’s in a Picture: Steganography, Digital Image Forensics, and more Read more about Dr. Jennifer Newman, 'What’s in a Picture: Steganography, Digital Image Forensics, and More', TADS Lunch-n-Learn
Dr. Myra Cohen, 'Evolutionary Algorithms and Hyper Heuristic Search', TADS Lunch-n-Learn
Presenter: Dr. Myra Cohn
Topic: Evolutionary algorithms and hyper heuristic search Read more about Dr. Myra Cohen, 'Evolutionary Algorithms and Hyper Heuristic Search', TADS Lunch-n-Learn
Dr. Jin Tian, 'Causal Interference', TADS Lunch-n-Learn
Presenter: Dr. Jin Tian
Topic: Causal inference Read more about Dr. Jin Tian, 'Causal Interference', TADS Lunch-n-Learn
Dr. Jonathan Smith, 'Concept Identification and Logic for Neural Network Layers', TADS Lunch-n-Learn
Presenter: Dr. Jonathan Smith
Topic: Concept identification and logic for neural network layers Read more about Dr. Jonathan Smith, 'Concept Identification and Logic for Neural Network Layers', TADS Lunch-n-Learn
Hamid Bagheri, 'Expressing and Verifying Probabilistic Assertions', TADS Lunch-n-Learn
Presenter: Hamid Bagheri
Expressing and Verifying Probabilistic Assertions, PLDI'14 paper Read more about Hamid Bagheri, 'Expressing and Verifying Probabilistic Assertions', TADS Lunch-n-Learn
Midwest Big Data Summer School
For information visit the Midwest Big Data Summer School website. Read more about Midwest Big Data Summer School