This work is funded by an NIH-NIMH K99/R00 award. Research Interests : High Performance Data Analytics, Graph Analytics and Network Science, Machine Learning and Database Systems. What long-term project do you want to work on? Optimization. Machine Learning. Website Email: Phone: (734) 936-2831 Office: 3749 Beyster Bldg. Research Interests. Engineering 2, Room 341A. (2010), and Ph.D. (2016) in Mechanical Engineering from the Sharif University of Technology. Machine learning. Developing large-scale benchmark for machine learning on graphs. My research interests are at the intersection of machine learning and basic systems neuroscience. Machine learning theory aims to provide a mathematical analysis of, and algorithms for, the problems and issues that arise in getting machines to learn from experience. List of Recent Papers. We have built a team of internationally recognized experts in artificial intelligence and machine learning—in fact, Duke ECE is said to be among the world's top universities in AI/ML research. [May 2021] I am hiring FTEs and interns for several projects on perception, cognitive and controllable AI/VR/AR and Robotics Systems at our Seattle Research Center, including but not limited to machine learning and pattern recognition, multimedia and multi-sensor signal processing, computer vision, natural language processing, decision making . RESEARCH INTERESTS Machine learning/data mining/data science for the physical sciences; Real-world applications with a special interest in high-impact weather. Artificial Intelligence. Experts will cover wide range of topics relevant to cutting-edge research, new technologies, and emerging areas in the field. His research interests are in the broad areas of wireless communications, communication theory, signal processing, machine learning, and applied math. Machine Learning. Education. Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs. Research Interests. Departmental investigators engage in a range of quantitative topics including biostatistics, clinical trials, genetics and genomics, biomedical informatics, biomedical quantitative science and health data science research. Research Interests Machine learning theory and algorithms. In Proceedings of Thirty-seventh International Conference on Machine . Research Interests: Machine learning and statistical learning theory, scalable stochastic and distributed optimization, randomized numerical linear algebra, dimensionality reduction. AI/Machine Learning. I am a graduate student and Research Assistant at the Department of CSE, at Pennsylvania State University, co-advised by Dr. Rui Zhang and Dr. Rebecca J. Passonneau.My research interest lies in Natural Language Processing, Machine Learning, Computer Vision, and Data Mining. Specifically, my research group focuses on developing predictive methods to capture spatio-temporal, dynamic, and interpretable patterns in large-scale data. More concretely Robustness of Neural Networks, Robustification through Adversarial and Natural Perturbations, Explainable AI, Explainability using Visual Attributes, Studying Counterintuitive Visual Attributes and Adversarial Examples. Research Interests Machine Learning of Non-Linear Fluid Dynamics Uncertainty . Biography. Email: dzorin at cs.nyu.edu . Graph Neural Network for large-scale graph mining; Self-supervised learning; Transfer Learning; Bioinformatics and Computational Biology. Research Interests. My current research is focused on data-driven modeling and optimization of thermal and mechanical systems. Earlier, I have worked as a research intern at the Research Center for Advanced Science and Technology of the University of Tokyo under Dr. Hideki Koizumi, and also as a management consulting intern at PwC India. Yisong Yue is a professor in the Computing and Mathematical Sciences Department at the California Institute of Technology. I received my B.Sc. Denis Zorin. Dr. Alkhateeb is the recipient of the 2012 MCD Fellowship from The University of Texas at Austin, the 2016 IEEE Signal Processing Society Young Author Best Paper Award for his work on hybrid . Previously, I have also interned at the European Organization for Nuclear Research (CERN) where I worked on applying machine learning to high energy physics problems. Biases, inequities and long-term dynamics in intelligent systems. Research Interests. Dr. Douglas Allaire holds B.S., M.S., and Ph.D. degrees from the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology. DBLP. What are your career goals. Machine learning-based predictive models are gaining popularity for combining a huge amount of data into a single model and evaluating the model's predictive value for previously unseen individuals, e.g., at-risk and new patients. Machine learning Computer vision Neurobiology Animal behavior Computational neuroscience Prognostic modeling Traumatic brain injury. Machine Learning, Pattern Recognition, Multi-resolution Sensor Fusion, Target Detection, Dimensionality Reduction and Manifold Learning, Learning from Imprecise and Uncertain Labels, Weak Learning, Multiple Instance Learning, Metric Embedding. Research Interests. Journal of Machine Learning Research, 22(240):1-9, 2021. Research interests. Our faculty are world renowned in the field, and are constantly recognized for their contributions to Machine Learning and AI. theoretical computer science. MEng in Computer Science, 2018. Machine Learning. Research Interests: Game Theory and Applications, Resilient and Secure Socio-Cyber-Physical Systems, Adversarial Machine Learning and Signal Processing, Human-Robot Interactions, Internet of Things, Game and Decision Theory for Cyber Security, Economics and Optimization of Infrastructure Systems, Resource Allocations in Communication Networks Uncertainty quantification. M.Sc. Education . Publications 2021 Research Interests Prof. Abdelfattah's research lies at the intersection of computer architecture and machine learning, with a special focus on reconfigurable computing. Machine Learning Systems; Intelligent Networking: Network Designing and Optimization based on Machine Learning and Deep Learning; Programmable Networks: Software Defined Networking (SDN), Network Function Virtualization (NFV) Data Center Networking and Cloud Computing; Available positions: research assistant positions are available for self-motivated Ph.D. students who are interested in conducting research on the topic of signal processing, machine learning and networking for Fall 2022 (click for details). of Computer Science and Engineering and Department of Biomedical Informatics, The Ohio State University, USA. Dr. Alkhateeb is the recipient of the 2012 MCD Fellowship from The University of Texas at Austin, the 2016 IEEE Signal Processing Society Young Author Best Paper Award for his work on hybrid . Research Interests: machine learning Teaching and Research. Her research interests focus on machine learning, data mining, bioinformatics and health informatics. Research Interests. By applying machine learning approaches to more and more complex flow configurations we want to eventually be able to amalgamate the two approaches and uncover new machine learning algorithms and new insights into the underlying fluid dynamics in the process. Reinforcement Learning. Information Reciprocity. Research Interests Machine learning for graph-structured data. Human-centered machine learning. Research Interests. Research Interests. Amin Assareh is a professor of computer science in the Khoury College of Computer Sciences at Northeastern University. Research Interests Machine learning Deep learning Computational biology Current Research Interests: Machine Learning and Computer Vision. Interpretable Models. Silver Professor of Computer Science and Mathematics, Chair, Computer Science Department. My name is Girish L- I am a researcher at the Visvesvaraya Technological University.Currently, I am pursuing a PhD in Artificial Intelligence in Next Generation Network under supervision of Prof. Sridhar K N Rao.. My research focus is on Machine Learning, Deep Learning, Software Defined Networking (SDN) and Network Function Virtualization (NFV). I am a graduate student at MILA & Université de Montréal, advised by Ioannis Mitliagkas. My research interests are machine learning, data analytics, and social media analysis motivated by real-world problems in social informatics, health informatics, and personalization. Research Interests: theoretical foundations of deep learning; machine learning (ML) for vulnerability identification; large-scale machine learning (ML) Featured Course: STAT 991: Topics in Deep Learning Awards, Honors, and Distinctions. His research interests are in data-efficient machine learning, with a special interest in probabilistic methods for real-time inference and sensor fusion. Patents. Jieming Shi*, Tianyuan Jin* ,, Renchi Yang, Xiaokui Xiao, Yin Yang. McKnight Foundation. CSE 6240, Spring 2018 . My long-term goals include improving mathematical understanding of empirical phenomena, and developing principled approaches to modern deep learning applications. Research Interests: Machine Learning for Imaging, Artificial Intelligence, Predictive Analytics, Biomarker Discovery Denis Zorin. ribbon. My current projects are focused on developing deep learning techniques for understanding population-level neural computations underlying perceptual decision making. Fish, Benjamin. Multi-Source Data Mining. Research Interests: Machine learning and statistical learning theory, scalable stochastic and distributed optimization, randomized numerical linear algebra, dimensionality reduction. Machine Learning and Economics: Strategic behavior, Stability, Fairness.. Statistical Inference in Dynamic Systems: Kernel ODE, ODE inference, SGD dynamics.. High-Dimensional Nonparametric Inference: Double machine learning, Knockoffs, FDR control.. Research Interests: Machine Learning and Data Mining: Rishabh Sharma : EMAIL: rishabh230795@gmail.com: Research Interests: Machine Learning and Computer Vision: Raunak Sarbajna : EMAIL: Raunak.DBL@gmail.com: Research Interests: Geographic Information System, Remote Sensing and Geospatial Data Analysis: I am interested in Machine Learning, Natural Language Processing, Neuro-Symbolic AI and Reinforcement Learning. Nov. 2019: New preprint: Deep Ordinal Classification with Inequality Constraints. Text Mining and Knowledge Discovery. Work Experiences. Summary. Machine learning: Deep Learning, Explainable AI, Network Analysis ; Computational Biology and Medicine: Single Cell Biology, Network Biology, Biomedical Ontology Broadly, his academic interests are machine learning and data mining. His Research area is Materials Design using Machine Learning; Materials currently focused are Multi-Principal Element Alloys (MPEAs). Brain Imaging Analysis and Biomedical Research: Multi-modality analysis, Neuroimaging, Cardiovascular disease. in Computer Science and Technology, Soochow University, 2016 - 2020. Website Email: Office: 2649 Beyster. Graph Neural Networks. His current research focuses on the development of computational methods for the . Machine learning and mental health. Interests. Research Interests. Machine learning Weakly supervised learning Semi-supervised learning Regularization. Leveraging large amounts of data to learn useful graph representations. Scholar. Sep. 2019: New preprint: Deep Weakly-supervised Learning Methods for . Learn more about the research interests of our faculty and staff here. My main research interests are in machine learning theory, on-line algorithms, and approximation algorithms. Research Interests Machine learning, particularly data selection, zero-shot learning, and adversarial learning. I am a PhD student in Statistics and Econometrics at University of Chicago, advised by Prof. Mladen Kolar.My research interests include machine learning, federated learning, probabilistic graphical models, high-dimensional statistics and optimization, with a focus on developing novel methodologies with both practical applications and theoretical guarantees. BIOGRAPHY Dr. Amy McGovern is a professor in the School of Computer Science at the University of Oklahoma and in the School of Meteorology at the University of Oklahoma. His lab focuses on various aspects of creating intelligent systems, with an emphasis on principled learning and optimization algorithms for autonomous systems and smart grids. The research will explore the data gathering phase, where a smartphone will be used as a data collection device to replace the telematics device. 2021.07—Present Postdoctoral research fellow at A*STAR, Singapore Machine Learning: meta-learning, transfer learning, time series prediction, anomaly detection, few-shot learning Research Interests: Machine learning, signal and image analysis, statistical modeling, optimization techniques and their applications to developing computational tools to analyze and understand the big data in the biomedical field, particularly related to brain research. Research Interests Human & Emotion Oriented Computing, Human Computer Interaction, Distributed Systems, Biomedical Informatics, Cybersecurity, . Ph.D. Research Title is "Computational, Statistical & Experimental studies on Multi-Principal Element Alloys . Proceedings of the VLDB Endowment (PVLDB 2020)), 13 (7): 966-978, 2020. Research Interests → Machine Learning → Deep Learning → Cognitive Computing → Biometrics → Secure ML View Profile. multi-armed bandits. Machine Learning Theory. He gave a tutorial on Machine Learning with Signal Processing at ICML 2020 and was one of the organisers of MLSP 2020. About me. Research Interests. STEM education. 2020 Research Interests: Reinforcement Learning, Machine Learning, Computational Game Theory, Adaptive Human Computer Interaction. My research interests include machine learning, natural language processing, and human computer interaction. Multi-Instance Learning. I am an Assistant Professor in the School of Statistics at the Southwestern University of Finance and Economics.I completed my Ph.D. and postdoctoral training in the Department of Biostatistics at Columbia University, under the supervision of Professors Yuanjia Wang and R. Todd Ogden. Natual Language Processing. Research Interests: Machine learning and statistical learning theory, scalable stochastic and distributed optimization, randomized numerical linear algebra, dimensionality reduction. Cyber Security: AI for security, attack and defense models, action recommendations for network resilience, malware propagation models. Machine Learning. Dr. Zhang is a William Wulf Faculty Fellow and Professor of Computer Science, with a joint appointment in the Department of Biomedical Engineering and School of Data Science at University of Virginia. [Paper Acceptance] December 30, 2021: Our paper, Reservoir Computing Meets Extreme Learning Machine in Real-Time MIMO-OFDM Receive Processing, has been . Assistant Professor, Electrical Engineering and Computer Science. Prabhash Kumar, Ph.D. Prabhash Kumar is a PMRF Research Scholar in IIT Kharagpur (December 2020 Cycle). I will be working on Machine Learning topics. Research Interests → Internet of Things Security → Healthcare Applications → Blockchain for Industry 4.0 → UAV / Drone Networks Research Interests : High Performance Data Analytics, Graph Analytics and Network Science, Machine Learning and Database Systems. What do you enjoy most about your work? Under review/preprints • Machine Learning and Deep Learning. Research Interests. 16 Nov 2021 4:30 PM — 4:50 PM Boston (in-person, 7-11 Nov 2021) and Virtual (15-19 Nov 2021) Samuel D. Young, Zixuan Wang, Nirala Singh, Bryan Goldsmith. applications of information theory to learning, optimization, and probability He gave a tutorial on Machine Learning with Signal Processing at ICML 2020 and was one of the organisers of MLSP 2020. Research Interests - Machine Learning (Deep Learning, Adversarial Learning, Security and Robustness, Computer Vision, Natural Language Processing) - Operations Research (Large-scale optimization, Transportation, Project Management) Do We Need Zero Training Loss After Achieving Zero Training Error? At Aalto, Arno leads a research group in machine learning. His research interests lie primarily in the theory and application of statistical machine learning. convex optimization. Validation of a machine learning algorithm to guide the diagnosis of myocardial infarction. Software Engineer Intern Project Slides. Contact Research Interests: Machine learning, natural language processing, and data mining. I had completed my undergraduate double major program in Mathematics and Computer . Learning from human behavioral data and implicit feedback in search and recommender systems. Research interests • Machine learning: statistical learning theory, reinforcement learning, causal inference • Operations research: decision-making, applied probability, optimization. Research interests: machine learning, optimization, reinforcement learning, computational mathematics, energy Ahmad al-Tawaha MS: Mechanical Engineering, Jordan University of Science and Technology Machine learning; Neural networks; Representation learning; Weakly supervised learning; Interpretable machine learning; News. Machine Learning: adversarial machine learning and robustness, online and distributed learning, unsupervised and semi-supervised learning. My detailed cv can be found here. Joining academia or industry both are interesting for me. My current research interest is machine learning on graphs and manifolds, and their applications for understanding molecular mechanisms and improving genotype-phenotype predictions in complex biological systems. At Aalto, Arno leads a research group in machine learning. He seeks to codesign algorithms and hardware for the next generation of machine-learning-centric computer systems. 2021; Peer Recognition Honor. The 38th International Conference on Machine Learning (ICML), 7192-7203, 2021. Natural Language Processing (Information Extraction) Human Computer Interaction. (2007), M.Sc. online algorithms (in particular metrical task systems and k-server) statistical network analysis, random graphs and random matrices. Prior to joining MILA, I was a Research Fellow at Microsoft Research Lab India, where I worked with Amit Sharma on Machine Learning and Causal Inference. Research Interests. Research Interests Machine learning applications in finance & economics, Knowledge representation and reasoning, Natural language processing Joe Johnson. Website Mentoring Plan Email: Office: 2649 Beyster His research interests broadly lie in machine learning and AI, optimization, dynamical systems and control theory, and network science. Research Projects/Funding. Dealing with intact topics in my field of study. Research Interests . Research interests include: Machine Learning, Text Mining, Information Retrieval, Computational Statistics and Simulation/Statistical Modeling, Stochastic Modeling Hongning Wang received his Ph.D. from the Department of Computer Science at University of Illinois at Champaign-Urbana in 2014, and joined University of Virginia as Assistant . Developing machine learning methods that can efficiently and effectively handle graph-structured complex data. machine learning. in Computing Science, University of Alberta, 2021 - B.E. Affiliations : Professor, Dept. Dec. 2019: New preprint: Convolutional STN for Weakly Supervised Object Localization and Beyond. I am a researcher at Data Science Research Labs, NEC Corporation . My research interests lie in the broad area of machine learning. Website Mentoring Plan Email: Office: 2649 Beyster His research interests are in data-efficient machine learning, with a special interest in probabilistic methods for real-time inference and sensor fusion. Our engineers urge computer hardware to higher levels of performance by efficiently allocating the computing resources that machine learning applications require, allowing us to . Single-cell analysis; Microbiome data analysis; Education. Publications Conference Papers (Full Review) T. Ishida, I. Yamane, T. Sakai, G. Niu, M. Sugiyama. Computer vision, particularly image clustering, classification, and retrieval, motion segmentation, activity recognition, and video summarization. His research interests are in the broad areas of wireless communications, communication theory, signal processing, machine learning, and applied math. He received his PhD in Computer Science from Kent State University, where his dissertation focused on Ensemble Learning. Phone: 831-459-1721. Affiliations : Professor, Dept. S V N Vishwanathan. of Computer Science and Engineering and Department of Biomedical Informatics, The Ohio State University, USA. Research Interests. Machine Learning; . Research Interests Machine Learning for Networking Systems (NetAI) Next-Generation Internet Architecture Social Network Analysis Publications Polygon: A QUIC-Based CDN Server Selection System Supporting Multiple Resource Demands. Research Interests: Data Analytics, Decision making (control, optimization and game theory), Logistics/Supply Chain/Industrial Engineering, Mathematics, Statistics, and Foundations, Machine Learning and AI Algorithms, Reinforcement Learning and Planning, Vision and video analytics, Change point detection and its applications . Research Interests. This work has been presented at the ICML 2021 Subset Selection in Machine Learning: From Theory to Practice Workshop. Professor, Computer Science. My name is Songgaojun Deng, and my preferred name is Amy.I am a forth-year Ph.D. candidate in the Department of Computer Science at Stevens Institute of Technology, supervised by Dr. Yue Ning.My research interests are machine learning, data analytics, and social media analysis motivated by real-world problems in social informatics and health informatics. Batch and online multi-armed bandits and reinforcement learning. My research interests are machine learning, deep learning, medical statistics, cardiology and R Shiny app development as clinical decision support tools. This research aims to create a viable system to gather data through a mobile device and apply machine learning algorithms to classify different types of driving events. Divyat Mahajan. Research Interests: Machine learning, algorithms for massive . of the 22nd ACM/IFIP Middleware Conference (Middleware'21), Industry Track, Virtual Event, Canada, Dec. 2021. The Machine Learning Department at Carnegie Mellon University is ranked as #1 in the world for AI and Machine Learning, we offer Undergraduate, Masters and PhD programs. Research Intern Tencent AI Lab, Shenzhen, Feb 2020 - Jun 2021. Proc. Website. Research Interests. Youzhi Luo, Keqiang Yan, Shuiwang Ji: GraphDF: A Discrete Flow Model for Molecular Graph Generation. Duke, Pratt School of Engineering. My research interests include Machine Learning and Data Mining, including Transfer Learning, Multi-task Learning, Multi-view Learning and Recommendation Systems. Interests. Multi-Task Learning & Transfer Learning. Technological Innovations in Neuroscience Award. I am interested in leveraging machine learning techniques to reduce the computational cost of engineering analyses. 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At ICML 2020 and was one of the organisers of MLSP 2020 received his PhD Computer... Recommender systems '' > Tianyuan Jin *,, Renchi Yang, Xiaokui Xiao Yin... Deep Weakly-supervised learning methods that can efficiently and effectively handle graph-structured complex data for Security attack. Dynamic, and developing principled approaches to modern deep learning techniques for understanding population-level Neural computations underlying decision. And optimization of thermal and Mechanical systems lie primarily in the field, and developing principled approaches to modern learning. Group in machine learning Computer vision Neurobiology Animal behavior Computational neuroscience Prognostic Traumatic! Allaire holds B.S., M.S., and interpretable patterns in large-scale data Language Processing, video! Papers ( Full Review ) T. Ishida, I. Yamane, T. Sakai, G. Niu, Sugiyama... That can efficiently and effectively handle graph-structured research interests machine learning data to work on developing learning! > Dr of Biomedical Informatics, the Ohio State University, USA are constantly for.