Alessandro Morari, Ph.D.
Alessandro Morari, Ph.D.
GPU Performance Optimization for AI @NVIDIA
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Technical Leader and Researcher with over 17 years of experience in High Performance Computing and Deep Learning. Currently working on GPU kernels performance for AI frontier-labs and top hyper-scalers.
My tenure includes spearheading the AI for Code research at IBM, which led to the creation of the Watson Code Assistant. In 2018, I contributed to developing the Summit and Sierra supercomputers, the world's fastest supercomputers. In 2014, I spearheaded PNNL's GEMS project, a high-performance, massively multithreaded graph database, which led to the spinoff of the startup Trovares.
I developed and taught the first graduate course on High Performance Machine Learning at New York University. I hold a PhD in Computer Architecture and I have contributed to more than 30 academic publications and 15+ patents.
Education
Education
Ph.D. in Computer Architecture, Polytechnic University of Catalunya.
M.Sc. in Computer Engineering, University of Rome Tor Vergata.
B.Sc. in Computer Engineering, Roma Tre University.
Selected Papers
Selected Papers
Towards Learning (Dis)-Similarity of Source Code from Program Contrasts. Authors: Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, Saikat Chakrabort. ACL 2022.
VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements. Authors: Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail Kaiser, Baishakhi Ray. SANER 2022.
D2a: A dataset built for ai-based vulnerability detection methods using differential analysis. Authors: Yunhui Zheng, Saurabh Pujar, Burn Lewis, Luca Buratti, Edward Epstein, Bo Yang, Jim Laredo, Alessandro Morari, Zhong Su. ICSE-SEIP 2021.
Data-Driven AI Model Signal-Awareness Enhancement and Introspection. Authors: Sahil Suneja, Yufan Zhuang, Yunhui Zheng, Jim Laredo, Alessandro Morari. arXiv preprint arXiv:2111.05827.
Contrastive Learning for Source Code with Structural and Functional Properties. Authors: Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, Saikat Chakraborty. arXiv preprint arXiv:2110.03868.
Software Vulnerability Detection via Deep Learning over Disaggregated Code Graph Representation. Authors: Yufan Zhuang, Sahil Suneja, Veronika Thost, Giacomo Domeniconi, Alessandro Morari, Jim Laredo. arXiv preprint arXiv:2110.03868.
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization. Authors: Sahil Suneja, Yunhui Zheng, Yufan Zhuang, Jim Laredo, Alessandro Morari. ESEC/FSE 2021.
Towards Reliable AI for Source Code Understanding. Authors: Sahil Suneja, Yunhui Zheng, Yufan Zhuang, Jim A Laredo, Alessandro Morari. ACM Symposium on Cloud Computing 2021. SoCC 2021.
Cush: Cognitive scheduler for heterogeneous high performance computing system. Authors: Giacomo Domeniconi, Eun Kyung Lee, V Venkataswamy, S Dola. DRL4KDD 2019.
Presentations and Seminars
Presentations and Seminars
Links
Links
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