Alessandro Morari, Ph.D.
Technical Leader and Senior Research Scientist
High Performance Computing and Machine Learning
IBM Research
Technical leader and researcher with a decade of experience in High Performance Computing (HPC) and five years in Machine Learning.
In my current role, I am leveraging HPC to scale Deep Learning algorithms. I've also engineered large-scale Generative ML algorithms for the analysis and generation of source code, resulting in the creation of the IBM Watson Code Assistant.
Previously, I evaluated and improved Linux OS performance and scalability for IBM's Summit and Sierra supercomputers, the world's fastest in 2018. I also led the development of PNNL’s GEMS, a high performance, massively multithreaded graph database, which resulted in the spin-off of Trovares, a startup offering highly scalable cloud-based graph analytics.
I have taught a graduate course on how to leverage HPC for Machine Learning, and I have authored 24 academic publications in international conferences and journals. Additionally, I have contributed to 17 patents.
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.
Current Research
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.