Prof. Jens Palsberg — Research Profile
University of California, Los Angeles · Computer Science
Graduate application deadlines
Computer Science
PhD in Computer Science
Fall 2027Application deadline
Dec 15, 2026 23:59 PST
No year on the page — check the original to confirm these dates are for this cycle.
Source: cs.ucla.eduChecked Nov 2, 2026MS in Computer Science
Fall 2027Application deadline
Dec 15, 2026 23:59 PST
No year on the page — check the original to confirm these dates are for this cycle.
Source: cs.ucla.eduChecked Nov 2, 2026
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Prof. Jens Palsberg at University of California, Los Angeles Computer Science lists Compilers, Embedded systems, Programming languages as their registered research area.
Research keywords
Recent papers
- Verified Pauli-Product Measurement Compilation for Fault-Tolerant Quantum ComputationPreprintarXiv (Cornell University) · Oct 20
- Distance-Independent Universality of Clifford+TPreprintarXiv (Cornell University) · Oct 2
- Reinforcement Learning for Syndrome ExtractionPreprintarXiv (Cornell University) · Sep 10
From OpenAlex · papers whose author affiliation matches this university
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Labs that recently published on topics this lab's recent papers share
Shared topic: Quantum Computing Algorithms and Architecture
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Fast Random Compilers for Time-Dependent and Time-Independent Lindbladian SimulationPreprintarXiv (Cornell University) · Oct 4Yongshan Ding Lab
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Modeling Quantum Error Detection with Transition MatricesPreprintarXiv (Cornell University) · Sep 10Sitan Chen Lab
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Out-of-control Hamiltonian LearningPreprintarXiv (Cornell University) · Oct 5
Other labs in this department
- Aditya Grover Lab
Probabilistic machine learning for unsupervised representation learning and sequential decision making
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Probabilistic and logical reasoning and its applications, Diagnosis, planning, system design and analysis
- Alexander Sherstov Lab
Theoretical computer science
- Amit Sahai Lab
Theoretical computer science, Foundations of cryptography, Computer security, Cybersecurity and future internet
- Baharan Mirzasoleiman Lab
Machine learning, Data mining, Optimization, Approximation algorithms
- Blaise-Pascal Tine Lab
Systems, compilers and hardware support for heterogeneous architectures, Reconfigurable and hybrid architectures for high performance computing using FPGAs, Software-hardware codesign of custom accelerators in Graph Analytics, Relational Databases and Machine Learning