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I am a software developer and researcher with a particular interest in programming language theory, compilers, and static program analysis. I am currently working as a software developer in the HotSpot compiler team at Oracle.

I received my PhD degree in Information and Communication Technology in 2023 from KTH Royal Institute of Technology, Stockholm, Sweden.

I am working as a software developer in the HotSpot JVM compiler team.

Continuation of my work as a doctoral student (see below).

I did research in probabilistic programming, an interdisciplinary field with influences from computer science, probability theory, statistics, machine learning, and artificial intelligence. I focused on developing mathematical foundations and efficient compilers for probabilistic programming languages.

I worked as a teaching assistant in multiple courses (see Teaching).

I worked with the Unison project: a code generator using a combined constraint model of register allocation and instruction scheduling to generate potentially optimal code. My task was to update the target description of a processor to the most recent version within the project.

I assisted high school students with mathematics and related topics during the semesters.

I worked as a front-end Android and back-end PHP developer.

I worked with both front-end and back-end web development in JavaScript and PHP.

Doctoral thesis in Information and Communication Technology with specialization in Software and Computer Systems (see Theses). My main supervisor was David Broman.

Degree Programme in Computer Science and Engineering (Datateknik).

European Association for Programming Languages and Systems (EAPLS)

European Symposium on Programming (ESOP)

[ DiVA | PDF ]

I was in charge of the overall planning and execution of one course round (approximately 200 students). I also gave two lectures.

I was a core member of the teaching team, and my tasks included exercises, seminars, labs, examination, and a few lectures.

I worked as a teaching assistant at lab sessions. The main task was to help and examine students.

PROBPROG

NeurIPS

• Daniel Lundén, Lars Hummelgren, Jan Kudlicka, Oscar Eriksson, and David Broman. Suspension Analysis and Selective Continuation-Passing Style for Higher-Order Probabilistic Programming Languages. ESOP 2024. [ Springer Link | PDF | arXiv (extended) | PDF (extended) ]
• Daniel Lundén, Gizem Çaylak, Fredrik Ronquist, David Broman. Automatic Alignment in Higher-Order Probabilistic Programming Languages. ESOP 2023. EAPLS Best Paper Award. [ Springer Link | PDF | arXiv (extended) | PDF (extended) ]
• Daniel Lundén, Joey Öhman, Jan Kudlicka, Viktor Senderov, Fredrik Ronquist, David Broman. Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference. ESOP 2022. Distinguished Artifact Award. [ Springer Link | PDF | arXiv (extended) | PDF (extended) ]
• Daniel Lundén, Johannes Borgström, and David Broman. Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages. ESOP 2021. [ Springer Link | PDF | arXiv (extended) | PDF (extended) ]
• Gizem Caylak, Daniel Lundén, Viktor Senderov, and David Broman. Statically and Dynamically Delayed Sampling for Typed Probabilistic Programming Languages. SLE 2024. [ ACM | PDF ]
• Fredrik Ronquist, Jan Kudlicka, Viktor Senderov, Johannes Borgström, Nicolas Lartillot, Daniel Lundén, Lawrence Murray, Thomas B. Schön, and David Broman. Universal probabilistic programming offers a powerful approach to statistical phylogenetics. In Communications Biology 4. 2021. [ Nature | bioRxiv | PDF ]
• Lawrence M. Murray, Daniel Lundén, Jan Kudlicka, David Broman, and Thomas Schön. Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs. AISTATS 2018. [ AISTATS | PDF ]

• Daniel Lundén. Correct and Efficient Monte Carlo Inference for Universal Probabilistic Programming Languages. Doctoral thesis, KTH Royal Institute of Technology. 2023. [ DiVA | PDF | Errata ]
• Daniel Lundén. Delayed Sampling in the Probabilistic Programming Language Anglican. Master's thesis, KTH Royal Institute of Technology. 2017. [ DiVA | PDF ]
• Erik Forsblom, Daniel Lundén. Factoring Integers with Parallel SAT Solvers. Bachelor’s thesis, KTH Royal Institute of Technology. 2015. [ DiVA | PDF ]

• Viktor Senderov, Jan Kudlicka, Daniel Lundén, Viktor Palmkvist, Mariana P. Braga, Emma Granqvist, David Broman, Fredrik Ronquist TreePPL: A Universal Probabilistic Programming Language for Phylogenetics. 2023. [ bioRxiv | PDF ]

• Daniel Lundén, Joey Öhman, David Broman. Compilation of Universal Probabilistic Programs to GPGPUs. PROBPROG 2020. [ PROBPROG | PDF | Poster ]
• Daniel Lundén, David Broman, Fredrik Ronquist, and Lawrence M. Murray. Automatic Discovery of Static Structures in Probabilistic Programs. PROBPROG 2018. [ PROBPROG | PDF | Poster ]
• Daniel Lundén, David Broman, and Lawrence M. Murray. Combining Static and Dynamic Optimizations Using Closed-Form Solutions. PPS 2018. [ PPS | PDF | Poster ]