Veljko Milutinović
Computer Science · Indiana University
Publications
319
Citations
3,295
Est. group size
—
Recurring co-author estimate
Active years
48
Publishing since 1979
Veljko Milutinović works in computer systems, focusing on how to design specialized hardware and computing architectures that run algorithms faster and more efficiently. A recurring theme is the 'dataflow' paradigm, where computing is organized around the flow of data rather than a fixed sequence of instructions, and its application to machine learning, big data, and scientific simulations. Recent work also touches on supercomputing chips, analog solver circuits, and applied topics such as civil-engineering simulations.
Publication activity has generally slowed since a 2017 peak, settling to a lower output of roughly 3 papers per year over the last five years.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- On mapping of topological structures and mathematical algorithms onto specialized architectures for graph-based computing
Journal Of Big Data · 2026
- Twenty Years of Personality Computing: Threats, Challenges and Future Directions
arXiv (Cornell University) · 2025
- Algorithm profiling for architectures with dataflow accelerators
Journal Of Big Data · 2025
- Competition Law and Policy in Serbia
European Union and its neighbours in a globalized world · 2025
- Near instantaneous O(1) Analog Solver Circuit for Linear Symmetric Positive-Definite Systems
2025
- Research in computing-intensive simulations for nature-oriented civil-engineering and related scientific fields, using machine learning and big data: an overview of open problems
Journal Of Big Data · 2023
- Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains
Journal Of Big Data · 2023
- Fine Grain Algorithm Parallelization on a Hybrid Control-flow and Dataflow Processor
Research Square · 2023
- Synergizing Four Different Computing Paradigms for Machine Learning and Big Data Analytics
Lecture notes in networks and systems · 2023
- A runtime job scheduling algorithm for cluster architectures with dataflow accelerators
Advances in computers · 2022
- Energy efficient implementation of tensor operations using dataflow paradigm for machine learning
Advances in computers · 2022
- The Emerging Internet Congestion Control Paradigms
2022 11th Mediterranean Conference on Embedded Computing (MECO) · 2022
- Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Advances in systems analysis, software engineering, and high performance computing book series · 2022
- VLSI for SuperComputing: Creativity in R+D from applications and algorithms to masks and chips
Advances in computers · 2022
- A Survey of Some Important Algorithms Used in Military Applications
2022 11th Mediterranean Conference on Embedded Computing (MECO) · 2022
- Computer communications and networks×13
- Advances in computers×10
- SpringerBriefs in business×7
- arXiv (Cornell University)×7
- Journal Of Big Data×5
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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