Smart Information Flow Technologies (United States)
- World rank, all time
- #28,183 of 34,923
- Rank in United States
- #5,914 of 7,310
- Research works
- 158 ▼ 23% vs 2018-21
- Citations
- 1.9k 11.9 per fractional work
- Top-10% rate
- 4.3% all institutions 10.0%
- vs its own fields
- 0.97× 1.00× is exactly expected
- Open access
- 23% world 40%
- International
- 10% world 18%
Which fields of science does Smart Information Flow Technologies (United States) work in?
In all years, 61% of research at Smart Information Flow Technologies (United States) is in Physical Sciences, 30% in Social Sciences. Its largest fields are Computer Science (44%), Psychology (14%), Engineering (14%). It does 1.5× the world's share of Physical Sciences.
Each ring splits the one inside it: the four domains of science, their fields, their subfields. Size is fractional works in all years. Every slice is a page; the interactive view zooms down to single topics and colours each by how much more of it this institution does than the world.
Its 4 domains and 18 fields, with their numbers
- Physical Sciences9660.7%
- Computer Science7044.2%
- Engineering2314.3%
- Physics and Astronomy21.4%
- Mathematics10.4%
- Chemistry10.3%
- Chemical Engineering00.1%
- Earth and Planetary Sciences00.0%
- Social Sciences4830.2%
- Psychology2314.4%
- Social Sciences127.5%
- Decision Sciences63.8%
- Business, Management and Accounting42.5%
- Arts and Humanities21.3%
- Economics, Econometrics and Finance10.7%
- Health Sciences137.9%
- Medicine106.0%
- Health Professions31.9%
- Life Sciences21.1%
Field profile
Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.
Rings at 0.5×, 1× and 2×. Widest outward: Pharmacology, Toxicology and Pharmaceutics, 7.7×. Every wedge is a field page.
All 17 fields, with their numbers
- Pharmacology, Toxicology and Pharmaceutics7.70×0 works
- Computer Science4.16×6 works
- Mathematics3.08×1 works
- Decision Sciences2.26×0 works
- Health Professions1.54×1 works
- Economics, Econometrics and Finance1.48×1 works
- Chemical Engineering1.29×0 works
- Neuroscience1.21×0 works
- Social Sciences1.20×3 works
- Engineering1.06×3 works
- Psychology0.83×0 works
- Arts and Humanities0.63×0 works
- Business, Management and Accounting0.56×0 works
- Biochemistry, Genetics and Molecular Biology0.46×0 works
- Medicine0.46×2 works
- Physics and Astronomy0.41×0 works
- Earth and Planetary Sciences0.08×0 works
- Pharmacology, Toxicology and Pharmaceutics 7.7×
- Computer Science 4.2×
- Mathematics 3.1×
- Decision Sciences 2.3×
- Health Professions 1.5×
- Economics, Econometrics and Finance 1.5×
- Chemical Engineering 1.3×
- Neuroscience 1.2×
- Social Sciences 1.2×
- Engineering 1.1×
- Psychology 0.8×
- Arts and Humanities 0.6×
- Business, Management and Accounting 0.6×
- Biochemistry, Genetics and Molecular Biology 0.5×
- Medicine 0.5×
- Physics and Astronomy 0.4×
- Earth and Planetary Sciences 0.1×
Who are the top researchers at Smart Information Flow Technologies (United States)?
Ranked on the quality score, Robert P. Goldman, John Maraist and Christopher Geib lead among researchers whose main affiliation is Smart Information Flow Technologies (United States).
- 1
Robert P. Goldman
United States · #1,318,315 worldwide 3.7k citations · 200 works
- 2
John Maraist
United States · #1,830,017 worldwide 571 citations · 19 works
- 3
Christopher Geib
United States · #1,845,180 worldwide 1.9k citations · 85 works
- 4
Christopher A. Miller
United States · #3,417,346 worldwide 1.2k citations · 89 works
- 5
Sonja Schmer-Galunder
United States · #3,532,986 worldwide 213 citations · 42 works
- 6
Tammy E. Ott
United States · #3,567,384 worldwide 262 citations · 39 works
- 7
Dan Thomsen
United States · #4,006,335 worldwide 301 citations · 54 works
- 8
Harry B. Funk
United States · #4,116,042 worldwide 182 citations · 19 works
- 9
Matthew D. McLure
United States · #4,409,590 worldwide 133 citations · 17 works
- 10
Jeffrey M. Rye
United States · #4,806,541 worldwide 117 citations · 29 works
Which keywords describe research at Smart Information Flow Technologies (United States)?
By fractional works in all years, weighted toward what it does more of than the world: Cognitive Load, Autonomous Vehicles, Trust, Human Factors, Automation, Driver Distraction, Autonomous Systems and Knowledge Representation.
- Reinforcement Learning
- Dialectical Argumentation
- Formal Methods
- Social Media
- Negotiation
- Ontology
- Clinical Alarms
- Knowledge Management
- Answer Set Programming
- Semantic Web
- Agent-Based Modeling
- Multi-Agent Systems
- Temporal Logic
- Description Logics
- Heuristic Search
- Knowledge Representation
- Driver Distraction
- Human Factors
- Trust
- Machine Learning
- Cognitive Load
- Autonomous Vehicles
- Deep Learning
- Automation
- Autonomous Systems
- Cognitive Architecture
- Planning Systems
- Model Checking
- Simulation
- Artificial Intelligence
- Data Integration
- Risk Assessment
- Modal Logic
- Alarm Fatigue
- Linked Data
- Software Engineering
- IoT Security
- Detection
- Argumentation Frameworks
- Collision Avoidance
Size is fractional works in all years in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 40 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 40 words, with their numbers
- Cognitive Load15▲ 239×2 topics
- Machine Learning14▲ 4.0×22 topics
- Autonomous Vehicles13▲ 58×3 topics
- Trust13▲ 31×3 topics
- Deep Learning12▲ 3.7×21 topics
- Human Factors12▲ 139×3 topics
- Automation12▲ 129×1 topic
- Driver Distraction12▲ 257×1 topic
- Autonomous Systems11▲ 228×3 topics
- Knowledge Representation11▲ 48×3 topics
- Cognitive Architecture10▲ 184×2 topics
- Heuristic Search10▲ 323×1 topic
- Planning Systems10▲ 323×1 topic
- Description Logics10▲ 63×2 topics
- Model Checking8▲ 48×3 topics
- Temporal Logic8▲ 64×2 topics
- Simulation7▲ 14×6 topics
- Multi-Agent Systems7▲ 23×5 topics
- Artificial Intelligence6▲ 4.7×7 topics
- Agent-Based Modeling6▲ 22×5 topics
- Data Integration6▲ 15×4 topics
- Semantic Web6▲ 24×3 topics
- Risk Assessment6▲ 5.8×5 topics
- Answer Set Programming5▲ 94×1 topic
- Modal Logic5▲ 58×1 topic
- Knowledge Management5▲ 7.1×8 topics
- Alarm Fatigue5▲ 231×1 topic
- Clinical Alarms5▲ 231×1 topic
- Linked Data5▲ 41×1 topic
- Ontology5▲ 18×1 topic
- Software Engineering5▲ 40×2 topics
- Negotiation4▲ 61×2 topics
- IoT Security4▲ 16×2 topics
- Social Media4▲ 3.5×7 topics
- Detection4▲ 8.6×2 topics
- Formal Methods4▲ 65×2 topics
- Argumentation Frameworks4▲ 110×1 topic
- Dialectical Argumentation4▲ 110×1 topic
- Collision Avoidance3▲ 18×4 topics
- Reinforcement Learning3▲ 26×3 topics
Which research topics does Smart Information Flow Technologies (United States) publish most on?
By volume in 2022-now: Evacuation and Crowd Dynamics, Hungarian Social, Economic and Educational Studies, Hate Speech and Cyberbullying Detection and Modular Robots and Swarm Intelligence.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Evacuation and Crowd Dynamics Ocean Engineering 1 works
- 2 Hungarian Social, Economic and Educational Studies Geography, Planning and Development 1 works
- 3 Hate Speech and Cyberbullying Detection Artificial Intelligence 0 works
- 4 Modular Robots and Swarm Intelligence Mechanical Engineering 0 works
- 5 Reinforcement Learning in Robotics Artificial Intelligence 0 works
- 6 Topic Modeling Artificial Intelligence 0 works
- 7 Social Media and Politics Communication 0 works
- 8 Digital Games and Media Sociology and Political Science 0 works
- 9 Artificial Intelligence in Games Artificial Intelligence 0 works
- 10 Logic, Reasoning, and Knowledge Artificial Intelligence 0 works
How open and international is its research?
Against the world's own shares: the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.
World: 40% of research is openly available.
World: 18% is written across borders.
How has Smart Information Flow Technologies (United States)'s research output changed?
Output in 2022-2025 was 23% lower than in 2018-2021.
The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.
Its share of all research
Growing output can still be a shrinking share: all of science grows. This is Smart Information Flow Technologies (United States) as a percentage of every work published that year, 0.00012% in 2024.
Fractional works of Smart Information Flow Technologies (United States) over all fractional works that year. How the balance of science has shifted.
Other research institutions in Minneapolis
- University of Minnesota
- University of Minnesota System
- University of Minnesota Medical Center
- Walden University
- Augsburg University
- Allina Health
- Minneapolis Institute of Arts
- HealthPartners
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
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