Janis Terpenny

3.1k citations

116 papers · 2.3k indexed · 2 hit papers · h-index 25

Mechanical Engineering top 2%
Industrial and Manufacturing Engineering top 0.5%
Control and Systems Engineering top 2%
Management of Technology and Innovation top 1%
Electrical and Electronic Engineering

Co-authors: Dazhong Wu Robert X. Gao Connor Jennings Soundar Kumara Yupeng Wei Xiaomeng Chang Thomas R. KurfessLi Zhang
Topics: Design Education and Practice (27 papers)Product Development and Customization (25 papers)Manufacturing Process and Optimization (24 papers)
Cited by: Industrial and Manufacturing Engineering Management of Technology and Innovation Medical Laboratory Technology
Journals: Sensors AIAA Journal Mechanical Systems and Signal Processing
Partner nations: United States United Kingdom Denmark

In The Last Decade

Janis Terpenny

104 papers receiving 2.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

2017 487 citations Dazhong Wu, Connor Jennings et al. profile →
A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing

2017 222 citations Dazhong Wu, Janis Terpenny et al. Journal of Manufacturing Systems profile →

Peers

Countries citing papers authored by Janis Terpenny

Since Specialization

Citations

This map shows the geographic impact of Janis Terpenny's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Janis Terpenny with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janis Terpenny more than expected).

Fields of papers citing papers by Janis Terpenny

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Janis Terpenny. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Janis Terpenny. The network helps show where Janis Terpenny may publish in the future.

Co-authorship network of co-authors of Janis Terpenny

This figure shows the co-authorship network connecting the top 25 collaborators of Janis Terpenny. A scholar is included among the top collaborators of Janis Terpenny based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Janis Terpenny. Janis Terpenny is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Remaining useful life prediction using graph convolutional attention networks with temporal convolution-aware nested residual connections 2023 ·Reliability Engineering & System Safety ·Yupeng Wei,Dazhong Wu,Janis Terpenny	26
2	Leveraging Active Learning for Failure Mode Acquisition 2023 ·Sensors ·(unknown),Janis Terpenny,Vittaldas V. Prabhu	4
3	Bearing remaining useful life prediction using self-adaptive graph convolutional networks with self-attention mechanism 2022 ·Mechanical Systems and Signal Processing ·Yupeng Wei,Dazhong Wu,Janis Terpenny	99
4	Robust Incipient Fault Detection of Complex Systems Using Data Fusion 2020 ·IEEE Transactions on Instrumentation and Measurement ·Yupeng Wei,Dazhong Wu,Janis Terpenny	46
5	Utilizing The Internet To Improve Student Learning In A First Course In Engineering Economy With Real World Unsolved Problems In Collaboration With Industry 2020 ·William G. Sullivan,(unknown),(unknown),Janis Terpenny	4
6	Bridging Theory And Practice In A Senior Level Robotics Course For Mechanical And Electrical Engineers 2020 ·Papers on Engineering Education Repository (American Society for Engineering Education) ·Ping Ren,Janis Terpenny,Dennis Hong,(unknown)	2
7	Surface Roughness Prediction in Additive Manufacturing Using Machine Learning 2018 ·Journal of International Crisis and Risk Communication Research ·Dazhong Wu,Yupeng Wei,Janis Terpenny	34
8	Cloud-based machine learning for predictive analytics: Tool wear prediction in milling 2016 ·Dazhong Wu,Connor Jennings,Janis Terpenny,Soundar Kumara	55
9	A Computational Framework for Cloud-based Machine Prognosis 2016 ·Procedia CIRP ·Peng Wang,Robert X. Gao,Dazhong Wu,Janis Terpenny	11
10	Democratizing digital design and manufacturing using high performance cloud computing: Performance evaluation and benchmarking 2016 ·Journal of Manufacturing Systems ·Dazhong Wu,Xi Liu,(unknown),Wolfgang Gentzsch,Janis Terpenny	29
11	Forecasting Obsolescence Risk Using Machine Learning 2016 ·Connor Jennings,Dazhong Wu,Janis Terpenny	6
12	Haptic perception of users with low vision and their needs in haptic-incorporated user interfaces 2013 ·Disability and Rehabilitation Assistive Technology ·Hyung Nam Kim,Tonya L. Smith‐Jackson,Janis Terpenny	1
13	Engineering Design Education - Core Competencies 2012 ·50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition ·(unknown),Janis Terpenny	10
14	Modeling Constraints in Design Refresh Planning 2011 ·(unknown),Peter Sandborn,Janis Terpenny,(unknown)	3
15	Ontology-based data integration and decision support for product e-Design 2009 ·Robotics and Computer-Integrated Manufacturing ·Xiaomeng Chang,Janis Terpenny	22
16	Cooperative body–brain coevolutionary synthesis of mechatronic systems 2008 ·Artificial intelligence for engineering design analysis and manufacturing ·Jiachuan Wang,Zhun Fan,Janis Terpenny,Erik D. Goodman	10
17	Principles for Managing Technological Product Obsolescence 2007 ·Guidelines for a Decision Support Method Adapted to NPD Processes ·(unknown),Janis Terpenny	1
18	Design for adaptability (DFAD)—a new concept for achieving sustainable design 2007 ·Robotics and Computer-Integrated Manufacturing ·Mary Kasarda,Janis Terpenny,Dan Inman,(unknown),John G. Jelesko,Aslı Şahin,Jaeil Park	59
19	Learning and Adapting Fuzzy Set-Based Trade-off Strategy in Engineering Design Synthesis 2003 ·Jiachuan Wang,Janis Terpenny	2
20	Design, layout, and tools for effective Web-based instruction 2003 ·(unknown),Janis Terpenny,William G. Sullivan	1

About Janis Terpenny

Janis Terpenny is a scholar working on Architecture, Management of Technology and Innovation and Industrial and Manufacturing Engineering, having authored 116 papers that have together received 2.3k indexed citations. Recurring topics across this work include Design Education and Practice (27 papers), Product Development and Customization (25 papers) and Manufacturing Process and Optimization (24 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (785 citations), Management of Technology and Innovation (334 citations) and Medical Laboratory Technology (67 citations). Janis Terpenny has collaborated with scholars based in United States, United Kingdom and Denmark. Frequent co-authors include Dazhong Wu, Robert X. Gao, Connor Jennings, Soundar Kumara, Yupeng Wei, Yupeng Wei, Xiaomeng Chang, Thomas R. Kurfess, Li Zhang and Shaopeng Liu. Their work appears in journals such as Sensors, AIAA Journal and Mechanical Systems and Signal Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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