World's Best Scientists 2026 revealed!
CAD Computer Aided Design
H-index 19

CAD Computer Aided Design

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 420 49 82 14
Engineering and Technology 818 21 30 10

Additional Metrics

Number of Best Scientists*: 103
Documents by Best Scientists*: 151
Top 100 Ranked Scientists*: 2
SCIMAGO H-index: 133
SCIMAGO SJR: 0.766
Impact Factor: 3.1

Overview

Top Research Topics at Computer-aided Design?

The journal mainly tackles studies in Computer Aided Design, Algorithm, Engineering drawing, Geometry and CAD. Artificial intelligence and Machining are some topics wherein Computer Aided Design research discussed in it have an impact. Most of the works presented in it deals with Artificial intelligence but it intersects with the subject of Pattern recognition.

Research in Machining discussed is concerned with the study of Mechanical engineering as a whole. The Algorithm study featured in Computer-aided Design draws parallels with the field of Mathematical optimization. Geometry works presented in Computer-aided Design have a specific focus on Surface (mathematics).

  • Computer Aided Design (15.97%)
  • Algorithm (15.70%)
  • Engineering drawing (14.94%)

What are the most cited papers published in the journal?

  • Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems (2177 citations)
  • Recursively generated B-spline surfaces on arbitrary topological meshes (1744 citations)
  • The status, challenges, and future of additive manufacturing in engineering (1129 citations)

Research areas of the most cited articles at Computer-aided Design:

The journal papers focus largely on the fields of Computer Aided Design, Algorithm, Engineering drawing, Geometry and Machining. Issues in Computer Aided Design were discussed in the journal publications, taking into consideration concepts from other disciplines like Feature recognition and Computational geometry, Artificial intelligence. The most cited articles address concerns in the field of Engineering drawing by exploring it in line with topics in Process (engineering) which intersect with Systems engineering subjects.

What topics the last edition of the journal is best known for?

  • Artificial intelligence
  • Mechanical engineering
  • Operating system

The previous edition focused in particular on these issues:

The journal facilitates discussions on Point (geometry), Point cloud, Smoothness, Interpolation and Normal estimation. The field of Geometry is the anchor for the Point (geometry) studies presented in it. The research on Point cloud featured in it combines topics in other fields like Normal, Outlier, Estimator, Ground truth and Robustness (computer science).

Topics in Smoothness explored in it were investigated in conjunction with research in Scale (ratio), Phase (waves), Volume element and Volume (compression). In the journal, Minimal surface, Controllability, Function representation, Representation (mathematics) and Heat equation are investigated in conjunction with one another to address concerns in Interpolation research. Normal estimation is at the core of Artificial intelligence and Computer vision studies presented in it.

The most cited articles from the last journal are:

  • Fast and Accurate Normal Estimation for Point Clouds Via Patch Stitching (0 citations)
  • Efficient Representation and Optimization of TPMS-Based Porous Structures for 3D Heat Dissipation (0 citations)
  • A Shape Optimisation with the Isogeometric Boundary Element Method and Adjoint Variable Method for the Three-Dimensional Helmholtz Equation (0 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Computer-aided Design (based on the number of publications) are:

  • Gershon Elber (49 papers) absent at the last edition,
  • Charlie C. L. Wang (39 papers) absent at the last edition,
  • Kai Tang (38 papers) absent at the last edition,
  • Les A. Piegl (29 papers) absent at the last edition,
  • Jarek Rossignac (29 papers) published 1 paper at the last edition the same number as at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Computer-aided Design (based on the number of publications) are:

  • Zhejiang University (101 papers) absent at the last edition,
  • Purdue University (78 papers) absent at the last edition,
  • KAIST (69 papers) absent at the last edition,
  • University of Hong Kong (69 papers) absent at the last edition,
  • Technion – Israel Institute of Technology (69 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2022 edition, 25.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 33.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 50.00% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in Computer-Aided Design

Computer-aided design (CAD) offers a wide array of career possibilities for individuals interested in advanced technologies, artificial intelligence, mechanical engineering, and particularly mathematics. From industrial design to engineering, CAD professionals are in demand across diverse sectors.

One such career path is becoming a teacher, especially in topics that intersect with CAD such as mathematics. Teaching offers the opportunity to influence the next generation of CAD specialists. For example, aspiring educators in California can find comprehensive information on how to become a middle school math teacher in California on our dedicated web page. This page provides insights on the steps to follow, required qualifications, and potential career prospects.

Apart from education, CAD professionals can work in a variety of fields such as Product Development Engineer, CAD Designer, CAD Manager, and so on. Jobs in CAD offer competitive salaries and a chance to work on pioneering technology projects. Additionally, they offer the chance to be part of a fast-paced, ever-evolving industry that has a direct impact on everything from consumer goods to aerospace technology.

Whichever path you choose, a career in the CAD sector promises to be rewarding and exciting, heavily influenced by technological progress and offering numerous opportunities for growth and development.

Top Publications

  • Anisotropic design and optimization of conformal gradient lattice structures

    Dawei Li;Wenhe Liao;Ning Dai;Yi Min Xie

    (2020)
    99 Citations
  • Efficient Representation and Optimization of TPMS-Based Porous Structures for 3D Heat Dissipation

    Shengfa Wang;Yu Jiang;Jiangbei Hu;Xin Fan

    (2022)
    84 Citations
  • Material characterization and precise finite element analysis of fiber reinforced thermoplastic composites for 4D printing

    Yuxuan Yu;Haolin Liu;Kuanren Qian;Humphrey Yang

    (2020)
    72 Citations
  • A Kernel Correlation-Based Approach to Adaptively Acquire Local Features for Learning 3D Point Clouds

    (2022)
    55 Citations
  • Normal Estimation for 3D Point Clouds via Local Plane Constraint and Multi-scale Selection

    (2020)
    46 Citations
  • A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling

    Tim Kuipers;Eugeni L. Doubrovski;Jun Wu;Charlie C.L. Wang

    (2020)
    38 Citations
  • 3D Shape Segmentation Using Soft Density Peak Clustering and Semi-Supervised Learning

    (2021)
    29 Citations
  • NURBS-Diff: A Differentiable Programming Module for NURBS

    (2021)
    27 Citations
  • Geometry Guided Deep Surface Normal Estimation

    Jie Zhang;Jun-Jie Cao;Hai-Rui Zhu;Dong-Ming Yan

    (2022)
    26 Citations
  • Shape-Morphing Mechanical Metamaterials

    Caigui Jiang;Florian Rist;Hui Wang;Johannes Wallner

    (2022)
    26 Citations

Related Online Degrees & Career Pathways

For those considering further education in Computer Science, exploring related online degrees can open up diverse career opportunities. Many students prioritize programs that balance quality with manageable workloads, which is why discovering the easy masters degrees can be a strategic choice for advancing skills without overwhelming stress.

Cost is another key consideration. Fortunately, there are affordable online doctoral programs that offer advanced academic pathways without burdening students with excessive debt. Additionally, many reputable online schools that accept fafsa provide financial aid options, making education accessible to a broader range of learners.

Beyond traditional degrees, online certifications can often lead to well-paying roles in tech. Identifying the job certifications online that align with industry demand is an efficient way to enhance employability and career growth.

By considering these options—affordability, ease, and targeted skill certification—students can tailor their educational journey to fit their goals and lifestyle in the competitive field of Computer Science.

Best Scientists Contributing to This Journal

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