Portfolio item number 1
Short description of portfolio item number 1
Posts by Collection
portfolio
Portfolio item number 2
Short description of portfolio item number 2
publications
Curve shapes: Comparison and alignment
Published in submitted to TPAMI, 2004
Use Google Scholar for full citation
Recommended citation: John Femiani, Anshuman Razdan, Gerald Farin, "Curve shapes: Comparison and alignment." submitted to TPAMI, 2004.
A System for Discriminating Handwriting from Machine Print on Noisy Arabic Documents
Published in In the proceedings of Proceedings 2005 Symposium on Document Image Understanding Technology, 2005
Use Google Scholar for full citation
Recommended citation: John Femiani$^1$, Mariano Razdan, "A System for Discriminating Handwriting from Machine Print on Noisy Arabic Documents." In the proceedings of Proceedings 2005 Symposium on Document Image Understanding Technology, 2005.
3D face authentication and recognition based on bilateral symmetry analysis
Published in The Visual Computer, 2006
Use Google Scholar for full citation
Recommended citation: Liyan Zhang, Anshuman Razdan, Gerald Farin, John Femiani, Myungsoo Bae, Charles Lockwood, "3D face authentication and recognition based on bilateral symmetry analysis." The Visual Computer, 2006.
Quadric-based metrics for shape analysis of three-dimensional osteological surfaces
Published in Am J Phys Anthropol, 2006
Use Google Scholar for full citation
Recommended citation: Matthew Tocheri, John Femiani, Caley Orr, Mary Marzke, "Quadric-based metrics for shape analysis of three-dimensional osteological surfaces." Am J Phys Anthropol, 2006.
Fourier shape descriptors of pixel footprints for road extraction from satellite images
Published in In the proceedings of 2007 IEEE International Conference on Image Processing, 2007
Use Google Scholar for full citation
Recommended citation: Jiuxiang Hu, Anshuman Razdan, John Femiani, Peter Wonka, Ming Cui, "Fourier shape descriptors of pixel footprints for road extraction from satellite images." In the proceedings of 2007 IEEE International Conference on Image Processing, 2007.
Road network extraction and intersection detection from aerial images by tracking road footprints
Published in IEEE Transactions on Geoscience and Remote Sensing, 2007
Use Google Scholar for full citation
Recommended citation: Jiuxiang Hu, Anshuman Razdan, John Femiani, Ming Cui, Peter Wonka, "Road network extraction and intersection detection from aerial images by tracking road footprints." IEEE Transactions on Geoscience and Remote Sensing, 2007.
Urban road network extraction and intersection detection in aerial images using local shape classification
Published in IEEE T. on Remote Sensing and GeoSciences, 2007
Use Google Scholar for full citation
Recommended citation: J Hu, A Razdan, P Wonka, M Cui, J Femiani, "Urban road network extraction and intersection detection in aerial images using local shape classification." IEEE T. on Remote Sensing and GeoSciences, 2007.
3D VQI: 3D visual query interface
Published in In the proceedings of 2009 Sixth International Conference on Information Technology: New Generations, 2009
Use Google Scholar for full citation
Recommended citation: Subhash Uppalapati, John Femiani, Anshuman Razdan, Kevin Gary, "3D VQI: 3D visual query interface." In the proceedings of 2009 Sixth International Conference on Information Technology: New Generations, 2009.
Curve matching for open 2D curves
Published in Pattern Recognition Letters, 2009
Use Google Scholar for full citation
Recommended citation: Ming Cui, John Femiani, Jiuxiang Hu, Peter Wonka, Anshuman Razdan, "Curve matching for open 2D curves." Pattern Recognition Letters, 2009.
Interval HSV: Extracting ink annotations
Published in In the proceedings of 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009
Use Google Scholar for full citation
Recommended citation: John Femiani, Anshuman Razdan, "Interval HSV: Extracting ink annotations." In the proceedings of 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
Comparative 3D quantitative analyses of trapeziometacarpal joint surface curvatures among living catarrhines and fossil hominins
Published in American Journal of Physical Anthropology: The Official Publication of the American Association of Physical Anthropologists, 2010
Use Google Scholar for full citation
Recommended citation: Mary Marzke, Matthew Tocheri, B Steinberg, JD Femiani, SP Reece, RL Linscheid, Caley Orr, RF Marzke, "Comparative 3D quantitative analyses of trapeziometacarpal joint surface curvatures among living catarrhines and fossil hominins." American Journal of Physical Anthropology: The Official Publication of the American Association of Physical Anthropologists, 2010.
Least Eccentric Curves
Published in Computer Aided Geometric Design, 2010
Use Google Scholar for full citation
Recommended citation: John Femiani, Chia Chen, Anshuman Razdan, "Least Eccentric Curves." Computer Aided Geometric Design, 2010.
Semi-Automatic Hole Filling Guided by Hermite Curves
Published in Computer Aided Design, 2010
Use Google Scholar for full citation
Recommended citation: Myungsoo Bae, John Femiani, A Razdan, "Semi-Automatic Hole Filling Guided by Hermite Curves." Computer Aided Design, 2010.
Comparative and analytic apparatus method for converting two-dimensional bit map data into three-dimensional data
Published in US Patent 7,729,541, 2010
US Patent 7,729,541
Recommended citation: Anshuman Razdan, John Femiani, "Comparative and analytic apparatus method for converting two-dimensional bit map data into three-dimensional data." US Patent 7,729,541, 2010.
A new qem for parametrization of raster images
Published in In the proceedings of Computer Graphics Forum, 2011
Use Google Scholar for full citation
Recommended citation: Xuetao Yin, John Femiani, Peter Wonka, Anshuman Razdan, "A new qem for parametrization of raster images." In the proceedings of Computer Graphics Forum, 2011.
Ecological divergence and medial cuneiform morphology in gorillas
Published in Journal of Human Evolution, 2011
Use Google Scholar for full citation
Recommended citation: Matthew Tocheri, Christyna Solhan, Caley Orr, John Femiani, Bruno Frohlich, Colin Groves, William Harcourt-Smith, Brian Richmond, Brett Shoelson, William Jungers, "Ecological divergence and medial cuneiform morphology in gorillas." Journal of Human Evolution, 2011.
Least eccentric ellipses for geometric Hermite interpolation
Published in Computer aided geometric design, 2012
Use Google Scholar for full citation
Recommended citation: John Femiani, Chia-Yuan Chuang, Anshuman Razdan, "Least eccentric ellipses for geometric Hermite interpolation." Computer aided geometric design, 2012.
Methods for approximating Loop subdivision using tessellation enabled GPUs
Published in In the proceedings of Advances in Visual Computing: 8th International Symposium, ISVC 2012, Rethymnon, Crete, Greece, July 16-18, 2012, Revised Selected Papers, Part I 8, 2012
Use Google Scholar for full citation
Recommended citation: Ashish Amresh, John Femiani, Christoph F{\"u}nfzig, "Methods for approximating Loop subdivision using tessellation enabled GPUs." In the proceedings of Advances in Visual Computing: 8th International Symposium, ISVC 2012, Rethymnon, Crete, Greece, July 16-18, 2012, Revised Selected Papers, Part I 8, 2012.
Three-dimensional quantitative comparative analysis of trapezial-metacarpal joint surface curvatures in human populations
Published in Journal of Hand Surgery, 2012
Use Google Scholar for full citation
Recommended citation: MW Marzke, MW Tocheri, RF Marzke, JD Femiani, "Three-dimensional quantitative comparative analysis of trapezial-metacarpal joint surface curvatures in human populations." Journal of Hand Surgery, 2012.
Topology Free Automated Landmark Detection
Published in In the proceedings of Advances in Applied Human Modeling and Simulation, 2012
Use Google Scholar for full citation
Recommended citation: Chiayuan Chuang, John Femiani, Brian Corner, "Topology Free Automated Landmark Detection." In the proceedings of Advances in Applied Human Modeling and Simulation, 2012.
Evaluating the effectiveness of flipped classrooms for teaching CS1
Published in In the proceedings of 2013 IEEE Frontiers in Education Conference (FIE), 2013
Use Google Scholar for full citation
Recommended citation: Ashish Amresh, Adam Carberry, John Femiani, "Evaluating the effectiveness of flipped classrooms for teaching CS1." In the proceedings of 2013 IEEE Frontiers in Education Conference (FIE), 2013.
Functional morphology of the primate hallucal metatarsal (Mt1) and implications for inferring hallucal grasping capability in fossil primates.
Published in In the proceedings of AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, 2013
Use Google Scholar for full citation
Recommended citation: Katherine Goodenberger, Caley Orr, Doug Boyer, Rachel Jacobs, John Femiani, Biren Patel, "Functional morphology of the primate hallucal metatarsal (Mt1) and implications for inferring hallucal grasping capability in fossil primates.." In the proceedings of AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, 2013.
Improving E-Learning Videos Using Personalization and Social Signals
Published in In the proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 2013
Use Google Scholar for full citation
Recommended citation: Adit Shah, Ashish Amresh, John Femiani, "Improving E-Learning Videos Using Personalization and Social Signals." In the proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 2013.
UAV sensor operator training enhancement through heat map analysis
Published in In the proceedings of 2013 17th International Conference on Information Visualisation, 2013
Use Google Scholar for full citation
Recommended citation: Ashish Amresh, John Femiani, Jason Fairfield, Adam Fairfield, "UAV sensor operator training enhancement through heat map analysis." In the proceedings of 2013 17th International Conference on Information Visualisation, 2013.
A hybrid method for multi-sensor remote sensing image registration based on salience region
Published in Circuits, Systems, and Signal Processing, 2014
Use Google Scholar for full citation
Recommended citation: Jichao Jiao, Zhongliang Deng, Baojun Zhao, John Femiani, Xin Wang, "A hybrid method for multi-sensor remote sensing image registration based on salience region." Circuits, Systems, and Signal Processing, 2014.
Shadow-based rooftop segmentation in visible band images
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014
Use Google Scholar for full citation
Recommended citation: John Femiani, Er Li, Anshuman Razdan, Peter Wonka, "Shadow-based rooftop segmentation in visible band images." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014.
Methods and System for Monitoring Computer Users
Published in US Patent App. 13/762,306, 2014
US Patent App. 13/762,306
Recommended citation: Anshuman Razden, John Femiani, "Methods and System for Monitoring Computer Users." US Patent App. 13/762,306, 2014.
Functional morphology of the hallucal metatarsal with implications for inferring grasping ability in extinct primates
Published in American journal of physical anthropology, 2015
Use Google Scholar for full citation
Recommended citation: Katherine Goodenberger, Doug Boyer, Caley Orr, Rachel Jacobs, John Femiani, Biren Patel, "Functional morphology of the hallucal metatarsal with implications for inferring grasping ability in extinct primates." American journal of physical anthropology, 2015.
Robust rooftop extraction from visible band images using higher order CRF
Published in IEEE Transactions on Geoscience and Remote Sensing, 2015
Use Google Scholar for full citation
Recommended citation: Er Li, John Femiani, Shibiao Xu, Xiaopeng Zhang, Peter Wonka, "Robust rooftop extraction from visible band images using higher order CRF." IEEE Transactions on Geoscience and Remote Sensing, 2015.
The Role of Certainty and Time Delay in Students' Cheating Decisions during Online Testing.
Published in In the proceedings of CogSci, 2015
Use Google Scholar for full citation
Recommended citation: Chia-Yuan Chuang, Scotty Craig, John Femiani, "The Role of Certainty and Time Delay in Students' Cheating Decisions during Online Testing.." In the proceedings of CogSci, 2015.
An adaptive time reduction technique for video lectures
Published in In the proceedings of 12th International Conference on e-Learning, ICEL 2017, 2017
Use Google Scholar for full citation
Recommended citation: Sreenivas Shenoy, Ashish Amresh, John Femiani, "An adaptive time reduction technique for video lectures." In the proceedings of 12th International Conference on e-Learning, ICEL 2017, 2017.
BigSUR: Large-scale structured urban reconstruction
Published in ACM Transactions on Graphics, 2017
Use Google Scholar for full citation
Recommended citation: Tom Kelly, John Femiani, Peter Wonka, Niloy Mitra, "BigSUR: Large-scale structured urban reconstruction." ACM Transactions on Graphics, 2017.
Detecting probable cheating during online assessments based on time delay and head pose
Published in Higher Education Research & Development, 2017
Use Google Scholar for full citation
Recommended citation: Chia Chuang, Scotty Craig, John Femiani, "Detecting probable cheating during online assessments based on time delay and head pose." Higher Education Research & Development, 2017.
Automatic Sign Detection with Application to an Assistive Robot.
Published in In the proceedings of AAAI Workshops, 2018
Use Google Scholar for full citation
Recommended citation: Amlaan Shakeel, Peining Che, Xien Liu, Yamuna Rajesekhar, John Femiani, "Automatic Sign Detection with Application to an Assistive Robot.." In the proceedings of AAAI Workshops, 2018.
Facade segmentation in the wild
Published in arXiv preprint arXiv:1805.08634, 2018
Use Google Scholar for full citation
Recommended citation: John Femiani, Wamiq Para, Niloy Mitra, Peter Wonka, "Facade segmentation in the wild." arXiv preprint arXiv:1805.08634, 2018.
Fine scale registration of walking paths and other ribbon-like features
Published in In the proceedings of Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018
Use Google Scholar for full citation
Recommended citation: Zhongyu Liu, Xian Liu, John Femiani, "Fine scale registration of walking paths and other ribbon-like features." In the proceedings of Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018.
Shortcut to Adiabaticity for Harmonic and Anharmonic Traps using BFGS Algorithm
Published in Bulletin of the American Physical Society, 2018
Use Google Scholar for full citation
Recommended citation: Hok Chang, John Femiani, Edward Samson, "Shortcut to Adiabaticity for Harmonic and Anharmonic Traps using BFGS Algorithm." Bulletin of the American Physical Society, 2018.
Post capture imagery processing and deployment systems
Published in US Patent 10,121,223, 2018
US Patent 10,121,223
Recommended citation: Dennis Vegh, John Femiani, Michael Katic, Anshuman Razdan, "Post capture imagery processing and deployment systems." US Patent 10,121,223, 2018.
User interaction event data capturing system for use with aerial spherical imagery
Published in US Patent 10,120,878, 2018
US Patent 10,120,878
Recommended citation: Dennis Vegh, John Femiani, Michael Katic, Anshuman Razdan, "User interaction event data capturing system for use with aerial spherical imagery." US Patent 10,120,878, 2018.
Segmentation of Color-Coded Underground Utility Markings
Published in In the proceedings of Science and Information Conference, 2019
Use Google Scholar for full citation
Recommended citation: Peining Che, John Femiani, "Segmentation of Color-Coded Underground Utility Markings." In the proceedings of Science and Information Conference, 2019.
Trajectory Simulation and Optimization for Shortcuts to Adiabaticity using Artificial Neural Network
Published in Bulletin of the American Physical Society, 2019
Use Google Scholar for full citation
Recommended citation: Hok Chang, John Femiani, E Samson, "Trajectory Simulation and Optimization for Shortcuts to Adiabaticity using Artificial Neural Network." Bulletin of the American Physical Society, 2019.
Post capture imagery processing and deployment systems
Published in US Patent 10,467,726, 2019
US Patent 10,467,726
Recommended citation: Dennis Vegh, John Femiani, Michael Katic, Anshuman Razdan, "Post capture imagery processing and deployment systems." US Patent 10,467,726, 2019.
Improved stylegan embedding: Where are the good latents?
Published in arXiv preprint arXiv:2012.09036, 2020
Use Google Scholar for full citation
Recommended citation: Peihao Zhu, Rameen Abdal, Yipeng Qin, John Femiani, Peter Wonka, "Improved stylegan embedding: Where are the good latents?." arXiv preprint arXiv:2012.09036, 2020.
Large-Scale Architectural Asset Extraction from Panoramic Imagery
Published in IEEE Transactions on Visualization and Computer Graphics, 2020
Use Google Scholar for full citation
Recommended citation: Peihao Zhu, Wamiq Para, Anna Fr{\"u}hst{\"u}ck, John Femiani, Peter Wonka, "Large-Scale Architectural Asset Extraction from Panoramic Imagery." IEEE Transactions on Visualization and Computer Graphics, 2020.
Barbershop: Gan-based image compositing using segmentation masks
Published in arXiv preprint arXiv:2106.01505, 2021
Use Google Scholar for full citation
Recommended citation: Peihao Zhu, Rameen Abdal, John Femiani, Peter Wonka, "Barbershop: Gan-based image compositing using segmentation masks." arXiv preprint arXiv:2106.01505, 2021.
Mind the gap: Domain gap control for single shot domain adaptation for generative adversarial networks
Published in arXiv preprint arXiv:2110.08398, 2021
Use Google Scholar for full citation
Recommended citation: Peihao Zhu, Rameen Abdal, John Femiani, Peter Wonka, "Mind the gap: Domain gap control for single shot domain adaptation for generative adversarial networks." arXiv preprint arXiv:2110.08398, 2021.
Clip2stylegan: Unsupervised extraction of stylegan edit directions
Published in In the proceedings of ACM SIGGRAPH 2022 conference proceedings, 2022
Use Google Scholar for full citation
Recommended citation: Rameen Abdal, Peihao Zhu, John Femiani, Niloy Mitra, Peter Wonka, "Clip2stylegan: Unsupervised extraction of stylegan edit directions." In the proceedings of ACM SIGGRAPH 2022 conference proceedings, 2022.
Hairnet: Hairstyle transfer with pose changes
Published in In the proceedings of European Conference on Computer Vision, 2022
Use Google Scholar for full citation
Recommended citation: Peihao Zhu, Rameen Abdal, John Femiani, Peter Wonka, "Hairnet: Hairstyle transfer with pose changes." In the proceedings of European Conference on Computer Vision, 2022.
SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation
Published in International Conference on Machine Learning (ICML), 2025
SketchDNN is a generative model for synthesizing CAD sketches that jointly models both continuous parameters and discrete class labels through a unified continuous-discrete diffusion process. The core innovation is Gaussian-Softmax diffusion, where logits perturbed with Gaussian noise are projected onto the probability simplex via a softmax transformation, facilitating blended class modeling for high-fidelity CAD sketch generation.
Recommended citation: Sathvik Chereddy, John Femiani, "SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation." International Conference on Machine Learning (ICML), 2025.
resources
GPU Node 50 Access and Configuration Guide
Published:
GPU Node Access and Configuration Guide
talks
Barbershop: GAN-based Image Compositing using Segmentation Masks Permalink
Published:
Watch out for my COVID beard look! This talk presents Barbershop, a GAN-based image compositing system that uses segmentation masks for highly realistic and controllable image generation. The focus is on applying deep learning to image editing tasks.
teaching
CSE464/564: Algorithms
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2016
This course covers the design and analysis of algorithms, including topics such as dynamic programming, graph algorithms, and NP-completeness. Graduate students are expected to explore advanced topics in approximation algorithms and randomized algorithms.
CSE464/564: Algorithms
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2017
This course covers the design and analysis of algorithms, including topics such as dynamic programming, graph algorithms, and NP-completeness. Graduate students are expected to explore advanced topics in approximation algorithms and randomized algorithms.
CSE466/566: Computer Graphics
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2017
This course introduces students to the principles of computer graphics, including rasterization, ray tracing, 3D transformations, and shading techniques. Both undergraduate and graduate students are exposed to the mathematics and programming involved in rendering 3D scenes and developing computer graphics applications.
CSE464/564: Algorithms
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2017
This course focuses on the analysis and design of algorithms, with cross-listed sections for both undergraduate (CSE464) and graduate students (CSE564). The curriculum covers foundational topics such as dynamic programming, graph algorithms, and NP-completeness, along with an introduction to approximation algorithms.
CSE310D: Preparing for Tech Interviews
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2017
This course is designed to prepare students for technical interviews in the software industry. It covers a wide range of topics, including algorithms, data structures, and problem-solving techniques commonly used in technical interviews.
CSE664: Advanced Algorithms
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2018
This graduate course explores advanced topics in algorithms, with an emphasis on NP-hard problems, approximation algorithms, and advanced techniques for solving optimization problems. Students will focus on proving algorithm correctness and analyzing their complexity. Topics include probabilistic methods, approximation algorithms, and advanced graph algorithms.
CSE310D: Preparing for Tech Interviews
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2018
This course is designed to prepare students for technical interviews in the software industry. It covers a wide range of topics, including algorithms, data structures, and problem-solving techniques commonly used in technical interviews.
CSE464/564: Algorithms
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2018
This course focuses on the analysis and design of algorithms, with cross-listed sections for both undergraduate (CSE464) and graduate students (CSE564). The curriculum covers foundational topics such as dynamic programming, graph algorithms, and NP-completeness, along with an introduction to approximation algorithms.
CSE627: Advanced Machine Learning
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2018
This graduate-level course offers an in-depth theoretical exploration of machine learning, with a focus on both classical and modern techniques. Grounded in Bishop’s Pattern Recognition and Machine Learning (PRML), this course delves into the probabilistic and mathematical foundations of machine learning, making it distinct from the undergraduate applied courses.
CSE488/588: Computer Vision
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2018
This course introduces students to the fundamental techniques in computer vision, including image processing, feature detection, object recognition, and machine learning-based approaches for visual data analysis.
CSE664: Advanced Algorithms
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This graduate course explores advanced topics in algorithms, with an emphasis on NP-hard problems, approximation algorithms, and advanced techniques for solving optimization problems. Students will focus on proving algorithm correctness and analyzing their complexity. Topics include probabilistic methods, approximation algorithms, and advanced graph algorithms.
CSE310D: Preparing for Tech Interviews
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This course is designed to prepare students for technical interviews in the software industry. It covers a wide range of topics, including algorithms, data structures, and problem-solving techniques commonly used in technical interviews.
CSE488/588: Computer Vision
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This course introduces students to the fundamental techniques in computer vision, including image processing, feature detection, object recognition, and machine learning-based approaches for visual data analysis.
CSE627: Advanced Machine Learning
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This graduate-level course offers an in-depth theoretical exploration of machine learning, with a focus on both classical and modern techniques. Grounded in Bishop’s Pattern Recognition and Machine Learning (PRML), this course delves into the probabilistic and mathematical foundations of machine learning, making it distinct from the undergraduate applied courses.
CSE464/564: Algorithms
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This course focuses on the analysis and design of algorithms, with cross-listed sections for both undergraduate (CSE464) and graduate students (CSE564). The curriculum covers foundational topics such as dynamic programming, graph algorithms, and NP-completeness, along with an introduction to approximation algorithms.
CSE465/565: Comparative Programming Languages
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This course covers the theory and practice of different programming paradigms and languages. Students explore a variety of programming languages, comparing their design, syntax, semantics, and implementation.
CSE287: Foundations of Graphics
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2019
This course introduces students to the basics of computer graphics, including rendering techniques, 3D transformations, and graphical algorithms. The emphasis is on understanding the mathematical foundations and practical implementation of graphics pipelines.
CSE664: Advanced Algorithms
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2020
This graduate course explores advanced topics in algorithms, with an emphasis on NP-hard problems, approximation algorithms, and advanced techniques for solving optimization problems. Students will focus on proving algorithm correctness and analyzing their complexity. Topics include probabilistic methods, approximation algorithms, and advanced graph algorithms.
CSE627: Advanced Machine Learning
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2020
This graduate-level course offers an in-depth theoretical exploration of machine learning, with a focus on both classical and modern techniques. Grounded in Bishop’s Pattern Recognition and Machine Learning (PRML), this course delves into the probabilistic and mathematical foundations of machine learning, making it distinct from the undergraduate applied courses.
CSE465/565: Comparative Programming Languages
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2020
This course covers the theory and practice of different programming paradigms and languages. Students explore a variety of programming languages, comparing their design, syntax, semantics, and implementation.
CSE620B: Remote Sensing & Computer Vision
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2020
This initial offering of course explores computational methods in remote sensing with a focus on computer vision applications. Topics include image segmentation, classification, feature detection, and the use of large geospatial datasets.
CSE488/588: Computer Vision
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2020
This course introduces students to the fundamental techniques in computer vision, including image processing, feature detection, object recognition, and machine learning-based approaches for visual data analysis.
CSE627: Advanced Machine Learning
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2021
This graduate-level course offers an in-depth theoretical exploration of machine learning, with a focus on both classical and modern techniques. Grounded in Bishop’s Pattern Recognition and Machine Learning (PRML), this course delves into the probabilistic and mathematical foundations of machine learning, making it distinct from the undergraduate applied courses.
CSE664: Advanced Algorithms
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2021
This graduate course explores advanced topics in algorithms, with an emphasis on NP-hard problems, approximation algorithms, and advanced techniques for solving optimization problems. Students will focus on proving algorithm correctness and analyzing their complexity. Topics include probabilistic methods, approximation algorithms, and advanced graph algorithms.
CSE465/565: Comparative Programming Languages
Undergraduate course, Miami University, Department of Computer Science and Software Engineering, 2021
This course covers the theory and practice of different programming paradigms and languages. Students explore a variety of programming languages, comparing their design, syntax, semantics, and implementation.
CSE664: Advanced Algorithms
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2022
This graduate course explores advanced topics in algorithms, with an emphasis on NP-hard problems, approximation algorithms, and advanced techniques for solving optimization problems. Students will focus on proving algorithm correctness and analyzing their complexity. Topics include probabilistic methods, approximation algorithms, and advanced graph algorithms.
CSE434: Generative AI
Undergraduate & Graduate course, Miami University, Department of Computer Science and Software Engineering, 2024
This course introduces the fundamental concepts and techniques of Generative AI, with a focus on language models, neural networks, and creative AI systems. Students will explore state-of-the-art generative models such as GANs, transformers, and VAEs, and learn how to apply these techniques to real-world problems. Emphasis is placed on prompt engineering, model fine-tuning, and evaluation.
CSE620B: Remote Sensing & Computer Vision
Graduate course, Miami University, Department of Computer Science and Software Engineering, 2024
The 2024 version of the course builds on the principles of remote sensing and computer vision, incorporating modern machine learning techniques. Topics include advanced segmentation methods, deep learning for geospatial data, and hyperspectral analysis.