Teaching @ Carnegie Mellon University,
Heinz College
Fall 2018
94-842, Programming in R for Analytics
This course introduces students to R, a widely used statistical programming language, and Shiny – a popular R-based web-application development framework that offers a front-end interface to the statistical prowess of the libraries accessible through R. Students will learn to manipulate data objects, produce graphics, analyze data using common statistical methods, and generate reproducible statistical reports. They will also gain experience in applying these acquired skills in various public policy areas.
By the end of the class, students learn to:
By the end of the class, students learn to:
- Use RStudio, read R documentation, and write R scripts.
- Import, export and manipulate data.
- Produce statistical summaries of continuous and categorical data.
- Produce basic graphics using standard functions, and produce more advanced graphics using the ggplot2 library.
- Perform common hypothesis tests, and run simple regression models in R
- Produce reports of statistical analyses in R Markdown.
Teaching @ Duquesne University
Fall 2017
BMED 444 / 544: Introduction to Biomedical Imaging
Course instructor for Fall 2017 undergraduate course on Introduction to Biomedical Imaging which introduces the fundamental principles of imaging and image processing from major modalities – X-ray, CT, MRI, Ultrasound and optical imaging systems including microscopy – used in clinical medicine and biomedical research. The course is a combination of lectures as well as demonstrations which introduce the fundamentals of acquiring and processing images from a signals & systems standpoint, grounded on mathematical modeling of imaging systems. A strong foundational understanding of imaging techniques will be established through assignments involving simulation of image acquisition processes as well as basic algorithmic image processing for image filtering and de-noising. To this end, course will involve programming-focused assignments (in Matlab).
Fall 2016, 2017
BMED 310: BioSignals and Systems
Course instructor for Fall 2016 and 2017 undergraduate course on BioSignals & Systems, BMED-310, listed in the department of biomedical engineering in Duquesne University, at Pittsburgh, PA. This course is designed to enable students to develop mathematical models for biological systems and for biomedical engineering systems, devices, components, and processes and to use models for data reduction and for system performance analysis, prediction and optimization. Models considered will be drawn from a broad range of applications and will be based on algebraic equations, ordinary differential equations and partial differential equations. The tools of advanced engineering mathematics comprising analytical, computational and statistical approaches will be introduced and used for model manipulation.
Spring 2016, 2017
BMED 110: Intro to Programming for Engineers
Course instructor for Spring 2016 and 2017 undergraduate course on Introduction to Programming for Engineers, BMED-110, listed in the department of biomedical engineering in Duquesne University, at Pittsburgh, PA. This course introduces software tools and scientific programming techniques so that the student may make use of the powerful computing environments now commonly available. The course uses Matlab and R for study of scientific computation. Matlab is used to demonstrate programming methods, as well as to introduce numerical techniques whereas R is utilized as a vehicle to demonstrate rapid prototyping of graphical interfaces and more advanced data analytics functionalities. The course is directed towards scientific programming which is relevant to solving engineering problems, analysis of data, and simulation of physical phenomena. Software design aspects of this course include mastering flow control, conditional statements, input and output, two and three dimensional graphics, and data structures. Students apply these software constructs to solve problems in statistics, imaging, and problems in biomedical engineering during this course.
uLectures and notes are only available on the Duquesne University Blackboard system to enrolled students or upon special request - so contact me if interested!
uLectures and notes are only available on the Duquesne University Blackboard system to enrolled students or upon special request - so contact me if interested!
Teaching @ University of Pittsburgh
Spring 2015, 2016, 2017, 2018
Engineering Medical Devices for Quantitative Image Analysis & Visualization
Course instructor for Spring 2015 and Spring 2016 graduate course on Engineering Medical Devices for Quantitative Image Analysis & Visualization, BIOENG-2385 - listed in the department of bioengineering of the University of Pittsburgh, at Pittsburgh, PA. The goals of this course are to introduce students the fundamentals of medical image formation, image processing, computational geometry, numerical methods for analysis of medical image data and data visualization as they relates to engineering medical devices ready for clinical translation. Additionally, medical device regulations on device safety and efficacy specifically in the context of image post-processing technologies for clinical workflow augmentation are discussed. More about this course including its syllabus, course objectives and texts may be found at the Engineering Medical Devices for Quantitative Image Analysis & Visualization webpage.
Lectures and notes are only available on the University of Pittsburgh CourseWeb Blackboard system to enrolled students or upon special request - so contact me if interested!
Lectures and notes are only available on the University of Pittsburgh CourseWeb Blackboard system to enrolled students or upon special request - so contact me if interested!
Fall 2015, Fall 2018
Biomedical Imaging: Fundamentals of Biomedical Imaging & Image Processing
Course instructor for Fall 2015 and Fall 2018 undergraduate courses titled, Biomedical Imaging (BIOENG-1330 / 2330) and Medical Imaging and Image Analysis (BIOENG-1340/2340), open to graduate student enrollment, listed in the department of Bioengineering of the University of Pittsburgh, at Pittsburgh, PA. BIOENG 1330 was previously instructed by Prof. George Stetten, prior to 2015. The course introduces the fundamental principles of imaging and image processing from major modalities – X-ray, CT, MRI, Ultrasound and Optical Imaging systems – used in clinical medicine and biomedical research. The course is a combination of lectures as well as demonstrations which introduce the fundamentals of acquiring and processing images from a signals & systems standpoint, grounded on mathematical modeling of imaging systems. Therefore, while the emphasis will be on imparting an understanding of physics behind tomographic imaging devices, the course provides students with some intuition in regard to engineering effective image processing pipelines for visualization or analysis of acquired images. More about this course including its syllabus, course objectives and texts may be found at the course webpage. This class includes 51 enrolled undergraduate students from the department of Bioengineering, in University of Pittsburgh. Lectures and notes are only available on the University of Pittsburgh CourseWeb Blackboard system to enrolled students or upon special request.
Teaching @ SYSU - CMU, China
Joint Institute of Engineering
Fall 2014
Biomedical Imaging & Analysis (BIA)
Course instructor for Spring 2014 graduate course on Biomedical Imaging & Analysis (BIA), J1-791 - listed in the electrical & computer engineering department of the Sun Yat-sen University - Carnegie Mellon University Joint Institute of Engineering, at Guangzhou, China. The goals of this course are to familiarize students with biological and medical imaging data from various imaging modalities (eg: Magnetic Resonance Imaging (MRI), X-ray Computed Tomography (CT), Fluoroscopy, Ultrasound and Optical Systems for Microscopy), how these data are acquired as well as how to process 2D, 3D and 4D (3D + time) data for quantification and visualization purposes using contemporary software tools and open-source libraries (including, SimpleITK, ITK, VTK). Additionally, this course integrates these image-processing concepts their real-world applications from the fields of mechanical and biomedical engineering, including computational simulation of mechanics or flow for improved medical diagnosis, treatment & image-guided surgery. More about this course including its syllabus, course objectives and texts may be found at the Biomedical Imaging & Analysis (BIA) course webpage. Lectures and notes are only available on the Sun Yat-sen University Blackboard system to enrolled students or upon special request - so contact me if interested!This class included 34 graduate students having diverse engineering or biology backgrounds.
Teaching @ Carnegie Mellon, Pittsburgh
Spring 2014
I. Methods in Medical Image Analysis (MIIA)
Course instructor for Spring 2014 graduate course on Methods In Medical Image Analysis, listed across departments of biomedical engineering, electrical & computer engineering and the robotics institute at Carnegie Mellon University (16-725 (CMU RI) : 18-791 (CMU ECE) : 42-735 (CMU BME) as well as course number cross listed as BioE 2630 in University of Pittsburgh's school of bioengineering. This class was co-taught with Dr. John Gaelotti, Senior Project Scientist, with Carnegie Mellon University's Robotics Institute. I was primarily involved with re-designing and conducting selected lectures, tutorials as well as assignments on basic mathematical background in linear algebra and probability, shape-based image analysis and Python based programming using ITK / SimpleITK libraries for image processing. The class included 25 graduate students having diverse engineering or biology backgrounds. The text book for this class was Machine Vision, Wesley E. Snyder & Hairong Qi.
Check out one some of the basic math or SimpleITK assignments I prepared for this class here:
1) Basic linear algebra review: http://www.cs.cmu.edu/~galeotti/methods_course/assignment-math.html
2) Learning SimpleITK with iPython Notebooks: Assignment, Tutorial iPython Notebook
Check out one some of the basic math or SimpleITK assignments I prepared for this class here:
1) Basic linear algebra review: http://www.cs.cmu.edu/~galeotti/methods_course/assignment-math.html
2) Learning SimpleITK with iPython Notebooks: Assignment, Tutorial iPython Notebook
II. Bio-Image Informatics
Course instructor of Bio-Image Informatics, listed across departments of biomedical engineering, electrical & computer engineering and the computational biology (course number BME42-731 / ECE18-795 / CB02-740), at Carnegie Mellon University. This class was co-taught with Prof. Ge Yang, Assistant Professor of Biomedical Engineering, at Carnegie Mellon University. I was primarily involved with re-designing and conducting selected lectures on systems modeling of optical systems and as mathematical foundations for image processing, filtering and linear transforms. The class comprised over 25 graduate students. The text book for this class was Gonzalez & Woods, Digital image processing, 3rd ed., Prentice Hall, 2007. [Course Syllabus PDF].
Fall 2012, Spring 2019
Course instructor of 42-431, Introduction to Biomechanics, in Fall 2012 (co-instructor) and Spring 2019 (lead instructor), at Carnegie Mellon University.
In Fall 2012, this class was co-taught with Prof. Conrad M. Zapanta, Teaching Professor of Biomedical Engineering. I was primarily involved with designing and delivering lectures, tutorials and experiential learning exercises in biofluid mechanics and hemodynamics in the circulatory system, to a class of 20 mechanical / biomedical engineering juniors, seniors and graduate students. This course was developed based on the text book, Introductory Biomechanics: from Cells to Organisms, by Ross Ethier, with the support of Carnegie Mellon University's Eberly Center. Please contact me for information on faculty course evaluation and student feedback from this course.
In Fall 2012, this class was co-taught with Prof. Conrad M. Zapanta, Teaching Professor of Biomedical Engineering. I was primarily involved with designing and delivering lectures, tutorials and experiential learning exercises in biofluid mechanics and hemodynamics in the circulatory system, to a class of 20 mechanical / biomedical engineering juniors, seniors and graduate students. This course was developed based on the text book, Introductory Biomechanics: from Cells to Organisms, by Ross Ethier, with the support of Carnegie Mellon University's Eberly Center. Please contact me for information on faculty course evaluation and student feedback from this course.
Invited Teaching Lectures 2013-14
Path / Motion Planning for Robots
28 Nov 2014: Guest lecture in Dr. Juan Rojas's Introduction to Robotics class, in the School of Software, at Sun Yat-sen University's East Campus, in Guangzhou, China, on applications of image processing techniques to robotic path and motion planning. The focus of this lecture was to go over algorithms for optimal path planning in configuration spaces specific to the problem of using a multi degree of freedom robot designed for the purpose of autonomous driving of a vehicle through a maze. Primarily, the search problem of planning the motion of goal-based, rational agents in fully observable, deterministic, discrete, known environments was discussed along with basics on how to define the configuration space of a robotic system, creating probabilistic road maps (PRM) within this space, and traversing graphs along optimal paths (i.e. using the A* and Dijkstra algorithms). The use of different equations to solve the weighted Eikonal Equation (with the fast marching algorithm), was also discussed in the context of addressing the path-planning problem using a potential field approach.
Computational Biomodeling and Visualization
Guest lecture for Prof. Yongjie (Jessica) Zhang's Spring 2014 class on Computational Biomodeling and Visualization (CMU BME 24-658/ MechE 42-640), on 16 April 2014, titled: "Quantitative Analysis of Cardiovascular Morphology and Function: An Intro to Statistical Shape Descriptors & Shape Analysis."
The objectives of this course are:
• To introduce students the fundamentals of medical imaging, image processing, computational geometry, mesh generation, visualization and finite element analysis, and
• To expose students novel and advanced applications in computational biomedicine and other engineering fields
The objectives of this course are:
• To introduce students the fundamentals of medical imaging, image processing, computational geometry, mesh generation, visualization and finite element analysis, and
• To expose students novel and advanced applications in computational biomedicine and other engineering fields
Leveraging social media for networking
22 Nov 2013: Successfully taking advantage of social media for networking: For the active job seeker or entrepreneur. An interactive distance-learning seminar with biomedical engineering students of the University of Alabama at Birmingham, focused on how to successfully take advantage of social media for networking with potential employers, using social media to identify potential employees or business in industry, as well as how networking with social media may benefited the journey through graduate school and in starting a company. Several interesting aspects of leveraging the power of the internet, social media and one's online profile to behoove the opinion of a third person investigating a person's candidacy for a job were discussed. The session concluded with a discussion of strategies for approaching potential employers and marketing one's academic and professional experiences, skills and personality, with the goal of departing from mundane communications but instead leaving lasting, positive impressions...
Engendering the spirit of STEM
Teaching Science with an Engineering Twist
Conducted a workshop for middle and high school science, technology and mathematics teachers as well as school guidance counselors in the Pittsburgh regions, on 5 April 2014, investigating the value of invoking engineering principles into the high-school science & math curriculum. This workshop was sponsored by: Carnegie Mellon University Educational Outreach & The Leonard Gelfand Center for Service Learning & Outreach. Participants earned Act 48 hours and a stipend of $62.
Read more on the workshop goals and syllabus at the the workshop webpage: http://justcallharry.com/engineering-pittsburghs-high-school-curriculum.html
Read more on the workshop goals and syllabus at the the workshop webpage: http://justcallharry.com/engineering-pittsburghs-high-school-curriculum.html
Demonstrating the value of engineering in medicine using QuantMD's in-house surgical navigation technology in an animal study ...
On Monday, 22 July 2013, team QuantMD viz. David Schwartzman, MD, Daniel Ludwig and Prahlad G Menon, PhD, delivered a lecture to a class of students from the STEM academy of the Fox Chapel High School (Pittsburgh, PA) on image-guided surgery applied to cardiovascular interventions and demonstrated the value of the same in a live pig whose heart was accessed minimally invasively using a pericardial access needle introduced by sub-xyphoid access, under only image-guidance.
Selected Mentoring Experience
- Mentored students and interns from Carnegie Mellon’s Master of Software Engineering (MSE and MSIT) programs, as project sponsor for the Fall 2011 MSE Studio program and the Summer 2012 MSIT e-business technology summer practicum. Project work for QuantMD, LLC.
- Mentor and industry sponsor of the 2012 Computational and Systems Biology / Biomedical Informatics Summer Academy (CoSBBI) program. Trained a high school student to operate on proprietary advanced medical imaging programs, and mentored him to contribute to my ongoing independent research study on, “Assessing morphometric differences between patient-specific MRI reconstructed left ventricular models and an averaged left ventricular myocardial stereotactic atlas using parametric spherical harmonic technique.” Machine learning approaches and Baysian Rule Learning was employed to correlate resulting morphometric differences with clinical metrics for left ventricular function.
- Mentor and industry sponsor of the 2012 Computational and Systems Biology / Biomedical Informatics Summer Academy (CoSBBI) program. Trained a high school student to operate on proprietary advanced medical imaging programs, and mentored him to contribute to my ongoing independent research study on, “Assessing morphometric differences between patient-specific MRI reconstructed left ventricular models and an averaged left ventricular myocardial stereotactic atlas using parametric spherical harmonic technique.” Machine learning approaches and Baysian Rule Learning was employed to correlate resulting morphometric differences with clinical metrics for left ventricular function.
Other selected invited research lectures
- Invited talk on "Bridging the gap between personalized surgical planning and surgical practice, for cardiovascular procedures", hosted by Prof. Ender Finol, at the Department of Mechanical Engineering, UT San Antonio, San Antonio, TX on 23 Sept 2016.
- Invited talk on "Patient-specific Medical Image Quantification for Prognosticating Timely Treatment Response & Informing Therapeutic Strategy for Improved Cardiovascular Outcomes" at University of Texas at Austin, Austin, TX, hosted by Prof. Michael Sacks. This talk is part of the ICES Cardiovascular Engineering Seminar Series (Friday, Nov 21, 2014).
- Invited by Prof. Jaywant Arakeri, Department of Mechanical Engineering, Indian Institute of Science (IISc), Bangalore (India), to deliver a lecture on my research program, The MeDCaVE, titled, “Engineering surgical practice through cloud-based technology at the confluence of radiology, physics and informatics.” (16 Dec 2013).
- Invited to lecture on present and future directions based on lessons learned from computational fluid dynamics and computational function analysis applied to right ventricular biomechanics in pulmonary artery hypertension, at the 2013 Allegheny General Hospital / Allegheny Singer Research Institute Right Ventricular Function Meeting (9 Feb 2013).
- Invited by Prof. Jian-Gang (Jimmy) Zhu, Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh (USA), to deliver a lecture on, “Personalized Healthcare: Improving Healthcare through Quantitative Evaluation of Cardiovascular Morphology, Mechanics and Hemodynamics.” (27 Nov 2012).
- Delivered invited lecture titled, "Medical Device Innovation & Commercialization, from Concept to Exit – A Lesson on Entrepreneurship," at the 2012 CoSBBI program, at University of Pittsburgh.
- Invited talk on "Patient-specific Medical Image Quantification for Prognosticating Timely Treatment Response & Informing Therapeutic Strategy for Improved Cardiovascular Outcomes" at University of Texas at Austin, Austin, TX, hosted by Prof. Michael Sacks. This talk is part of the ICES Cardiovascular Engineering Seminar Series (Friday, Nov 21, 2014).
- Invited by Prof. Jaywant Arakeri, Department of Mechanical Engineering, Indian Institute of Science (IISc), Bangalore (India), to deliver a lecture on my research program, The MeDCaVE, titled, “Engineering surgical practice through cloud-based technology at the confluence of radiology, physics and informatics.” (16 Dec 2013).
- Invited to lecture on present and future directions based on lessons learned from computational fluid dynamics and computational function analysis applied to right ventricular biomechanics in pulmonary artery hypertension, at the 2013 Allegheny General Hospital / Allegheny Singer Research Institute Right Ventricular Function Meeting (9 Feb 2013).
- Invited by Prof. Jian-Gang (Jimmy) Zhu, Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh (USA), to deliver a lecture on, “Personalized Healthcare: Improving Healthcare through Quantitative Evaluation of Cardiovascular Morphology, Mechanics and Hemodynamics.” (27 Nov 2012).
- Delivered invited lecture titled, "Medical Device Innovation & Commercialization, from Concept to Exit – A Lesson on Entrepreneurship," at the 2012 CoSBBI program, at University of Pittsburgh.
Second opinions and medical technology solutions for the Patient.
We offer timely and accurate image processing of radiology images for clinical care, research, and training.
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The MeDCaVE – where QuantMD is engineered.
This is a service brought to you by the MEdical Diagnostics and CArdio-Vascular Engineering Lab.
The MeDCaVE – where QuantMD is engineered.
