## Penn Engineering Summer 2020 Course Offerings

**FULL SUMMER**

** **

**MEAM 520 901 Introduction to Robotics Kumar, V.**

**MW 12:00 pm – 1:30 pm/F 12:00 pm – 1:00pm**

** **The rapidly evolving field of robotics includes systems designed to replace, assist, or even entertain humans in a wide variety of tasks. Recent examples include human-friendly robot arms for manufacturing, interactive robotic pets, medical and surgical assistive robots, and semi-autonomous search-and-rescue vehicles. This course presents the fundamental kinematic, dynamic, and computational principles underlying most modern robotic systems. The main topics of the course include: rotation matrices, homogeneous transformations, manipulator forward kinematics, manipulator inverse kinematics, Jacobians, path and trajectory planning, sensing and actuation, and feedback control. The material is reinforced with hands-on lab exercises involving a robotic arm.

**SUMMER SESSION I**

**BIOENGINEEERING**

** **

**BE 551 BIOMICROFLIDICS Huh, D. **

**TWRF 5:00 pm – 7:00 pm **

The focus of this course is on microfluidics for biomedical applications. Topics to be covered in the first half of this course include microscale phenomena, small-scale fabrication techniques, and sensing technologies that are often leveraged in the development of microfluidic systems for the study of biomolecules, cells, tissues, and organs in living biological systems. In the second half of this course, strong emphasis will be placed on the application of microfluidics in cell biology, bioanalytical chemistry, molecular biology, tissue engineering, and drug discovery.

Prereqisite: Experience with an undergraduate level fluid mechanics course is preferred. Examples of relevant SEAS courses include BE 350 (Biotransport), CBE 350 (Fluid Mechanics), and MEAM 302 Fluid Mechanics).

** **

**BE 559 910 Multiscale Modeling of Chemical Systems Radhakrishnan, R. **

**MTWR 10:00 am – 12:00 pm**

This course provides theoretical, conceptual, and hands-on modeling experience on three different length and time scales – (1) electronic structure (A, ps); (2) molecular mechanics (100A, ns); and (3) deterministic and stochastic approaches for microscale systems (um, sec). Students will gain hands-on experience, i.e., running codes on real applications together with the following theoretical formalisms: molecular dynamics, Monte Carlo, free energy methods, deterministic and stochastic modeling. Prerequisite: Undergraduate courses in numeral analysis and statistical mechanics.

**COMPUTER AND INFORMATION SCIENCE**

** **

**CIS 110 910 Introduction to Computer Programming Mally, A.**

**MTWR 10:00 am – 12:00 pm **

Introduction to Computer Programming is the first course in our series introducing students to computer science. In this class you will learn the fundamentals of computer programming in Java, with emphasis on applications in science and engineering. You will also learn about the broader field of computer science and algorithmic thinking, the fundamental approach that computer scientists take to solving problems.

**CIS 120 910 Programming Languages and Techniques I Fouh, E. **

**MTWR 10:00 am – 12:00 pm **

** **A fast-paced introduction to the fundamental concepts of programming and software design. This course assumes some previous programming experience, at the level of a high school computer science class or CIS110. (If you got at least 4 in the AP Computer Science A or AB exam, you will do great.) No specific programming language background is assumed: basic experience with any language (for instance Java, C, C++, VB, Python, Perl, or Scheme) is fine. If you have never programmed before, you should take CIS 110 first.

** **

**CIS 160 910/911 Mathematical Foundations of Computer Science Tannen, V. **

**LEC MW 1:00 pm – 3:30 pm/T 1:00 pm – 3:00 pm REC R 1:00 pm – 3:00 pm**

What are the basic mathematical concepts and techniques needed in computer science? This course provides an introduction to proof principles and logics, functions and relations, induction principles, combinatorics and graph theory, as well as a rigorous grounding in writing and reading mathematical proofs.

** **

**CIS 320 910 Introduction to Algorithms Kannan, S. **

**MW 2:00 pm – 5:00 pm **

How do you optimally encode a text file? How do you find shortest paths in a map? How do you design a communication network? How do you route data in a network? What are the limits of efficient computation? This course gives a comprehensive introduction to design and analysis of algorithms, and answers along the way to these and many other interesting computational questions.

You will learn about problem-solving; advanced data structures such as universal hashing and red-black trees; advanced design and analysis techniques such as dynamic programming and amortized analysis; graph algorithms such as minimum spanning trees and network flows; NP-completeness theory; and approximation algorithms.

**CIS 502 910 Analysis of Algorithms Khanna, S.**

**MW 9:30 am – 1:30 pm**

An investigation of paradigms for design and analysis of algorithms. The course will include dynamic programming, flows and combinatorial optimization algorithms, linear programming, randomization and a brief introduction to intractability and approximation algorithms. The course will include other advanced topics, time permitting. Prerequisite: Data Structures and

Algorithms at the undergraduate level.

** **

** ****ENGINEERING AND APPLIED SCIENCE**

** **

**EAS 203 910 Engineering Ethics Shields, B.**

**TR 1:15 pm – 5:05 pm **

** **In this course, students will study the social, political, environmental and economic context of engineering practice. Students will develop an analytical toolkit to identify and address ethical challenges and opportunities in the engineering profession, including studies of risk and safety, professional responsibility, and global perspectives. The course will begin with a foundation in the history of engineering practice and major Western ethical and philosophical theories. Students will then apply this material to both historical case studies, such as Bhopal, the NASA Shuttle Program, and Three Mile Island, as well as contemporary issues in big data, artificial intelligence, and diversity within the profession. Students will consider how engineers, as well as governments, the media, and other stakeholders, address such issues.

**EAS 512 910 Engineering Negotiation Diamond, S.**

**TR 9:00 am – 12:50 pm**

** **The goal of this course is to teach students of engineering and applied science to be effective negotiators. It aims to improve the way these students communicate i virtually any human interaction. The course intends to improve the ability of engineers and other technology disciplines to gain more support more quickly for projects, researc product and services development, and marketing. For those wanting to be entrepreneurs o r intrapreneurs, the course is designed essentially to find the most value possible in starting up and running companies. Based on Professor Diamond’s innovative and renowned model of negotiation, it is intended to assist those for whom technical expertise is not enough to persuade others, internally and externally, to provide resources, promotions and project approvals; or to resolve disputes, solve problems and gain more opportunities.

**ENGINEERING MATHEMATICS**

** **

**ENM 503 910 Introduction to Probability and Statistics Venkatesh, S.**

**MWF 12:00pm – 2:30 pm**

** **Introduction to combinatorics: the multiplication rule, the pigeonhole principle, permutations, combinations, binomial and multinomial coefficients, recurrence relations, methods of solving recurrence relations, permutations and combinations with repetitions, integer linear equation with unit coefficients, distributing balls into urns, inclusion-exclusion, an introduction to probability. Introduction to Probability: sets, sample setsevents, axioms of probability, simple results, equally likely outcomes, probability as a continuous set function and probability as a measure of belief, conditional probability, independent events, Bayes’ formula, inverting probability trees. Random Variables: discrete and continuous, expected values, functions of random variables, variance. Some Special Discrete Random Variables: Bernoulli, Binomial, Poisson, Geometric, Pascal (Negative Binomial) Hypergeometric and Poisson.

** **** **

**ELECTRICAL AND SYSTEMS ENGINEERING**

** **

**ESE 400 910/ESE 540 910 Engineering Economics Cassel, T.**

**MWF 9:00 am – 11:30 am**

** **This course investigates methods of economic analysis for decision making among alternative courses of action in engineering applications. Topics include: cost-driven design economics, break-even analysis, money-time relationships, rates of return, cost estimation, depreciation and taxes, foreign exchange rates, life cycle analysis, benefit-cost ratios, risk analysis, capital financing and allocation, and financial statement analysis.

Case studies apply these topics to actual engineering problems. Prerequisite: Knowledge of Differential Calculus

** **

**ESE 503 910 Simulation Modeling and Analysis Carchidi, M.**

**MWF 12:00 pm – 2:30 pm**

** **This course provides a study of discrete-event systems simulation in the areas of queuing, inventory and reliability systems as well as Markov Chains, Random-Walks and Monte-Carlo systems. The course examines many probability distributions used in simulation studies as well as the Poisson process. Fundamental to most simulation studies is the ability to generate reliable random numbers and so the course investigates the basic properties of random numbers and techniques used for the generation and testing of pseudo-random numbers. Random numbers are then used to generate other random variable using the methods of inverse-transform, convolution, composition and acceptance/rejection. Finally, since most inputs to simulation are probabilistic instead of deterministic in nature, the course examines some techniques used for identifying the probabilistic nature of input data. These include identifying distributional families with sample data, using maximum-likelihood methods for parameter estimating within a given family and testing the final choice of distribution using chi-squared goodness-of-fit.

** **** **** **

**MECHANICAL ENGINEERING AND APPLIED MECHANICS**

** **

**MEAM 415 910 Product Design Burns, C**

**TR 1:30 pm – 5:30 pm **

**(cross listed with OIDD 415, OIDD 515 and IPD 515)**

** **This course provides tools and methods for creating new products. The course is intended for students with a strong career interest in new product, development, entrepreneurship, and/or technology development. The course follows an overall product design methodology, including the identification of customer needs, generation of product concepts, prototyping, and design-for-manufacturing. Weekly student assignments are focused on the design of a new product and culminate in the creation of a prototype, which is launched at an end-of-semester public Design Fair. The course project is a physical good – but most of the tools and methods apply to services and software products. The course is open to any Penn sophomore, junior, senior or graduate student.

** **

**MEAM 543 910 Performance, Stability and Control of UAVs Kothmann, B.**

**MTWR 11:00 am – 1:00 pm**

** **This course covers the application of classical aircraft performance and design concepts to fixed-wing and rotary-wing Unmanned Aerial Vehicles (UAVs). A survey of the latest developments in UAV technology will be used to motivate the development of quantitative mission requirements, such as payload, range, endurance, field length, and detectability. The implications of theserequirements on vehicle configuration and sizing will be revealed through application of the fundamentals of aerodynamics and propulsion systems. The course will also cover basic flight dynamics and control, including typical inner-loop feedback applications.

** **

** **

** ****SUMMER SESSION II**

** Please Note: Offerings may be cancelled due to low enrollment up to one week before classes start.**

**COMPUTER AND INFORMATION SCIENCE**

** **

**CIS 262 920 Automata, Computability and Complexity He, P.**

**MTWR 1:00 pm – 3:00 pm**

This course explores questions fundamental to computer science such as which problems cannot be solved by computers, can we formalize computing as a mathematical concept without relying upon the specifics of programming languages and computing platforms, and which problems can be solved efficiently. The topics include finite automata and regular languages, context-free grammars and pushdown automata, Turing machines and undecidability, tractability and NP-completeness. The course emphasizes rigorous mathematical reasoning as well as connections to practical computing problems such as test processing, parsing, XML query languages, and program verification.

** **

**ENGINEERING AND APPLIED SCIENCE**

** **

**EAS 402 920/EAS 502 920 Renewable Energy and Its Impacts: Technology, Environment, Economics, Sustainability. Lior, N.**

**TWR 5:00 pm – 7:45 pm**

** **The objective is to introduce students to the major aspects of renewable energy, with its foundations in technology, association to economics, and impacts on ecology and society. This introduction is intended both for general education and awareness and for preparation for careers related to this field. The course spans from basic principles to applications. A review of solar, wind, biomass, hydroelectric, geothermal energy, and prospects for future energy systems such as renewable power generation in space. Prerequisite: Junior standing

** **

** ****ENGR 350 920 Biotechnology, Immunology, Vaccines and COVID-19 Hammer, D.**

**MTWRF 10:00 am – 12:00 pm**

This course will start with the fundamentals of biotechnology, and no prior knowledge of biotechnology is necessary. Some chemistry is needed to understand how biological systems work. We will cover basic concepts in biotechnology, including DNA, RNA, the Central Dogma, proteins, recombinant DNA technology, polymerase chain reaction, DNA sequencing, the functioning of the immune system, acquired vs. innate immunity, viruses (including HIV, influenza, adenovirus, and coronavirus), gene therapy, CRISPR-Cas9 editing, drug discovery, types of pharmaceuticals (including small molecule inhibitors and monoclonal antibodies), vaccines, clinical trials. Some quantitative principles will be used to quantifying the strength of binding, calculate the dynamics of enzymes, writing and solving simple epidemiological models, methods for making and purifying drugs and vaccines. The course will end with specific case study of coronavirus pandemic, types of drugs proposed and their mechanism of action, and vaccine development.

** **

** ****ELECTRICAL AND SYSTEMS ENGINEERING**

** **

**ESE 505 920 Feedback Control and Analysis Kothmann, B.**

**MTWR 11:00 am – 12:45 pm**

**(Cross listed with MEAM 513 920)**

Basic methods for analysis and design of feedback control in systems. Applications to practical systems. Methods presented include time response analysis, frequency response analysis, root locus, Nyquist and Bode plots, and the state-space approach.

** **

**ESE 531 920 Digital Signal Processing Khanna, T.**

**MTWR 2:00 pm – 4:00 pm**

** **This course covers the fundamentals of discrete-time signals and systems and digital filters. Specific topics covered include: review of discrete-time signal and linear system representations in the time and frequency domain, and convolution; discrete-time Fourier transform (DTFT); Z-transforms; frequency response of linear discrete-time systems; sampling of continuous-time signals, analog to digital conversion, sampling-rate conversion; basic discrete-time filter structures and types; finite implulse response (FIR) and infinite impulse response (IIR) filters; design of FIR and IIR filters; discrete Fourier transform (DFT), the fast Fourier transform (FFT) algorithm and its applications in filtering and spectrum estimation.

** **

**MATERIALS SCIENCE AND ENGINEERING**

** **

**MSE 561 920 Atomic Modeling in Materials Science Khantha, M.**

**MTWRF 1:30 pm – 3:00 pm**

**(cross listed with MEAM 553 920)**

** **This course covers two major aspects of atomic level computer modeling in materials. 1. Methods: Molecular statics, Molecular dynamics, Monte Carlo, Kinetic Monte Carlo as well as methods of analysis of the results such as radial distribution function, thermodynamics deduced from the molecular dynamics, fluctuations, correlations and autocorrelations. 2. Semi-empirical descriptions of atomic interactions: pair potentials, embedded atom method, covalent bonding, ionic bonding. Basics of the density functional theory. Mechanics, condensed matter physics, thermodynamics and statistical mechanics needed in interpretations are briefly explained. Prerequisite: Ability to write a basic code in a computer language such as fortran, C, C++

** **

**MECHANICAL ENGINEERING AND APPLIED MECHANICS**

** **

**MEAM 508 920 Materials and Manufacturing for Mechanical Design Turner, K.**

**MWF 2:00pm – 4:30 pm**

The selection of materials and manufacturing processes are critical in the design of mechanical systems. Material properties and manufacturing processes are often tightly linked, thus this course covers both topics in an integrated manner. The properties and manufacturing processes for a wide range of materials (i.e., metals, ceramics, polymers, composites ) are examined from both a fundamental and practical perspective. From a materials standpoint, the course focuses on mechanical properties, including modulus, strength, fracture, fatigue, wear, and creep. Established and emerging manufacturing processes will be discussed. Design-based case studies are used to illustrate the selection of materials and processes.

**MEAM 513 920 Feedback Control and Analysis Kothmann, B.**

**MTWR 11:00 am – 12:45 pm**

**(Cross listed with ESE 505 920)**

Basic methods for analysis and design of feedback control in systems. Applications to practical systems. Methods presented include time response analysis, frequency response analysis, root locus, Nyquist and Bode plots, and the state-space approach.

** ****MEAM 536 920 Viscous Fluid Flow and Modern Applications Arratia, P.**

**MWF 10:00 am – 12:45 pm**

This is an intermediate course that builds on the basic principles of Fluid Mechanics. The course provides a more in depth and unified framework to understand fluid flow at different time and length scales, in particular viscous flows. Topics include review of basic concepts, conservation laws (momentum, mass, and heat), fluid kinematics, tensor analysis, Stokes’ approximations, non-Newtonian fluid mechanics, and turbulence. The course will explore important modern topics such as microfluidics, swimming of micro-organisms, wind turbines, rheology, biofluid mechanics, and boundary layers. This course is intended for juniors, seniors, and graduate students from the School of Engineering and/or Arts and Sciences that have a general interest in fluid dynamics and its modern applications. Students should have an understanding of basic concepts in fluid mechanics and a good grasp on differential equations.

** **

**MEAM 553 920 Atomic Modeling in Materials Science Khantha, M.**

**MTWRF 1:30 pm – 3:00 pm**

**(cross listed with MSE 561 920)**

This course covers two major aspects of atomic level computer modeling in materials. 1. Methods: Molecular statics, Molecular dynamics, Monte Carlo, Kinetic Monte Carlo as well as methods of analysis of the results such as radial distribution function, thermodynamics deduced from the molecular dynamics, fluctuations, correlations and autocorrelations. 2. Semi-empirical descriptions of atomic interactions: pair potentials, embedded atom method, covalent bonding, ionic bonding. Basics of the density functional theory. Mechanics, condensed matter physics, thermodynamics and statistical mechanics needed in interpretations are briefly explained. Prerequisite: Ability to write a basic code in a computer language such as fortran, C, C++

** **