Review of sensing fundamentals, materials, mechanisms, read-out circuits, details of ADC’s, DAC’s, feedback control, real-time operating systems and implementations, mobile/wireless connectivity, mobile app development, predictive data analytics, machine learning implementations, embedded systems and board design process example, constraint-driven designs (power savings, bio-implantable sensing, long-range wireless connectivity, mission-critical life-support systems). Example state-of-the-art sensor system design examples on multimedia, security, healthcare, energy, consumer electronics tracks. Course project, optional labs.

A capstone design course where students apply engineering and science knowledge in an electrical-electronics engineering design project. Development, design, implementation and management of a project in teams under realistic constraints and conditions. Emphasis on communication, teamwork and presentation skills..

A capstone design project on an industrially relevant problem. Students work on teams in consultation with various faculty and industrial members.

Discrete and continuous random variables and processes, functions of random variables, independence of random variables. Central Limit Theorem. Discrete-time random processes, continuous-time random processes, stationary random processes, ergodicity, auto and cross correlation functions, power spectral density; spectral estimation, white noise processes, Markov chains.

Linear Algebra Review, Normal Matrices, Quadratic Forms and Semidefinite Matrices, Inner Product and Norm Spaces, State Space Descriptions for Continuous and Discrete Time Systems, Controllability, Observability, Stability, Realization Theory.

Study of computational models of visual perception and their implementation in computer systems. Topics include: image formation; edge, corner and boundary extraction, segmentation, matching, pattern recognition and classification techniques; 3-D Vision: projection geometry, camera calibration, shape from stereo/silhouette/shading, model-based 3D object recognition; color texture, radiometry and BDRF; motion analysis.

Characterization of communication signals & systems, digital modulation schemes, optimum reception for the additive white Gaussian noise (AWGN) channel, signal design for band-limited channels, Nyquist criterion, intersymbol interference (ISI), optimum reception for channels with ISI and AWGN, linear equalization, decision feedback equalization, adaptive equalization, channel capacity & coding, linear block codes, convolutional codes, multichannel and multicarrier systems, spread spectrum signals for digital communications, multiuser communications. Design oriented exercises using computer aids.

Entropy, Relative Entropy and Mutual Information; Asymptotic Equipartition Theory; Entropy Rates of a Stochastic Process; Data Compression; Kolmogorov Complexity; Channel Capacity; Differential Entropy; The Gaussian Channel; Maximum Entropy and Spectral Estimation; Rate Distortion Theory, Network Information Theory.

Review of sensing fundamentals, materials, mechanisms, read-out circuits, details of ADC’s, DAC’s, feedback control, real-time operating systems and implementations, mobile/wireless connectivity, mobile app development, predictive data analytics, machine learning implementations, embedded systems and board design process example, constraint-driven designs (power savings, bio-implantable sensing, long-range wireless connectivity, mission-critical life-support systems). Example state-of-the-art sensor system design examples on multimedia, security, healthcare, energy, consumer electronics tracks. Course project, optional labs.

A series of lectures given by faculty or outside speakers.

A series of lectures given by faculty or outside speakers.

Interns will spend four weeks in the Emergency Department. They will take an active role in the initial evaluation and treatment of patients, work alongside senior residents, attendings, and nursing staff, and are exposed to wide variety of patients, medical and surgical emergencies, and procedures. Interns will gain valuable experience, as they will be able to follow patients from presentation, through their workup, and onto their diagnosis and management. Interns will evaluate the patients’ level of urgency, learn and apply triage principles. Learn the basic interventions (such as urinary catheter, N/G gavage, taking blood sample, intubation etc). Interns will participate in daily teaching sessions, weekly departmental conferences, as well as lecture series designed specifically for them. (4 weeks; compulsory on-call nights and weekends)

Interns will spend four weeks in the Emergency Department. They will take an active role in the initial evaluation and treatment of patients, work alongside senior residents, attendings, and nursing staff, and are exposed to wide variety of patients, medical and surgical emergencies, and procedures. Interns will gain valuable experience, as they will be able to follow patients from presentation, through their workup, and onto their diagnosis and management. Interns will evaluate the patients’ level of urgency, learn and apply triage principles. Learn the basic interventions (such as urinary catheter, N/G gavage, taking blood sample, intubation etc). Interns will participate in daily teaching sessions, weekly departmental conferences, as well as lecture series designed specifically for them. (4 weeks; compulsory on-call nights and weekends)

Interns will spend four weeks in the Emergency Department. They will take an active role in the initial evaluation and treatment of patients, work alongside senior residents, attendings, and nursing staff, and are exposed to wide variety of patients, medical and surgical emergencies, and procedures. Interns will gain valuable experience, as they will be able to follow patients from presentation, through their workup, and onto their diagnosis and management. Interns will evaluate the patients’ level of urgency, learn and apply triage principles. Learn the basic interventions (such as urinary catheter, N/G gavage, taking blood sample, intubation etc). Interns will participate in daily teaching sessions, weekly departmental conferences, as well as lecture series designed specifically for them. (4 weeks; compulsory on-call nights and weekends)

Interns will spend four weeks in the Emergency Department. They will take an active role in the initial evaluation and treatment of patients, work alongside senior residents, attendings, and nursing staff, and are exposed to wide variety of patients, medical and surgical emergencies, and procedures. Interns will gain valuable experience, as they will be able to follow patients from presentation, through their workup, and onto their diagnosis and management. Interns will evaluate the patients’ level of urgency, learn and apply triage principles. Learn the basic interventions (such as urinary catheter, N/G gavage, taking blood sample, intubation etc). Interns will participate in daily teaching sessions, weekly departmental conferences, as well as lecture series designed specifically for them. (4 weeks; compulsory on-call nights and weekends)

The following objectives will be met through extensive reading, writing and discussion both in and out of class.Build a solid background in academic discourse, both written and spoken. Improve intensive and extensive critical reading skills. Foster critical and creative thinking. Build fundamental academic writing skills including summary, paraphrase, analysis, synthesis. Master cohesiveness as well as proper academic citation when incorporating the work of others.

The following objectives will be met through extensive reading, writing and discussion both in and out of class.Build a solid background in academic discourse, both written and spoken. Improve intensive and extensive critical reading skills. Foster critical and creative thinking. Build fundamental academic writing skills including summary, paraphrase, analysis, synthesis. Master cohesiveness as well as proper academic citation when incorporating the work of others.

Introduction to probability, sets, conditional probability, total probability theorem and Bayes rule; Independence, counting; Discrete random variables, functions of random variables, expectation, mean and variance; Continuous random variables, probability density functions, and cumulative distribution functions; Multiple random variables; Sums of random variables; Limit theorems; Covariance and correlation; Introduction to Stochastic Processes

Descriptive statistics; measures of association, correlation, simple regression; probability theory, conditional probability, independence; discrete and continuous random variables; probability distributions; functions of random variables; sampling distributions; estimation; inference (confidence intervals and hypothesis testing). Topics are supported by computer applications and specific examples from engineering applications.

Overview of corporate dynamics, including career paths, organizational structure and behavior in large organizations, corporate culture, decision-making process (organs, levels of authority, meetings, crisis and stress management), customer-focused organization and engineering ethics. There will be several case studies. There will also be high profile speakers from the corporate world to convey their real world experiences.

Overview of corporate dynamics, including career paths, organizational structure and behavior in large organizations, corporate culture, decision-making process (organs, levels of authority, meetings, crisis and stress management), customer-focused organization and engineering ethics. There will be several case studies. There will also be high profile speakers from the corporate world to convey their real world experiences.

Effective assessment of data by applying statistics and computing techniques. Introduction of major data descriptors. Applying spreadsheet tools to facilitate data analysis and consequent decision making. Introduction to flowcharts and algorithms. Algorithmic reasoning for computer programming. Emerging information and computing technologies and the future of computing.