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  • Classifying Holes, Voids, Negative Objects and Nothing and Quantum Computing

    Date: Tuesday, March 9, 2021 Time: 1:00 p.m. - 2:00 p.m. Speakers: Katrina Hooper, Javaid Iqbal Zahid Location: Virtual - Zoom Organizers: IEEE Toronto WIE Contact: Maryam Davoudpour Abstracts: In the fields of Urban Search and Rescue (USAR), Search and Rescue (SAR) and autonomous travel, understanding the entirety of the environment is an asset and most times a requirement. For example, in USAR, it is in the spaces between objects within a rubble pile, which are a type of negative objects, where trapped people can be found and where structural instabilities are located. While most research focuses on classifying positive objects, we work to build a framework to understand negative objects and a set of standardized terminology to discuss and classify them. This presentation will discuss the necessity for creating a lexicon for negative objects, exhibit applications of negative object research, and suggest a starting point for vocabulary to reduce ambiguity around classes of negative objects. Furthermore, we aim to spark a discussion about negative object research and suggest a starting point for a novel research area. Quantum computing is one of the emerging technologies for the future. Quantum computing is based on the principles of quantum mechanics and fuses beautifully with computer science. It is often in the news when computing supremacy is discussed. Governments and big technology companies like, IBM, Google, Microsoft, Intel, etc. along with private partners, are heavily investing in this technology. Quantum mechanics is based on counterintuitive properties like superposition, entanglement, and interference that make it different from classical computing. It is expected to outperform classical computing in certain areas of applications, like medical science, computer science, and cryptography, to name a few. In this talk, we will discuss the fundamentals of quantum computing with an introduction to the principle/properties of quantum mechanics, its usefulness for representing information, and what operations can be performed on the information represented by Qubits. While quantum gates, the fundamental information processing units of quantum computing are based on mathematical constructs from Linear Algebra and Probability, classical computing is based on Boolean Algebra and Logics gates. A number of possibilities for representing and processing quantum information are much larger than classical computing – hence the promise of larger computer power of quantum computing. Biographies: Katrina Hooper Katrina is in her final year in her Computer Science Masters at Ryerson University. She holds an Honors BSc. from the University of Toronto with a specialist in Physics and a minor in Mathematics. Her interests are in the development of negative object research and imitation learning for chess engines. Under the supervision of Dr. Alex Ferworn, she works to build a lexicon and a classifier for negative objects. Javaid Iqbal Zahid Mr. Javaid Iqbal Zahid is currently a PhD student in Department of Computer Science, Ryerson University, and is supervised by Dr. Alex Ferworn. Mr. Javaid holds Bachelor of Science degree in Telecommunication Engineering and Master of Science degree in Electrical Engineering, specializing in Communications and Computing. Additionally, he obtained advanced training in Cryptology and Wireless communications. Inspired by Dr. Claude E. Shannon, he has special interest in information theory, cryptography. He has been involved in deployment and operations of data networks and datacenters for a large government organization. He has also been acting as chief information security officer (CISO). At Ryerson, he is currently conducting research in quantum computing with special attention in quantum cryptography. He is member of IEEE Computer, Communication, and Information Theory Societies.

  • In celebration of International Women’s Day Wearables in Healthcare: A Woman’s Perspective

    Join us for an afternoon celebrating the work of women in wearable technology focused on health and life stages. Network with women using and integrating tech for the value it can provide. Collaborate in workshops where we will co-design the future wearables, apps and services that address our priorities and needs. Date: 10 Mar 2021 Time: 03:00 PM to 05:00 PM Speaker(s): Renn Scott, Samira Rahimi Location: Virtual Organizer(s): IEEE Toronto WIE, IM/RA Contact: Toronto Section Affinity Group,WIE, Toronto Section Jt. Chapter, IM09/RA24 Biographies: Renn Scott; MA, Interaction Design, RCA, Founder + Chief Designer of Daily Goods Design LABS, Senior Director of UX + ID at Myant A design leader and prolific inventor, Renn has a passion for creating innovative user experiences and forward-thinking product designs. With over 20 years of experience at companies such as Myant, IBM and BlackBerry in leadership roles within user experience, design research, consumer insights and strategic innovation, Renn has helped design best in class products and experiences. Renn’s hands-on approach and point of view as a designer is radically different than most. For any project she always starts with ‘WHY create’ in the first place and uses a co-creative design methodology and best practices based on insights gained from female consumers. Renn’s experience and observations has been that there is a lack of female design leaders and designers in the tech and design fields. Instead of just leading by example Renn also strives to empower other women to make, create and innovate in the field of design, technology and fashion by sharing her insights, skills and knowledge through Daily Goods Design LABS pop ups and educational event series. Samira Rahimi Eng. Ph.D., Assistant Professor, Department of Family Medicine, McGill University Samira Rahimi Eng. Ph.D. is an Assistant Professor in the Department of Family Medicine at McGill University, affiliated scientist at Lady Davis Institute for Medical Research of the Jewish General Hospital, and academic member of Mila—Quebec AI Institute. She is FRQS Junior 1 Research Scholar in human-centered AI in primary health care. Her work as Principal Investigator has been funded by the Fonds de recherche du Québec – Santé (FRQS), Natural Sciences and Engineering Research Council (NSERC), Roche Canada, Brocher Foundation (Switzerland), and the Strategy for Patient-Oriented Research (SPOR)-Canadian Institutes of Health Research (CIHR). With an interdisciplinary background, Dr. Rahimi is interested in the development and implementation of clinical decision support tools and patient decision aids, as well as integrating human-centered AI tools in primary health care. She specializes in computational intelligence, decision making, and applied operational research in health care.

  • Hands-on Reinforcement Learning Workshop using Python

    Montreal, Quebec Canada

    IEEE Young Professionals Affinity Group Montreal brings you a free hands-on reinforcement learning workshop using Python in Google Colab. This event is co-hosted by IEEE YP Ottawa, YP Toronto, YP Vancouver, IEEE SBs of Polytechnique Montreal, Concordia, ETS, INRS, WIE Ottawa, SIGHT Montreal, and CAS technical chapter of vancouver section. All students at all levels are welcome to attend, however, registration is mandatory through the secure IEEE web portal. This workshop will cover the basics of using Colab, an introduction to reinforcement learning, and together we will write your first Q-learning code. The workshop will be interactive, and you will have a chance to code with us and ask your questions. We will also have breaks, a discussion forum, polls, and Q&A. Virtual platform info has been delivered to registrants in rounds of emails. For immediate assistance, please write us at yp.ieee.mtl@gmail.com Speakers: Sadia Khaf Sadia Khaf received the B.E. degree in electrical engineering from the National University of Sciences and Technology, School of Electrical Engineering and Computer Science (NUST-SEECS), Islamabad, Pakistan, in 2015. She received the M.Sc. degree in electrical and electronics engineering from Bilkent University, Ankara, Turkey, in 2018. From 2015 to 2018, she was a Research Assistant with IONOLAB, Turkey. From 2018 to 2020, she worked with the Faculty of Electrical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), Pakistan, as a Lecturer. She conducted her research there on Mobile Edge Computing and Deep Learning with the TeleCoN research group. Currently, she is with École de Technologie supérieure, Montreal, Canada, as a Ph.D. student. Her research interests include reinforcement learning, radio resource management, cognitive radio networks, and industrial internet-of-things (IIoT). She was the recipient of the highest level of merit scholarships at NUST, Bilkent, and ÉTS. She also secured the P.E.O. International Peace Scholarship. She is the co-founder of SAYA school, Pakistan, and IEEE Women in Engineering (WIE) branch at ÉTS. She serves as the Vice-Chair of the IEEE ÉTS and Industrial Relations Manager of the IEEE Montreal Young Professionals Affinity Group. Faye Satari Faye Satari was born in Quchan, a small town with minimal educational infrastructure and facilities. When she finished primary school, she was accepted in the provincial entrance exam of the Exceptional Talents High School. After excelling in high school and hard working around the clock, she participated in a very competitive tuition-free nationwide university entrance exam (i.e. Konkour) among about one and half million participants; She was accepted in Computer Software Engineering of Urmia University. During her undergraduate education, she actively participated in many teamwork projects and attended some technical seminars as well as joining associations at her university. Furthermore, she got the title of top student in technical faculty of the university in one semester and received her B. Sc. degree in Computer Software Engineering from Urmia University of Technology, Urmia, Iran, in 2008. She is currently pursuing an M.Sc.A. Computer Engineering in the Department of Computer and Software Engineering, Polytechnique Montréal, University of Montreal, Montreal, Canada and she is a member of IEEE Young Professionals. Her current research interests include the Internet of Things (IoT), Smart Cities, and telecommunications systems.

  • IEEE VT Chapter Women in Engineering Series

    On April 13, 2021 at 7:00 p.m., Dr. Fatima Hussain will present the talk “Insider Threat and Behaviour Modelling/Professional Career Development Discussions”. Date: Tuesday, April 13, 2021 Time: 7:00-8:00pm Speaker(s): Dr. Fatima Hussain, Senior Member, IEEE, Manager, Event Management and Analytics, User Behaviour Analytics and Insider Threat, Global Cyber Security, Royal Bank of Canada, Toronto Adjunct Professor, Ryerson University, Toronto Location: All events are held with Zoom Meeting https://ryerson.zoom.us/j/96808290854 Meeting ID: 968 0829 0854 Organizer(s): IEEE VT Chapter Contact: Lian Zhao Abstract: In the first half of the talk, discussion about behaviour modelling and insider threat is done. Insider threat classification and related threat vectors are discussed in detail. Afterwards, various methods used for identification and remediation of insider threat are presented, along with cutting edge enterprise level tools and frameworks.In the second half of the talk, we will have on-live discussions for professional caree rdevelopment, through experience sharing and opinion sharing, to encourage and guide young researchers career development plan, and to motivate women career development in engineering. Biography: Fatima Hussain received the Ph.D. and M.A.Sc. degrees in Electrical and Computer engineering from Ryerson University, Toronto, ON, Canada. Upon graduation, she was a Postdoctoral Fellow with the Network-Centric Applied Research Team (N-CART), where she worked on various NSERC-funded projects in the realm of the Internet of Things. Currently, she is part of User Behaviour and Insider Threat team ,working as a Manager, Event Management and Analytics in Royal Bank of Canada (RBC), Toronto.She is responsible foremployee profiling and detection of insider threats, by establishing baseline behaviours. She is working as an editor for IEEE Newsletter (Toronto), and associate editor for various journals. She is also an Adjunct Professor with Ryerson University and her role includes supervision of graduate research projects. Her research interests include cyber security,insider threat, XAI etc. Her background includes a number of distinguished professorships with Ryerson University and University of Guelph, where she has been awarded for her research, teaching, and course development accomplishments within wireless telecommunication and Internet of Things.

  • The Role of AI in 5G/6G and IoT-Enabled Smart Grids

    Montreal, Quebec Canada

    IEEE Young Professionals brings speakers from Canadian research groups to give the community technical talks in AI-Powered Wireless Communications and Intelligent Cyber Physical Analysis in IoT-Enabled Smart Grids. The virtual platform information will be sent to registrants a couple of hours ahead of starting the event. Contact: IEEE Young Professionals Montreal Speakers: Dr. Melike Erol-Kantarci of University of Ottawa Topic: AI-Enabled Wireless Networks: A Bridge from 5G to 6G Abstract: Future wireless networks are expected to support a multitude of services demanded by Enhanced Mobile Broadband (eMBB), Ultra-Reliable and Low-latency Communications (uRLLC), and massive Machine Type Communications (mMTC) users. Heterogeneous devices with different quality of service (QoS) demands will require intelligent and flexible allocation of network resources in response to network dynamics. For instance, a highly reliable and low-latency network is needed to enable rapid transfer of messages between connected autonomous vehicles. At the same time, the same physical infrastructure is expected to serve users with high-quality video demand or even mobile Augmented/Virtual Reality entertainment applications. Next-generation wireless networks are expected to accommodate such diverse use cases. In addition, resource efficiency, reliability, and robustness are becoming more stringent for 5G and beyond networks. To meet this, future wireless networks must incorporate a paradigm shift in network resource optimization, in which efficient and intelligent resource management techniques are employed. Artificial intelligence, or more specifically machine learning algorithms stand as promising tools to intelligently manage the networks such that network efficiency, reliability, robustness goals are achieved and quality of service demands are satisfied. The opportunities that arise from learning the environment parameters under varying behavior of the wireless channel, positions AI-enabled 5G and 6G, superior to preceding generations of wireless networks. In this keynote, we will provide an overview of the state-of-art in machine learning algorithms and their applications to wireless networks, in addition to their challenges and the open issues in terms of their applicability to various functions of future wireless networks. Biography: Melike Erol-Kantarci is Canada Research Chair in AI-enabled Next-Generation Wireless Networks and Associate Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory. She is a Faculty Affiliate at the Vector Institute, Toronto, and the Institute for Science, Society and Policy at University of Ottawa. She has over 150 peer-reviewed publications which have been cited over 5500 times and she has an h-index of 38. She has received numerous awards and recognitions. Recently, she received the 2020 Distinguished Service Award of the IEEE ComSoc Technical Committee on Green Communications and Computing. She was named as N2Women Stars in Computer Networking and Communications in 2019. Dr. Erol-Kantarci has delivered 50+ keynotes, tutorials and panels around the globe and has acted as the general chair and technical program chair for many international conferences and workshops. Her main research interests are AI-enabled wireless networks, 5G and 6G wireless communications, smart grid and Internet of things. She is an IEEE ComSoc Distinguished Lecturer, IEEE Senior member and ACM Senior Member Hadis Karimipour Topic: Intelligent Cyber Security Analysis in IoT-Enabled Smart Grids Abstract: Today’s smart grids are complex Cyber-physical Systems (CPSs) that integrate computational and physical capabilities for controlling and managing the ever-growing number of cyber-connected devices. Aside from a fault in the physical domain, CPS also suffer from cyber-attacks in both cyber and physical domain e.g., an industrial controller can be manipulated to launch various attacks such as the device state inference attack, leading to system instability. Therefore, any effort to secure the emerging critical CPSs is of paramount importance.  Nowadays, a cyber-security specialist must detect, analyze, and defend against many cyber threats in almost real-time conditions. Without the employment of artificial intelligence and machine learning techniques, dealing with a huge number of attacks in a timely manner is not possible. Intelligent, big-data analytical techniques are necessary to mine, interpret and extract knowledge of data when there is a significant amount collected from or generated by different security monitoring solutions. This talk will go through the CPS security challenges and AI-enabled state of the art solution in the literature. Biography: Dr. Hadis Karimipour is the director of the Smart Cyber-physical System (SCPS) Lab and an Assistant Professor in the School of Engineering at the University of Guelph. She is among the pioneers of using Machine Learning (ML) for security analysis of critical infrastructure. She has published more than 80 journal articles, conference papers and book chapters in top IEEE journals and conferences. She has been a keynote/invited speaker for more than 20 different IEEE/International Conference. She was the chair of the IEEE workshop on AI for Securing Cyber-Physical System (AI4SCPS) at IEEE CCECE 2019 and IEEE CyberSciTech 2020 conferences and chair of the special session on the AI for Security of IoT-Enabled Critical Infrastructures at the IEEE SMC 2020 conference. She was the technical committee member of numerous IEEE conferences, including IEEE SEGE 2018, 2019, 2020, IEEE DSAA 2020, PST 2020, IEEE EPEC 2018, 2020, and IEEE SMC 2020. Dr. Karimipour is the Associate Editor of the Frontiers in Communications and Networks Journal, Editor of American Journal of Electrical and Electronic Engineering, and Editor of Journal of Electrical Engineering. She has also served as Guest Editor for Elsevier Journal of Computer and Electrical Engineering. She was the Editor of the Springer book on Security of Cyber-physical System. Dr. Karimipour is a Senior Member of IEEE member, chair of IEEE Women in Engineering and chapter chair of the IEEE Information Theory Kitchener-Waterloo Section, and an active member of Society for Canadian Women in Science and Technology.

  • Introduction to Python Programming

    Virtual

    This is an introduction to Python programming for students without any prior programming knowledge or experience. The proposed 5-day course covers the fundamental aspects of programming, which include data types, various operators, input/output, conditions, control flow, functions, and algorithms. The learning experience is enhanced by a number of examples and problem sets (data, strings, file processing and simple graphics) that will be solved interactively during the lecture with the participation of the students. The course format includes 3 hours of daily lectures. Course Objective: Attendees will gain a solid understanding of principles of programing using Python; they can progress to more advanced programming topics and explores algorithms that are integral parts of more sophisticated methodologies, e.g., Artificial Intelligence. Attendees will have the knowledge to write various Python programs, and to design algorithms manipulating files and different types of data including numbers, and text. Note: This course is designed to be offered online, and it requires the attendees to use their personal computers/laptops. Details to Join in will be forwarded to Registered Attendees Who should attend: Students, second career trainees, engineers, scientists, clinicians, and in general specialists in variety of non-STEM fields. What will you receive after completion: A certificate of completion will be given to the students who successfully complete the course and pass a short exam. Electronic copies of the course materials. Attendees will also be provided with career, and skills development advice. Speaker Dr. Alireza Sadeghian Dr. Alireza Sadeghian has been with the Department of Computer Science at Ryerson University since 1999, where he holds the position of the Professor. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, and serves as the AI research Theme Lead in Healthcare and Analytics at the Institute for Biomedical Engineering, Science, and Technology. Dr. Sadeghian was the Chair of the Department of Computer Science from 2005 to 2015. He is the founding Director of the Advanced Artificial Intelligence Initiative (AI2) Laboratory and has extensive expertise in the areas of AI, machine learning, and Deep Learning particularly related to industrial and medical applications. He has supervised 9 postdoctoral fellows, 8 PhD, and 24 Master’s students, as well as 60 research assistants. He has published over 150 journal manuscripts, refereed conference papers, and book chapters, as well as two edited books. He has 2 invention disclosures and 2 patents. Dr. Sadeghian has been actively involved with a number of international professional and academic boards including IEEE Education Activity Board. Presently, he is the Chair of IEEE Computational Intelligence Technical Society Chapter, Toronto Section. Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access, Information Sciences, and Expert Systems Journal. Email: dr.alireza.sadeghian@ieee.org Agenda Day 1 – June 7, 2021, 6:00-9:00 pm: Introduction to computer systems, hardware architecture, CPU, memory, compilation, high level vs. low-level programming language, data representation, Python and PyCharm interactive IDE installation, writing/editing/saving/retrieving and running a simple program, basic data types, variables, assignments, comments, and expressions. The material learned will be reinforced through examples provided during the lecture. Day 2 – June 8, 2021, 6:00-9:00 pm: The following topics will be discussed: conditions, operators (arithmetic, logic, and comparison), control statements (if and if-else), and loops (for and while). The material learned will be reinforced through examples provided during the lecture. Day 3 – June 9, 2021, 6:00-9:00 pm: Students will be introduced to Strings and text files in Python. They will learn how to work with files, reading/writing text and numbers from/to a file, string manipulation, indexing, and string slicing. The material learned will be reinforced through examples provided during the lecture. Day 4 – June 10, 2021, 6:00-9:00 pm: Functions, arguments, and return values will be discussed. The material learned will be reinforced through examples provided during the lecture. Day 5 – June 11, 2021, 6:00-9:00 pm: The topics of lists and dictionaries will be discussed. Students will learn about the basic operators, creating, accessing, slicing, adding, removing, replacing, and iteration methods for lists and dictionaries. The material learned will be reinforced through examples provided during the lecture.

  • From an Idea to a Startup

    Virtual - Zoom

    We are living in the age of innovation. Every day, innovators are solving many problems that people are facing in life. In the process of innovation, there are many questions about how we can find problems. What is innovation exactly? How can we find solutions? And how can we learn the innovation process? I am Masoud Valinejad, CEO-Director of technology in NovoSolTech Company, and innovation mentor with more than five-year experience, with 10 USA patents, and more than five national and international special prizes in innovation competitions. In this webinar, I want to show you how you can become an innovator and entrepreneur through some steps and practices. Contact: Ayda Naserialiabadi

  • Distributed Machine Learning 101

    Toronto, Ontario, Canada, Virtual: https://events.vtools.ieee.org/m/276938

    Machine Learning is an indispensable part of data science, and there is no need to have a thorough programming background to benefit from it. Machine Learning (ML) and statistical techniques have provided a new era that enables us to convert the data into information and transform it into actionable knowledge. SciKit and TensorFlow are two states of the art libraries that can be used in Python, and this seminar will open the gate to know their bases. The first seminar is about “Hello World!” Machine Learning program, using the python language and SciKit learn library. Speaker(s): Dr. Reza Dibaj Virtual: https://events.vtools.ieee.org/m/276938

  • Product Lifecycle Management

    Virtual: https://events.vtools.ieee.org/m/275555

    Product Lifecycle Management is a process used to manage all of the business and technical aspects in the life of a product business, from early stage concept to product retirement. It is used extensively by most Global MultiNational Corporations but it serves small startup businesses very well also. It deals with and includes participation from all of the important business organisations. As such it is very relevant to engineers involved in any aspect of product development. Marto Hoary has worked with a number of multinationals in the USA and Europe where in he has observed and learned the use of this process first hand. Speaker(s): Marto J Hoary, Sr MIEEE, M. Eng. Virtual: https://events.vtools.ieee.org/m/275555

  • Sustainable Service Pricing in Cloud Ecosystems

    Toronto, Ontario, Canada, Virtual: https://events.vtools.ieee.org/m/276942

    Energy efficiency, which has emerged as a top priority in cloud ecosystems, is the outcome of appropriate pricing mechanisms and resource allocations. Static pricing mechanisms are the most dominant approach among all the others. They are simple to implement for the service providers and easy to understand for the service users. Inaccurate price calculation and low efficient resource allocation in static pricing mechanisms made researchers discover other solutions to overcome these issues. Double auction mechanisms are among the most appropriate dynamic models. The main challenge of conventional double auction mechanisms is not considering the cloud ecosystems' specifications, such as dynamic online features. The term dynamic refers to the many variable parameters in cloud ecosystems, and they constantly change. Conventional static offline pricing solutions are set based on a series of parameters before running the process. In dynamic online methods, we customize our pricing models based on dynamic and current parameters. Also, we continuously optimize these methods to attain optimal results. In this seminar, firstly, we define a Dynamic Online Double Auction Mechanism (DODAM) for the IaaS environment, which covers a broader range of IaaS parameters by considering the dynamic online features of such markets. Considering the features of cloud dynamic online ecosystems, DODAM provides an appropriate price scheduling for service providers and service users. Cloud secondary market is a new paradigm in IaaS ecosystems. In these markets, brokers and reseller buyers have attained their resources from service providers of the cloud primary markets in the form of timed packages and repackage them into smaller chunks. As unsold packages do not transfer to the next intervals, brokers and reseller buyers need to sell their packages as much as possible. We develop a mechanical design that includes a market-based pricing model and a resource allocation algorithm in such markets as our second contribution. Next, by formulating the inherent competitive features in cloud secondary markets, we improve the pricing and resource allocation mechanisms in such competitive ecosystems. In the last contribution, we proposed a Priority-based Dynamic Online Double Auction Model (PB-DODAM), considering the perishability and time constraints of traded resources in IaaS secondary markets. The provided experimental results show that all proposed mechanisms drastically increase resource utilization and the overall utility. Speaker(s): Dr. Reza Dibaj Virtual: https://events.vtools.ieee.org/m/276942

  • Basics of Programming in Python

    Virtual: https://events.vtools.ieee.org/m/277447

    Workshop Description: In the workshop, first the attendees will revisit the basic concepts of Python programming related to (1) writing and executing Python scripts to perform basic tasks, (2) entering and executing basic Python commands in a Jupyter Notebook, and (3) creating objects, data types such as strings, integers, Booleans, variables, lists, loops, coordinate system, if-statements, inequalities, etc. Later, this workshop will discuss the implementation of random variables and probability models in Python. In particular, we will introduce numpy that includes the basic understanding of arrays, matrices, matrices operations, random data generation and exercises. Furthermore, since understanding of Matplotlib is necessary to iplot functions and models in Python, we will explore basic strategies to plot using matplotlib Speaker(s): Taha Sajjad

  • Internships for Graduate and Undergraduate Students

    Virtual: https://events.vtools.ieee.org/m/281467

    Not sure how to find an internship? Unclear about how internships are structured? Join a Ryerson University Career & Co-op Centre, IEEE, and IEEE Women in Engineering collaboration for this informative workshop to learn about internship opportunities available for undergraduate and graduate students on Sept. 16 from 6-7 pm.