“The evolution of computer systems has transformed the way we live. With our increasing affinity for smart-everything and our increasing interactions with several connected devices in everyday life, the security of computer systems has become a huge concern. Finding solutions for these new challenges keeps me motivated.”
Pritam Dash is a first year PhD student in Electrical and Computer Engineering at UBC. Along with with Guanpeng Li (University of Iowa), Zitao Chen, Mehdi Karimibiuki, and Karthik Pattabiraman, he has recently published a new paper: “PID-Piper: Recovering Robotic Vehicles from Physical Attacks.” This paper was awarded the Best Paper Award at the recent IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2021- number one out of nearly 300 total submissions!
In this interview, he discusses his recent award-winning paper, the future of safety for robotic vehicles, and why researching the security of autonomous systems is so important.
Testing the PID-Piper technique. You can watch the full video.
What is your winning paper about? Why is this line of research important?
In our paper, we present a new technique for mitigating sensor tampering attacks on autonomous robotic vehicles (RV), such as drones and rovers. Attackers can manipulate crucial sensors in RVs, like GPS or gyroscopes, and can hijack or crash RVs, resulting in damage and injuries- attacks like this have been performed on military and commercial drones. Our new technique, called “PID-Piper,” prevents the hijacking and the physical damage that can result from these attacks. What PID-Piper does is monitor the RVs during runtime to detect the attacks, and then, if it detects an attack, it activates a recovery controller that capacitates the RV to complete its mission despite the malicious interventions.
Autonomous systems such as drones and rovers are increasingly used, and make up a fast-growing industry. Attacks can disrupt critical missions and tasks, and this can have extensive economic impacts. And, as autonomous systems interact with us in the physical world, malicious intervention can cause people serious injuries. It’s important to identify and mitigate these security vulnerabilities before these systems are deployed widely.
What is the goal of your doctorate research? How does the topic of this paper fit into this?
In my doctoral research, I’m focusing on developing techniques to make autonomous systems safe and reliable. Basically, this involves analyzing the building blocks of autonomous systems (things like sensing and perception modules, control system, autonomous logic, and AI techniques) for vulnerabilities, and then mitigating these vulnerabilities. The goal of this is to enable autonomous systems such as RVs to operate normally, with minimal disruptions despite attacks or failure.
In this paper, we focused on one type of vulnerability- attacks targeting RV sensors. These attacks can’t be prevented by traditional software security techniques, so our attack resilient controller framework addresses this issue by enabling RVs to recover from sensor attacks and operate normally.
Testing the PID-Piper technique. You can watch the full video.
What is exciting to you about this topic?
Autonomous RVs have tremendous potential- not just in industrial sectors, but also for crucial tasks like carrying emergency medical supplies and assisting with disaster relief. Our research in the security and reliability of autonomous systems can help in developing safe and robust RV systems, and in ensuring that autonomous RV systems can handle even the worst possible circumstances. I believe that, by setting high safety standards, we can accelerate the use of autonomous systems in many more sectors and can begin to feel confident using RVs in everyday life.
What has motivated you to continue pursuing this research?
The evolution of computer systems has transformed the way we live. With the proliferation of connected devices, and our increasing interaction with them, the security and reliability of computer systems has become a huge concern. Our affinity for smart-everything has led to decentralization of computer systems and promotes autonomy in critical infrastructures like power grids, water treatment plants, in the automotive industry, etc. This presents new risks and challenges: intelligent designs and techniques must be developed to ensure the security and reliability of future computer systems. Finding solutions for these new challenges in a fast-evolving field keeps me motivated to pursue research in this area.
What has your career path looked like?
I completed my undergrad in Software Engineering at the Vellore Institute of Technology in India. During my undergrad, I’ve had some great opportunities- I worked at research institutes such as Fraunhofer SIT in Germany, and A*Star/NUS in Singapore. Following undergrad, I worked at the Technical University of Graz in Austria as a Research Engineer. After two years, I decided to return to graduate school and chose UBC for both my master’s and doctoral studies.
What advice do you have for a student interested in this field?
Designing and developing autonomous systems involves a lot of different types of expertise- namely in computer systems, robotics and control, signal processing, and computer vision. I’d encourage interested students to broaden their knowledge, even if it’s outside of their core area. The ECE department provides the perfect platform for this, with our wide range of courses offered, and we have professors who are experts in all of these fields.
Interested in having your own story shared? Do you have an interesting project, job, or initiative? Want to discuss your experience at ECE or your outlook on engineering? Get in touch with us, and you could win ECE merch!
“As a TA, you learn to look at problems from a different perspective, and come up with unique ways to explain the same problem to different audiences. ”
Rubinder Nagi completed his BASc and MASc at ECE, graduating in 2018 and 2021. Over his five years at ECE, he boasts the achievement of having been a teaching assistant (TA) for ten different courses, and in total has TA’ed an impressive eighteen separate times!
He’s TA’ed for APSC, ELEC, CPSC, and other courses taken by ECE students, and was even awarded the graduate teaching award by the CS department, recognizing his work managing over 34 other teaching assistants as Head TA for APSC 160.
We spoke to him about his experience in this important role. Rubinder shares his insights into the ups and downs of TAing, and discusses how his work teaching impacted his time at ECE and outlook as an engineer.
What has your career path/academic experience looked like?
I completed my BASc in Electrical Engineering in 2018 at UBC with one year of co-op, and joined the MASc program, under Christine Chen. After defending my thesis, “Bayesian Inference of Parameters in Power System Dynamic Model Using Trajectory Sensitivities” in early 2021, I began working at Intel as a hardware engineer. I really enjoyed my eight years at UBC- I met wonderful people and made connections with students, peers, colleagues, and professors.
Why did you start TAing?
I was passionate about teaching when I was young, even before I joined UBC. In my second year, the instructor for CPSC 259 told us they preferred students who have taken the course to TA it. That ended up being the first course I TA’ed, and it kickstarted my journey as a TA for the rest of my time at UBC.
What was TAing like at first? Did you face any initial challenges?
I started TAing in my third year of undergrad. Initially it was quite challenging, as I didn’t have experience teaching in a group setting or holding lab sessions. Over time, I became more comfortable with the role and improved my teaching skills. Since I was TAing a course that I’d taken one year ago, few of the students were also my classmates in other courses- which was quite an interesting experience! This happened again when I was TAing graduate courses later on.
As I gained more experience, I decided to take on more responsibilities. During my last year at UBC, I was the Head TA for APSC 160, and managed over 30 TAs (including distributing grading, and managing exam problems, lab sections, TA hours etc) online. I also received the CS GTA award!
How did your approach to TAing change over the course of your time at ECE?
I’ve worked with some really great TAs and instructors, who helped me improve my teaching skills. My explanation style has evolved as I observed how experienced TAs and instructors answered student questions. Now, I’m able to break down a problem into manageable steps and solve it one step at a time, which keeps students from feeling overwhelmed. Problem solving is an important skill for an engineer, and I tried my best to make students eager to face new challenges.
What was your favourite part of TAing? Any favourite courses, topics, or instructors? Why?
My favourite part was interacting with students and watching their faces glow when they finally understood the material. There’s no greater joy than seeing students light up as they solved a problem that they’d been stuck on for a whole week! I missed this a lot during the pandemic, as pretty much all the students had their webcams turned off.
I’ve TA’ed over 10 courses in the past five years. My favourite course to TA is APSC 160- it consists of a diverse audience, from programming pros to students who’ve never written code before. All in all I’ve TA’ed it seven times. Sometimes students would solve a problem in such a way that it left all the graders amazed- none of us had thought of that perspective.
I enjoyed working with all the talented and competent instructors at UBC. My favourite instructor to work with is Dr. Luis Linares, as I loved his classes as a student and how energized he was during his lectures. I TA’ed his courses as a grad student, and I saw all the work that needed to be put into making YouTube videos, WeBWorK assignments, exam solutions, Canvas quizzes, and rubrics. It’s a fascinating experience to see a course you took as a student from a grader’s perspective.
What have you learned?
TAing has significantly improved my confidence, communication, public speaking, and intrapersonal skills. My audience ranged from first year students to people with 10+ years of industry experience. As a TA, you learn to look at problems from a different perspective, and come up with unique ways to explain the same problem to different audiences.
What is your advice for other students who might be interested in working as a TA?
One misconception is that one needs to be in a masters or doctoral program to be a TA. Although this is true for higher-level courses, students can become a TA as early as in their second year!
Even if a student doesn’t have excellent grades, they can talk to the course instructors about TA positions, and show their interest and enthusiasm for TAing. ECE students are preferred to TA CPSC 259, as they are the only ones who take this course. APSC 160 has over 600 students and 30 TAs with various degrees of experience. A TA for this course could be completing their BASc, BSc, MASc, MEng, MSc, or PhD!
Interested students can apply for Undergraduate (or Graduate) TA positions with the ECE as well as with the CS department. Prospective or current TAs can attend events offered by UBC CTLT to prepare and improve themselves for this role.
It’s a great learning opportunity and you form invaluable connections. To quote Benjamin Franklin,
“Tell me and I forget, teach me and I may remember, involve me and I learn.”
Rubinder Nagi told us about his ECE experience through our survey. Fill out this survey to let us know if you have an ECE experience you think would make a great article. If your story is published on the website, we’ll send you ECE merch!
Khaled Ahmed, Dr. Mieszko Lis, and Dr. Julia Rubin
Congratulations to Khaled Ahmed, Dr. Mieszko Lis, and Dr. Julia Rubin, who received the Distinguished Paper Award at the IEEE International Conference on Software Testing, Verification, and Validation (ICST) 2021 for their paper, “MANDOLINE: Dynamic Slicing of Android Applications with Trace-Based Analysis.”
The paper, Dr. Rubin explains, “proposes an efficient and effective program slicing approach for mobile applications, which outperforms the state-of-the-art in this area. It is used in our current work on mobile malware detection and can also be used by other researchers and developers to build techniques for a variety of software engineering tasks, including automated program testing, repair, comprehension, and evolution.“
”Dynamic slicing was already extensively studied in the literature.” Khaled says. “However, we found the state-of-the-art in slicing Android apps was far from perfect. MANDOLINE introduces a highly accurate and efficient slicing tool. We also contribute a benchmark with manually marked ground-truth to evaluate dynamic slicing for Android – the first of its kind.”
“I’m thankful to my co-authors for the productive collaboration and to the ICST community for this recognition.” Dr. Rubin adds. “I hope this work will facilitate additional research in the area of mobile analysis.”
“Striking the right balance between the social and technological is what has given our app a competitive edge time and time again…”
Parsa Riahi is a senior undergraduate student in Computer Engineering at UBC, working on Machine Learning Research at Huawei. When not busy with studying or his co-op placement, he is hard at work developing a new startup that he hopes will revolutionize UBC’s social life and revitalize Vancouver’s restaurants.
Parsa Riahi is the Chief Technology Officer at Dyne, an app that has already accumulated hundreds of users. Dyne ranks as one of UBC’s top 10 ventures, and has entered the top 7% of 30000 companies who applied for Y-combinator. In this interview, Parsa discusses the ups and downs of startup development, his hopes for Dyne, and how his time at ECE shaped this initiative.
Dyne logo.
1. What does Dyne do?
As a UBC student, I always faced challenges staying connected with friends when our course schedules diverged. With Dyne, we combat isolation by connecting people over food. We have an app that uses map-based features such as radar to provide restaurant recommendations, shows real-time wait times, and suggest friend’s profiles- which allows users to meet up at a restaurant in just 5 clicks.
2. What has the process of developing Dyne been like? What is your role in this process?
The Agile development cycle at Dyne is, simply put, a rollercoaster. There are great highs in creating new features, deep lows in debugging and testing, cyclic loops of finding user issue after issue and designing solutions for them, and there are many times when things feel upside down. Despite all these challenges, I love the ride.
Once we understood our user base, it was a long road to developing a final product, starting from UI/UX to system design to full-stack feature development to DevOps, and finally to deployment.
My own role in this process is all over the place. I work around 80-90 hours a week and I handle a little bit of everything right now, but I am also supported by a fantastic team of twelve other engineering and computer science students. After all, as a UBC startup targeting students, it only makes sense to have that perspective throughout our company.
Henry McCreight (COO), Parsa Riahi (CTO), and Arnav Mishra (CEO)
3. What was the most challenging part of developing the app?
One of the most challenging parts of leading a social startup is understanding your user base. As engineers, we are often overly focused on the tech and lose sight of our core audience. Striking the right balance is what has given Dyne a competitive edge time and again- we have gotten into the top ten ventures at UBC and into the top 7% of 30000 applicants at Y-combinator. Most of all, it has allowed us to create an incredible and disruptive mobile app for our users.
4. How has COVID-19 affected the development of Dyne?
COVID-19 initially hit Dyne hard. We were unable to have in-person meetups- the backbone of our app. But in the 16 months since life in public shut down, we have seen a surge in our following. We used this time to really listen to our users and develop the best product possible. While we hit many barriers along the way, we have found a new resilience that has ensured Dyne will be instrumental in helping restore social and restaurant life.
The Dyne team meeting over Zoom.
5. What have you learned?
I have learned a lot — mostly because I have failed a lot. Beyond all the various technologies and Agile methodologies I’ve picked up, this ability to fix failures quickly has been vital in ensuring we move fast and meet deadlines. Albeit, sometimes fast fixes become all-nighters, and some weeks you work over 100 hours- but still, you press on because you have a responsibility to your users, your team, and yourself to consistently deliver on your promises.
6. What did you enjoy the most about developing the app?
I am obsessed with the impact that Dyne can have for all UBC students. I love that we are connecting friends old and new. Our app has established hundreds of meetups in just the first few weeks of our launch, and we are now poised to help revitalize the restaurant economy.
7. How has this experience fit into your overall experience at ECE?
ECE has given me the foundation to think from a principles-first perspective, and from a software engineering viewpoint. It has given me access to not only my great team (many of whom are from ECE) but also many wise and interesting professors and mentors from the faculty and industry at large.
Specifically, Dyne’s technical mentor and Lead SWE at Facebook’s Oculus, Matt Keoshkerian, and my long-time mentor and friend, ECE Professor Shahriar Mirabbasi, have taught me how to think and expand my potential. For this, I will be forever indebted to them.
8. What are your hopes for the app in the future?
I hope this app becomes a part of interaction in the social landscape of UBC and all universities across North America. I know that we at Dyne will not stop until we see this through and I am truly excited to bring everyone on this journey with us.
Interested in having your own story shared? Do you have an interesting project, job, or initiative? Want to discuss your experience at ECE or your outlook on engineering? Get in touch with us, and you could win ECE merch!
Six new projects led by UBC ECE researchers have been awarded a total of $1.3 million through the Natural Science and Engineering Research Council’s Discovery Grants and Discovery Accelerator Supplements programs. These awards, which are part of the Government of Canada’s investment of more than $635 million into science and research, will support ECE faculty in fostering new research, providing an environment for training and capability, and purchasing essential equipment.
From powering electric vehicles to experimenting with quantum computing, learn about how five ECE researchers will be using this funding to explore new ideas in electrical and computer engineering.
Thrampoulidis, Christos: Fundamentals of Modern Machine Learning: A Precise High-dimensional Approach
$220,000 (5 years)
What research will you be undertaking as a part of this grant? What impact will this work have?
We aim to use data-driven machine-learning (ML) algorithms to create automated decision rules in more aspects of everyday life — such as in disease diagnoses, self-driving cars, and digital banking. But we need to make sure that these algorithms meet critical requirements on safety, fairness, and efficiency. My goal is to contribute to the expanded use of ML by developing statistical theory-driven models equipped with formal theoretical guarantees that can inform and guide the design of algorithms that fulfill such requirements.
What draws you to this work?
An exciting feature of my work on modern learning theory is that there is a vast gap between theory and practice. Today, the most impressive recent discoveries in ML come from empirical/heuristic approaches inspired by practice. For the most part, we do not yet understand fundamental aspects about the operational characteristics and limitations of existing techniques. What drives me is the challenge to close this gap.
What specific aspect of this research are you most excited for, and why?
To me, the fast-growing pace of the field is most exciting: new algorithms, architectures, and phenomena are constantly discovered and documented; but also, as these new phenomena emerge, new questions and challenges arise — and with that, new theories await to be formulated. This fast pace of discoveries keeps us on our toes and constantly provides opportunities to learn something new.
Shahrad, Mohammad: From Serverless to Seamless: Building the Next-Generation of Cloud Systems by Eliminating Service Integration and Resource Heterogeneity Limitations
$120,000 (5 years)
What research will you be undertaking as a part of this grant? What impact will this work have?
This grant is focused on building cloud computing systems that can handle different usage scenarios, without a user or developer intervening. This way, developers spend less time figuring out how to connect different cloud services and can develop applications in a platform-agnostic manner.
What draws you to this work?
There are many different cloud providers, each with numerous varieties of services. Assisting developers through automated decision-making is critical in helping them focus on their primary role of software development.
What specific aspect of this research are you most excited for, and why?
Perhaps the most exciting part of this research is exploring new ways to seamlessly use heterogeneous hardware in cloud data centers. Modern cloud data centers are equipped with specialized hardware such as Graphics Processing Units (GPUs), Field Programmable Gate Arrays (FPGAs), and smart Network Interface Controllers (NICs), and current technology trends will only diversify this mix in the future.
Wang, Zehua: Next Generation Secure and Collaborative Internet of Things (IoT) System – Leveraging Blockchain for Decentralized Control and Privacy Preserving Machine Learning
X
$ 140,000 (5 years)
What research will you be undertaking as a part of this grant? What impact will this work have?
Basically, this grant provides us the opportunity to work towards building a trustworthy and collaborative environment where individuals can contribute their knowledge for machine learning and AI- without giving out their private data. It means the value of the data always belongs to data owners, who can directly benefit from their data without privacy leakage.
What draws you to this work?
My motivation with this research is to put the authority and control of data back to the hands of people. In most cases, it is the people or users that create the data when using online services. The service provider with big data and machine learning algorithms can build a better service when more data is received. On the other hand, the data contributed by individuals may be private, and the value of the data may not directly benefit the original data owner
What specific aspect of this research are you most excited for, and why?
Big data is the most valuable aspect of an information system, but usually, without a centralized system, we can’t guarantee the data’s quality or format, and can’t verify each user’s identity or authority. The most exciting aspect of this research is investigating how to resolve these issues. Another exciting element is incentivizing people to collaborate faithfully with the system by designing incentive mechanisms.
Ordonez, Martin: Flexible Power for Future Zero-Emissions Shipping and Delivery
X
$320,000 (5 years)
What research will you be undertaking as a part of this grant? What impact will this work have?
In a medium-sized North American city, collectively, people drive one billion kilometres each year for consumer goods and food, which leads to up to 400,000 tonnes of greenhouse gas emissions. In response to this, we envision the development of a home delivery infrastructure. The short-term goal of our program is to enable optimal infrastructure to supply energy to electric home delivery vehicles. The energy infrastructure technology we develop will reduce the impacts associated with peak load for charging an extensive, dynamic, fleet of electric vehicles.
What draws you to this work?
I love delivery, but I love it even more when it’s done with electric vehicles in a sustainable manner. Online shopping and delivery could potentially reduce up to 87% of greenhouse gas emissions compared to driving to the store.
What specific aspect of this research are you most excited for, and why?
I’m most excited about opening new research opportunities for our graduate students that lead to great jobs!
Salfi, Joseph: Reactive Ion Etcher for Commercially Relevant Quantum Devices
X
$150,000
What research will you be undertaking as a part of this grant? What impact will this work have?
Quantum technologies such as quantum sensors and quantum computers are expected to have measurement and computational capabilities that are provably impossible for classical technologies. However, we are still learning the best ways to design and build them. With this infrastructure grant, we are receiving cleanroom equipment that expands our capabilities to design and build quantum technologies to realize this potential. This grant will enable us to rapidly build devices for quantum sensing and computation directly inside our own cleanroom at UBC, which we can then carry out our own experiments on.
What draws you to this work?
Quantum computers and sensors store, process, and measure information that is encoded in a fundamentally different way from our familiar classical technologies. What draws me to this research is that this is a fundamental change in the way we process information- this is poised to revolutionize what can be computed. There are many problems that need to be solved for us to realize this potential.
What specific aspect of this research are you most excited for, and why?
What is most exciting about this infrastructure is that it will enable graduate students to build new types of devices directly at UBC. These devices can kickstart new academic research and academia-industry partnerships that could realize the potential of quantum technologies.
Lukas Chrostowski was also awarded $380,000 for his project Silicon Photonics for Quantum Computing.
Interested in having your own story shared? Do you have an interesting project, job, or initiative? Want to discuss your experience at ECE or your outlook on engineering? Get in touch with us, and you could win a special ECE prize.
*Content warning: The following announcement refers to residential schools*
We in the Electrical and Computer Engineering Department would like to express our heartbreak and solidarity with Indigenous students, staff, faculty and community members as a result of the ongoing work to recover unidentified remains of children at former residential schools. We share in the grief being experienced at this incredibly difficult time. While people may already have ways to cope and find strength, we would like to encourage connecting with a loved one, slowing down to rest, or reach out to the supports that are available 24/7.
Resources for Indigenous students:
Hope for Wellness Help Line offers immediate counselling and crisis intervention to all Indigenous Peoples across Canada. It is available 24/7 and services are offered in English and French, and by request in Inuktitut, Cree, and Ojibway. Call the toll-free Help line at 1-855-242-3310 or connect to the online chat at www.hopeforwellness.ca
Indian Residential School Crisis Line (IRSSS) offers emotional support and crisis referral services by calling the 24-hour national crisis line at 1-866-925-4419.
The KUU-US Crisis Line Society operates a 24/7 crisis line serving the entire province. More information is available at https://www.kuu-uscrisisline.com/ or BC Wide Toll Free: 1-800-KUU-US17 (1-800-588-8717)
Métis Crisis Line is available 24/7 for crisis services. Call BC Toll Free: 1-833MétisBC (1-833-638-4722)
For non-Indigenous individuals, you may be thinking of what you can do to support Indigenous members of your community. In doing so, remember to be mindful of the actions you can take as an individual including learning more about reconciliation by reading the Truth and Reconciliation Calls to Action, reviewing the Indigenous Strategic Plan, and speaking to other non-Indigenous friends about your learnings. We also encourage students to reach out to the UBC Student Assistance Program if needed: https://students.ubc.ca/health/ubc-student-assistance-program-sap
“Stepping into a new field has been a challenge… But every single step has been joyful. “
Golara Javadi is a third-year PhD candidate in the Electrical and Computer Engineering department at UBC. In her own words, she’s someone who’s “constantly looking for new adventures and opportunities.”
Golara obtained her Bachelor’s degree from Isfahan University of Technology, and in her Master’s at Simon Fraser University, where she worked on cognitive radio and signal processing. Following that, she worked in the power industry for three years at ZE Power Engineering.
Her work experience is in power engineering- but Golara now studies AI. She recently became a fellow with the Borealis AI research centre, where she will be working to contribute to the advancement of Artificial Intelligence and Machine Learning. She’s passionate about enhancing peoples’ lives with the help of AI, through her research with ECE and Borealis AI.
In this interview, she discusses her experience navigating this transition and finding success at ECE.
What research will you be conducting as part of your fellowship with Borealis AI?
I am working on developing a novel technique for prostate cancer detection, based on ultrasound data enhanced with AI and machine learning.
How did you find out about this fellowship?
I follow Borealis AI on Linkedin. I was browsing my feed, and I noticed their post about this fellowship. I wasn’t hopeful about it, but I’ve learned not to self reject, and I decided to go ahead and apply. The process was straightforward from there.
What has your career path looked like up to this point?
My background was always electrical engineering, but I’ve tried different disciplines. I did my bachelor’s in telecommunication and electronics in Iran. After that, I continued on to a master’s in telecommunication at SFU, and started working as a co-op student in a software company, ZE Power Group.
Halfway through my co-op, I decided to switch to their sister company, ZE Power Engineering. This company was owned by the same owner but existed in a totally different area- the power industry. I got a job offer after my co-op terms ended.
My professional character formed there, and in that company I grew from a co-op student, to an electrical engineer, to a team lead. After three years, I decided to move on to the PhD program at UBC to work on AI. Right now I am working as an intern at Borealis AI, where they build AI solutions for RBC products.
Why did you choose to change your focus? What was this like?
I was always passionate about research, especially in signal processing and AI. After three years of working in the power industry, I was no longer feeling challenged enough by the daily routine of my job, and I was looking for a change.
I’m always open to new opportunities and am open to stepping out of my comfort zone, but this change was not easy, both financially and technically. The Four Year Doctoral Fellowship (4YF) program at UBC helped me with financial aspects, and I was able to overcome the technical challenges by reading a lot and getting support from my great friends and colleagues at UBC and SFU.
What has been a challenge of PhD study at ECE?
Coming back to school after industrial experience and stepping into a new field has been a challenge, as well as keeping up with the pace of new methods and advanced techniques that are being generated in academia every day. But every single step has been joyful.
In the beginning, there were a lot of challenges. I had to build the foundations of my own computer science knowledge and start implementing very quickly. I am still learning, and I am quite happy with where I am now.
What has been something you’ve enjoyed?
Through my studies at ECE, I tried to be proactive and not only focus on learning and publishing results, but also be involved in extracurricular activities- things like being a secretary in ECEGSA and a woman in engineering advocate with the “Women in Engineering and Geoscience Division” of EGBC.
What is one piece of advice you would give a new student starting their program at ECE?
If you don’t feel happy with what you are doing, get out of your comfort zone. Trust in yourself, and never self-reject.
“Electrical and computer engineering is one of the most rapidly evolving fields of science, shaping people’s day-to-day lives.”
Melika Shahriari is a graduating PhD candidate in Electrical and Computer Engineering at UBC and TRIUMF, Canada’s particle accelerator centre. Melika received a MASc degree in Mechatronic Systems Engineering from Simon Fraser University, and her B.Sc. degree in Electrical Engineering from Sharif University of Technology, Iran.
Her research focuses on the control of the RF electromagnetic field of cavity resonators in particle accelerators. In this interview, Melika discusses her research, her experience at ECE, and her perspective on engineering- and shares highlights from her PhD thesis, Iterative Learning Control for Beam Loading Cancellation in Electron Linear Accelerators.
The draw of electrical and computer engineering
I’d always had this curiosity- I wanted to know what was going on in my computer or my phone, and I found that studying electrical engineering could answer some of my questions.
I think electrical and computer engineering is one of the most rapidly evolving fields of science. It shapes people’s day-to-day lives. Many of the biggest and most important modern technological advances- things like computers, cell phones, medical equipment and automotive systems- are owed to electrical and computer engineering.
TRIUMF control room.
Researching at TRIUMF
My research is based in TRIUMF, Canada’s particle accelerator centre, which is located at UBC. Particle accelerators are used to deliver beams of charged particles such as protons, electrons or heavy ions. These beams of accelerated particles are used for a variety of research topics- from astrophysics and the origin of our universe, to subatomic particles and particle physics.
My research involves cavity resonators, which are devices that generate an electric field to accelerate particles. I developed an iterative learning controller to predict and correct something called ‘cavity field error.’
Basically, if we want a high quality beam of particles, the electric field should be precisely controlled to ensure that all the particles receive the same energy. When the cavity accelerates a bunch of particles, its energy drops. This means there will be less energy available for the particles that arrive later, and there will be a lot of energy difference in the beam, which could lead to beam loss and instability. My research provides a solution by controlling the cavity field in a very short amount of time, which results in a uniformly accelerated beam.
These beams can be used for lots of different research activities. In TRIUMF, for example, apart from research in physics, the proton beam is used for treating eye tumours, and the Positron Emission Tomography program develops novel radioactor for medical imaging, which can be used for researching Parkinson’s disease.
I’d spent almost a year developing the control system on a new digital field-programmable gate array (FPGA) board, which is an integrated circuit that the user can configure and change its functionality. But, due to COVID-19, we never got to commission the new board, since we lost access to the lab.
I managed to do some tests with a different implementation of my controller on the current control system in the TRIUMF electron linear accelerator just before the pandemic, but because of the pandemic I didn’t get to compare those results with the controller on the FPGA board.
Work after graduation
I’ll be joining the Intel programmable solutions group in Toronto after I graduate. Intel is one of the biggest field-programmable gate array (FPGA) manufacturers in the world. FPGAs are usually used for applications that require high speed, where conventional processors can’t meet the timing requirements.
I had to learn FPGA for my research, so I was using the product as a user. I’m very excited to join the developer-side now! One interesting fact is that the team manager of the group I’m joining is actually also a PhD graduate of UBC ECE.
TRIUMF e-linac
Insights on her time with ECE at UBC
With my research, I really enjoyed getting to meet and work with so many brilliant minds, and having the luxury of working in a great lab with advanced technology. Conducting research in a multidisciplinary field has helped me learn a lot, especially from physicists.
My advice for others entering this field is to not underestimate the importance of connecting with people, be it other fellow students, professors, grads or people in the industry. Sometimes when you have a heavy workload, there’s a tendency to isolate yourself to get your work done. But I think now that the human connection is largely missing from our lives due to COVID-19, it’s easier to realize its importance.
Highlights from Melika Shahriari’s thesis:Iterative Learning Control for Beam Loading Cancellation in Electron Linear Accelerators
Radiofrequency (RF) cavities are metal structures that contain a standing wave electromagnetic field. The electric component of the field is used for particle acceleration. If a particle with charge q passes through the electromagnetic filed, the total force it experiences is given by Lorentz law as
F = q(E + v × B),
where E is the electric field, B is the magnetic field and v is the velocity of the particle.
A nine-cell superconducting cavity resonator used in TRIUMF electron linear accelerator (e-linac) is shown in Figure 1, and Figure 2 shows the field distribution in a single cell.
Figure 1. A nine-cell elliptical Niobium superconducting cavity
Figure 2. Field distribution in a single cell of an elliptical cavity. The blue arrows show the electric field and the red arrows show the magnetic field in π mode.
There are multiple phases of operation for a cavity resonator illustrated in Figure 3. In the filling phase, the generator stores energy into the cavity, and the cavity voltage increases with a time constant and reaches the desired value, like charging a capacitor. In the flat-top phase, when there is no beam, the generator provides energy to compensate for ohmic losses, which is pretty small in superconducting cavities. When beam is injected, energy is transferred from the cavity to the beam, and the cavity voltage drops, like discharging of a capacitor. This is called the beam loading effect. It is desired to cancel this effect as fast as possible and maintain a constant accelerating field.
Figure 3. Phases of operation for a cavity and beam loading effect during flat-top stage.
Feedback control is typically not fast enough to reach the desired response time. Therefore, feedforward control is often used in parallel to a feedback controller. The feedforward controller could be a constant gain. For complete beam loading cancellation, the gain should be equal to the voltage drop due to beam loading. An exact prediction of the beam current and the resulting voltage drop is required for effective beam loading cancellation. If there is an offset error due to wrong approximation, the error repeats at every pulse.
In this research, iterative learning control (ILC) is used in parallel to a constant-gain feedforward controller to predict the beam loading effect and cancel it by learning from the previous beam pulses. ILC is an open loop control strategy for systems that perform the same task repetitively. It improves the system performance by learning from the previous iterations.
The proposed iterative learning control was designed and tested on TRIUMF e-linac injector cavity (EINJ). The results are shown in Figure 4. The blue signal shows the cavity voltage when there is only the feedback controller in the loop. The beam loading effect can be clearly observed as a decrease in cavity voltage. The green signal shows the cavity voltage with the manual constant-gain feedforward controller. Beam loading cancellation is slightly improved. The best result is achieved when the ILC is on, shown in red. The beam loading effect is almost fully cancelled. Figure 5 shows the result from beam position monitor (BPM). BPM measure the energy of different electrons in the beam by measuring their position. In the ideal case, the BPM signal is flat, indicating that all the electrons have the same energy. In Figure 5, the blue curve shows the BPM data for the case where there is only a feedback controller. Due to lack of beam loading cancellation, the beam energy drops as time goes on. Turning the manual feedforward on results in the red curve, which is slightly better but still the beam energy decreases. The most stable beam energy is achieved with the ILC, shown with green, where the energy is mostly constant throughout the pulse.
Figure 3. Comparing the envelope of the cavity voltage for the cases where a) Both the ILC and feedforward controllers are off, b) Only the manual feedforward control is on, and c) Both ILC and feedforward are on. The best beam loading cancellation is achieved with the latter case.
Figure 5. Comparing beam position monitor data for three cases: a) Both feedforward and ILC are off. In this case, the energy of the beam gradually drops because of beam loading effect. b) Only the manual feedforward is on. Beam energy is more uniform compared to the previous case. c) Both ILC and manual feedforward are on. In this case since beam loading effect is canceled, we have the most stable beam energy throughout the beam pulse.
If you want to connect with Melika about her research, she can be reached at shahriari.melika@gmail.com.
Interested in having your own story shared? Do you have an interesting project, job, or initiative? Want to discuss your experience at ECE or your outlook on engineering? Get in touch with us, and you could win a special ECE merch prize.
“We are living in an ever-changing world, and the chances of your random bits of information positively impacting your life is not small…”
Amir Abdi graduated in 2020 with a PhD from the the Department of Electrical and Computer Engineering. Abdi’s research links the science of machine learning, the art of software engineering, and jaw reconstructive surgeries and cardiovascular interventions.
Over the course of his studies, Abdi pursued degrees in dentistry as well as in Computer Engineering. He followed these degrees with a Ph.D. in Electrical and Computer Engineering from UBC, during which he was awarded the Vanier Scholarship of Canada.
In this interview with UBC Applied Science, he discusses why he chose his unique field of study, his insights for students pursuing their own studies, and his outlook as he concludes his PhD.
A smart lithium battery charger design, one of five winning Design + Innovation Day projects.
This year, UBC Applied Science hosted their fifth annual Design + Innovation Day! At this event, students in their final year of undergraduate studies showcase their year-long Capstone projects. These projects are completed in small teams, and challenge students to use their skills and knowledge to solve a real-world engineering problem proposed by a community partner. By the end of it, our partners leave with a functioning design, and potentially a working prototype, as a solution.
ECE would like to congratulate our five winning teams for their project excellence based on technical achievements and the engineering process. The following five teams are the recipients of the UBC Applied Science Capstone Faculty Awards. Read about them below!
Automated AI Photogrammetry Apparatus
Team members: Estalin Alvarez, Robert Bradley, Sam Bedry, Seth Whalen, Tarryn MacPherson Community partner: UBC Studios
Our project
Our project automated the photogrammetry process, taking a series of standard photos from a camera and combining them into a 3D model.
UBC Studios’ current photogrammetry system can create 3D models; however, it is limited to small objects that can be placed on a turntable. To improve this system, we designed and simulated a mobile photogrammetry robot. Utilizing its free ranging wheels and vertical chain drive, the robot can scan large objects such as furniture. Additionally, the system is automated to reduce workload and time spent creating the 3D scans. The robot autonomously determines photo locations, uses VR tracking to orient the camera and takes a photo of the object at each location.
Our inspiration
We chose this project because we were all interested in some aspect of robotics, either the hardware or the software that controls them. We were also moved by the real-world problem that this project was attempting to solve: enabling more digital learning methods using 3D models to aid faculties and students that rely on analyzing physical objects, such as bones or antiques, for academia.
Our biggest challenge
As the COVID emergency limited our access to manufacturing equipment and materials, we soon realized that we were unable to construct a physical prototype of our robot. Due to this, we decided on a more unconventional approach of designing our project using simulation software. Similarly, the scope of the project was also a continuous concern since the project had multiple different sections, but we managed to successfully delegate each section in accordance with our own aptitudes.
What excited us most
Broadly speaking, it was just an awesome idea! We got to design a robot with a wide range of functionality that proved to be a rewarding technical challenge. It was awesome to take a lot of things we have seen in classes and apply them to something, as well as learn a lot along the way. More specifically, what continuously motivated us was the opportunity to develop a technology that will be able to materialize virtually any object into a digital model and the possibilities this opens for online learning and future VR technologies.
The most interesting/surprising thing we learned
Primarily, the most surprising factor that we came across was that we were able to create a fully functional virtual model that successfully met our clients’ requirements and expectations solely through simulation software.
Another aspect that we found interesting about this project in comparison to the other project courses we’ve had was the flexibility we had. These projects have so many options, nearly infinite possibilities, so it’s easy to get locked in dependent decision-making loops. But it was nice to see the group move and flow and adjust based on decisions we made together.
Our project’s future
The next steps for this project would be to build a physical model and work on integration and testing of sections of the robot that we only tested through simulation. More work could also be done for the body, in particular working on the placement of all the components within the frame and expanding the wheel control system and communication protocols. The image capture process can also be improved by adding more user inputs. Doing so would make the image capture process more customizable depending on the object being scanned.
Hand Gesture-Controlled Robot Pet
Team members: Charley Johnston, Dianna Kan, Steven Song, Danni Zhao, Sunny He Community partner: Huawei
Our project
Consider having a pet that is smart, responds to your commands without training and even takes pictures for you! You don’t even have to pick up after or buy kibble for this pet! This is a dream come true for those craving an animal companion but cannot afford the time, money or maintenance required for real animals. Robot pets are one example of how technology can assist in scenarios where companionship and fun are needed, but the handling and upkeep of real pets isn’t possible. especially in health care or senior homes.
Apart from doing normal pet things such as moving around and performing a few tricks, it can also perform robot tasks, like capturing photos with the camera in its nose. It can also communicate its mood through animated eyes on a colored LCD screen mounted to its head.
Through its camera “eyes”, this robot pet uses a combination of machine learning and computer vision to see and respond to commands given through its owner’s hand gestures. The robot pet can track, recognize and perform a task such as following the user while video capturing. The user is thus able to control the pet from a distance, enabling full autonomy.
Our inspiration
We were inspired to pursue this project largely because of the machine learning component used by the robot pet to recognize human faces and hand gestures, as well as the fun, entertaining nature of the project. As the use of machine learning applications is on the rise, we were very excited to take the opportunity to gain some experience with machine learning by integrating it into an ECE project. Many machine learning developments are used in important projects and applications, such as machine learning algorithms used in health care to detect cancer cells in patients, or machines in waste management facilities used to sort recyclables, in order to help protect the environment and prevent landfills from filling up. We were drawn to this project partly because it was an opportunity to integrate machine learning into something that could be a part of your average person’s everyday life. We hoped to bring to light that machine learning can be used by anybody that has a little bit of programming experience, not just in crucial applications or by big companies.
Our biggest challenge
The biggest challenge we faced was integrating together the many subsystems of the robot, while still having the robot respond quickly to commands given to it through hand gestures. Within just a couple of seconds, the robot needed to be able to recognize a hand gesture, update its LCD screen to display the appropriate animation, move itself forwards, backwards or spin around using the motors attached to its wheels or take pictures using its camera. We needed to change the design of the robot several times and make many optimizations in order to achieve this quick response time.
What excited us most
For us, the most exciting thing about this project was the experience we gained utilizing machine learning. We included several machine learning algorithms which allowed the robot to recognize different hand gestures, as well as adjust the robot’s camera position to track the user’s face by moving the robot’s camera “eyes” using servo motors. We were thrilled to gain some experience using machine learning, as it’s not taught in the core ECE curriculum.
The most interesting/surprising thing we learned
One of the most surprising things we learned through this project is that Huawei has its very own deep learning framework, similar to TensorFlow, called MindSpore. Most people probably know Huawei for their smartphones, but it turns out they are developing a lot of projects using machine learning and AI. One of Huawei’s goals is to redefine user experience with AI by making it more personalized for people in all aspects of their life.
Our project’s future
We hope that our robot pet project inspires people to think about how machine learning and robots can solve problems in ways that haven’t been considered before, as well as inspire people to create projects of their own. For example, we hope that our robot pet can help provide companionship to people who are unable to have pets. As well, we hope that smart toys such as our robot pet may be able to spark some passion in technology, electronics and machine learning in kids (or adults!) who play with them. Our project is open source on Huawei’s GitHub, so anyone who wants to is able to improve our robot by making it more pet-like or adding features.
Lab-in-a-Pack
Team members: Ray Allen, Richard Chang, Renz Patrick Angeles, Matthew Schwab, Victor Sira Community partners: ECE professor Dr. Sudip Shekhar and Intel Lab’s Rajesh Inti (individuals not representing their respective organizations)
Our project
Undergraduate ECE lab equipment has remained virtually unchanged over the last few decades. However, the costs have grown prohibitive for many. In addition, the COVID-19 pandemic has led to the global curtailment of on-site lab activities. Both of these issues have made it difficult to build electronics.
To combat both these problems, the team designed the Lab-in-a-Pack: a small, affordable device that replaces four common pieces of lab equipment: an oscilloscope, multimeter, signal generator and variable power supply. The capable hardware array in tandem with the flexible software stack makes the Lab-in-a-Pack an indispensable tool for anyone interested in electronics. Its extensibility combined with its low price will allow for important problems to be solved at a fraction of the cost compared to traditional equipment.
Our inspiration
We look back on our ECE education and remember the many late nights spent in the labs — if only the Lab-in-a-Pack had existed back then, we could have been home much earlier. Reflecting on our own experiences, we were motivated by an earnest desire to make an impact on future ECE students.
Our biggest challenge
Developing and testing hardware prototypes without access to a lab is a challenging endeavour. It is also especially challenging to debug circuits individually without the in-person help of your team.
What excited us most
Despite the challenges, our team was motivated by the fact that the Lab-in-a-Pack is a device that can solve many of the problems we faced working on our project remotely. We are also quite excited to use it ourselves!
The most interesting/surprising thing we learned
We were surprised by the number of companies working on portable lab equipment, and the extremely different approaches each one took.
Our project’s future
We’re looking into further developing the product, to bring the goal of affordable, portable lab equipment one step closer.
Smart Lithium Battery Charger
Team members: Grant Andersen, Arslan Bhatti, Will Ries, Igor Vuckovic, Yingrui Yang Community partner: GlüxKind Technologies
Our project
Our smart lithium battery charger is designed to cater to a self-driving stroller application, where the end user will want to be able to select fast charging if they are in a rush, or slow charging when they want to keep the batteries healthy.
Our battery charger is designed to function alongside a wireless user interface that can be used on any laptop or desktop capable of a bluetooth connection. The purpose of this is so that a GlüxKind engineer can have absolute control of how the batteries are charged, which is dependent upon battery type, capacity and voltage.
In the future, once the design of the self-driving stroller has been finalized, GlüxKind will modify our interface for the end user so that they can simply choose if they want fast charging or slow charging.
Our inspiration
The opportunity to work on a power electronics project with a large emphasis on adaptability, especially regarding the end-user market, and adding a large interactive component over a wireless interface.
Our biggest challenge
Due to COVID we found it especially hard to coordinate as a team in terms of the hardware. Testing our Printed Circuit Boards (PCBs) was especially difficult as there were safety restrictions and procedures that had to be created, approved and followed. Additionally, we were required to get a lot of information from our client about their facility, where we would be working, we came up with safety procedures that we would follow, and had to get approval from our instructor and TA.
What excited us most
In our power electronics course, ELEC 451, we learned about the basics of DC-DC converters and the theory behind them. This project allowed us to explore the practical applications of what we learned in that course and to verify it for ourselves.
The most interesting/surprising thing we learned
At the beginning of our project, our client had a good idea of what they wanted in terms of overall design in order to meet all requirements. In the end, we met the criteria for the project using an altogether different design.
Our project’s future
Additional features can be given/more control can be given through the wireless user interface, such as being able to save charging settings for later, and other such features that were outside of our project scope.
A few aspects of our hardware can be optimized to increase efficiency and/or reduce size of the product.
Xbox One Arm Cycle Adaptive Controller
Team members: Scott Beaulieu, Edward Luo, Keith Consolacion, Fabian Lozano, Nicholas Winship Community partners: Physical Activity Research Centre (PARC), UBC School of Kinesiology, Makers Making Change, Microsoft
Our project
Individuals with physical disabilities often have limited options to be physically active. A popular form of cardio exercise for people with Spinal Cord Injuries (SCIs) is “hand cycling”. At the Physical Activity Research Centre (PARC), users with SCIs can engage in many physical exercise activities while building social connections within their community.
With the ongoing COVID-19 situation and the initial closure of PARC, it was clear that there was a need for a new home-based exercise device for individuals with SCIs. The goal of this capstone project was to develop an Arm Cycle Controller, compatible with the Xbox adaptive controller for Xbox One Series consoles and Windows 10 PCs. The final product is aimed at bringing an inexpensive and engaging exercise experience into the end user’s home, one that can foster community through online engagement.
Our solution is an electromechanical adapter that adds controller functionality to a commercial mini-exercise bicycle. The device achieves this by sending control signals derived from encoder and inertial measurements to an Xbox Adaptive Controller through audio cables. These signals are interpreted as joystick and trigger inputs which allows for racing games to be played using an Xbox One Series console or Windows 10 PC.
Our inspiration
The common drive amongst our team members to work on this project would have to be wanting to give back to the community at large. It felt like a project where we could realistically create a product that would brighten lives.
Our biggest challenge
Our biggest challenge would definitively be how much in-person work was required for our project. We had to design the entire project before meeting in-person at our client’s facilities within the last several weeks of the course to properly assemble it.
What excited us most
It would have to be the first time we saw everything working. It involved lots of jumping in excitement and laughing when it first worked. I think it is a fond memory for all of us on the team.
The most interesting/surprising thing we learned
That you can quite quickly re-wire a TRRS audio jack into two TRS audio jacks!
Our project’s future
The project will continue to be iterated on and upgraded by teams working with PARC. They will work towards creating a finalized product that will hopefully be affordable, able to be built easily and then provided to persons with spinal cord injuries.
