Course Instructor (UCONN):
I have been a study helper since my childhood, and I really enjoy the process when I regularly teach, mentor, and engage with in total more than 160 students (including undergraduate advisees) annually. Since 2019 Fall, I have developed CSE-5095 Smart Cities and Urban Computing, as well as new materials for CSE-4502/5717 Big Data Analytics, and CSE-4820/5819 Introduction to Machine Learning. The latter two courses taught were part of the backbone of the UConn's MENG and MSDS programs during the COVID-19 pandemic (2020-2023), and shall have long-term and broader impacts ever after. Furthermore, I am really fortunate to work with the following TAs who are really responsible and professional.
Some Comments of Students (More will be Included; No Worries about Grammars):
CSE 4820/5819 (Fall 2023, Fall 2022, Fall 2021)
Teaching Assistant (HKUST) and Student Mentor:
I worked as a Teaching Assistant in 5 semesters out of my 8 amazing semesters in HKUST, and helped mentor more than seven Final Year Projects (FYP) and Undergrad Research Opportunities Projects (UROP).
I have been a study helper since my childhood, and I really enjoy the process when I regularly teach, mentor, and engage with in total more than 160 students (including undergraduate advisees) annually. Since 2019 Fall, I have developed CSE-5095 Smart Cities and Urban Computing, as well as new materials for CSE-4502/5717 Big Data Analytics, and CSE-4820/5819 Introduction to Machine Learning. The latter two courses taught were part of the backbone of the UConn's MENG and MSDS programs during the COVID-19 pandemic (2020-2023), and shall have long-term and broader impacts ever after. Furthermore, I am really fortunate to work with the following TAs who are really responsible and professional.
- CSE-4997: Senior Thesis CSE, Spring 2024
- CSE-4099: Independent Studies, Spring 2024
- CSE-4940: Computer Science and Engineering Design Project II, Spring 2024 (24 students)
- ENGR-5315: Capstone Project, Spring 2024
- CSE-4939W: Computer Science and Engineering Design Project I, Fall 2023 (24 students)
- ENGR-5315: Capstone Project, Fall 2023
- CSE-4099: Independent Studies, Fall 2023
- ENGR-1000: Orientation to Engineering, Fall 2023
- CSE-4820/5819: Introduction to Machine Learning, Fall 2023 (77 students; TAs: Rigel Mahmood, Abdul Wassay Qureshi)
- CSE-4502/5717: Big Data Analytics, Spring 2023 (66 students; TAs: Yijue Wang, Shaoyi Huang)
- CSE-4820/5819: Introduction to Machine Learning, Fall 2022 (58 students; TAs: Mahan Tabatabaie, Toan Nguyen)
- ENGR-5315: Capstone Project, Summer 2022
- CSE-4502/5717: Big Data Analytics, Spring 2022 (52 students; TA: Sara Wrotniak)
- CSE-4940: Computer Science and Engineering Design Project II, Spring 2022 (15 students)
- CSE-4939W: Computer Science and Engineering Design Project I, Fall 2021 (15 students)
- CSE-4820/5819: Introduction to Machine Learning, Fall 2021 (52 students; TA: Aaron Palmer)
- CSE-4502/5717: Big Data Analytics, Spring 2021 (60 students; TAs: Yijue Wang, Shariq Khan)
- CSE-5095: Special Topics in Computer Science and Engineering, Fall 2020
- CSE-4940: Computer Science and Engineering Design Project II, Spring 2020 (17 students)
- CSE-4939W: Computer Science and Engineering Design Project I, Fall 2019 (17 students)
- ENGR-1000: Orientation to Engineering, Fall 2019
- CSE-5095: Special Topics in Computer Science and Engineering, Fall 2019
- Abstract: Due to facilitating urbanization and exploding urban population, urban computing has attracted much attention across industry and academia. Urban computing involves the computing applications of networks, sensors, computational power, data and interdisciplinary knowledge domains to improve the living quality of densely populated areas. Topics in this course may include general framework of urban computing, urban computing applications, smart cities, urban sensing and data collection, urban data management, data mining and machine learning techniques for urban data processing, spatial-temporal data analytics, and knowledge domain fusion. Discussion and exploration may cover these and other emerging challenges and advanced topics in urban computing.
- Abstract: Due to facilitating urbanization and exploding urban population, urban computing has attracted much attention across industry and academia. Urban computing involves the computing applications of networks, sensors, computational power, data and interdisciplinary knowledge domains to improve the living quality of densely populated areas. Topics in this course may include general framework of urban computing, urban computing applications, smart cities, urban sensing and data collection, urban data management, data mining and machine learning techniques for urban data processing, spatial-temporal data analytics, and knowledge domain fusion. Discussion and exploration may cover these and other emerging challenges and advanced topics in urban computing.
Some Comments of Students (More will be Included; No Worries about Grammars):
CSE 4820/5819 (Fall 2023, Fall 2022, Fall 2021)
- "He was very clear, very sweet, and very helpful when concepts were confusing."
- "The contents were very well organized with some adequate examples. I liked the course overall."
- "The examples used are humorous and enjoyable and make the lessons stick."
- "The professor was easily the most engaging CSE professors I've every had. He was very nice and did his best to explain boring topics in an interesting way."
- "One of the most positive aspects in which the instructor taught the course was in personable character. I attended office hours to
ask questions following lecture and I felt comfortable asking questions and engaging with the professor." - "Professor He walked through complex math equations and the derivations needed for certain ML models."
- "I appreciated that the setup of the class promoted learning over grades because I was able to focus on learning the material and
mastering the assignments, rather than having to rush and do sub–optimal work. I also liked the instructor's lectures and found
them very informative." - "I'm deeply impressed by your personal fascination and professionalism. "
- "However, when I saw you gave a lot of passion and professionalism to this course, which gave me a strong courage to follow it.
- ...
- [The "Greatest" Comment Ever for My Teaching in CSE] "Uhm... maybe you should list it as a MATH course too because of how much math we did in that thing."
- "Professor He always goes through example problems in class so we can understand how to do them, and he posts the annotated
lecture slides on to HuskyCT, which is very helpful." - "The professor was quick to respond to any questions and concerns, and the example calculations definitely helped understand
many of the complicated calculations." - "The class materials were very interesting, the assignments help reinforce ideas learned."
- "HE included lots of coding assignments which I appreciated."
- "The lectures were well made, and having notes for the slides was very helpful."
- "Professor He is very invested in student success. Assignments are clear for the most part. Lectures and course outcomes are very
clear. He is always available to provide clarification or help in any other way." - "Suining He's office hours were very helpful in stimulating a learning enviornment."
- "Your passion for the subject matter was contagious, and it inspired me to work harder and strive for excellence. I appreciated your approachable and patient demeanor, which created a welcoming and supportive environment for us to learn and grow in."
- ...
- "Professor He is definitely one of the most caring professors I've had during my four years at UConn. He does everything in his
power to set students up for success. All assignments and deadlines are clearly communicated. Professor He always responded
immediately with relevant information. I especially appreciated the biweekly meetings and clearly defined assignments during
semester 1. Without the assignments, our team would have procrastinated the required writing and planning. By semester 2, I had
a much better understanding of what needed to be done and the discipline to keep projects on track. The biweekly meetings are a
perfect way of establishing accountability and offering help/guidance to the student group. Anything less than 2 weeks would be too
frequent to have any real progress to report. Anything more than 2 weeks would invite procrastination from the students. Keeping
projects on track was something I struggled a lot with (for past projects) before Professor He's guidance." - "Professor He is very responsive with emails and available pretty much whenever we need him. He explains things very well and
very encouraging as well." - "Dr. He was very open to communication. The weekly meetings seemed to have a point and helped guide us on track. He was
willing to join in on conference calls when he could and was always open to E–mails for more private discussion." - ...
- "The instructor gave a very thorough review of the many different research areas that are within the field of Urban Computing. The fact
that we had to do paper reviews now and then proved very beneficial for me. I learned how to approach a research problem and
experiment with different ideas." - "I thoroughly enjoyed the course. Of course, in–person would have probably been better, but you did a great job converting it into a
fully remote format." - "Be organized, enthusiastic, and willing to answer questions"
- "He gave a lot of examples and inspired us to learn."
- ...
Teaching Assistant (HKUST) and Student Mentor:
I worked as a Teaching Assistant in 5 semesters out of my 8 amazing semesters in HKUST, and helped mentor more than seven Final Year Projects (FYP) and Undergrad Research Opportunities Projects (UROP).
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