This award honors the memory of Tim Campbell, a CS PhD Student who was widely known for his innovative spirit, creativity, and cross-functional collaboration. This award is presented to a Computer Science or Electrical Engineering undergraduate or graduate student who demonstrates a spirit of innovation, collaboration, and creativity through her or his research and personal life. This award is funded by the Timothy B. Campbell Memorial Scholarship Foundation.
|Deadline to Nominate
|February 4, 2022 11:59PM (PST)
|Notification of Award
|May 4, 2022
Current applicants must be pursuing a degree in Computer Science or Electrical Engineering at the undergraduate or graduate level at UC Berkeley.
One award will be distributed each year in the amount of $2,000.
Nomination deadlines are handled by the Berkeley EECS department. You must be a faculty, student, or staff of the EECS department to nominate.
Compose a letter (approximately 1 page) for each nominee explaining your reason for recommending the student. Nominators should specifically address how the nominee meets the award criteria. Attach any relevant materials that will assist the Student Awards Committee in making their decision, such as: publications, CV, additional letters of nomination. The committee may seek additional information concerning the most promising nominees. Previous recipients of an award are ineligible to receive the same award again, but may be recommended for any remaining awards. Nominators are encouraged to refer to the description of each award, which includes a list of previous awardees.
Nomination deadlines are handled by the Berkeley EECS departmentSubmit a Nomination
Jennifer Grannen is a fourth-year undergraduate student majoring in Computer Science. She spends the majority of her free time researching robotic deformable object manipulation advised by Professor Ken Goldberg and in collaboration with Toyota Research Institute and Honda Research Institute. Over the past 2 years, she has published severalpapers in top robotics conferences in this area. She was accepted by UC Berkeley, MIT, and Stanford, and she will decide soon where she will undertake her PhD with an interest in learning.Jennifer is also deeply passionate about teaching and outreach.. She partners with campus student groups to expand outreach initiatives, including hosting robot demos and deep learning workshops for underrepresented middle and high school students. Jennifer teaches middle school girls Python and Scratch programming on weekends, and is enthusiastic about developing creative and effective teaching methods to share her love of research with others.
Brijen Thananjeyan is a 3rd year Computer Science PhD student advised by Professors Ken Goldberg and Joey Gonzalez. Brijen is interested in designing learning-based algorithms for robotics that effectively manage both the cost and quality of samples during data collection. To this end, Brijen’s projects span safe reinforcement learning, deformable manipulation, online optimization, human intervention,and surgical robotics, and he has an extensive publication record in both theoretical and applied problems in these areas. Brijen is also passionate about teaching, and simultaneously lectured full-time for two upper-divisioncomputer science courses, CS 188 (Intro to AI) and CS 189 (Intro to Machine Learning) in summer 2019. Each class had over a hundred students, and Brijen managed a staff of 4 TAs with a co-lecturer to run each course. Additionally, Brijen has served as a GSI for 5 semesters across 4 EE and CS courses.
Ashwin Balakrishna is a 3rd year Computer Science PhD student studying the relationships and tradeoffs between different approaches for specifying behaviors for autonomous robotic agents. In the process, Ashwin has had the opportunity to collaborate with a large number of researchers from 5 different labs within Berkeley and 4 external institutions. These collaborations have allowed him to synthesize ideas from a number of different fields such as robotics, control theory, machine learning, and computer vision to design a number of novel algorithms which can efficiently and safely learn new tasks using a variety of different modes of specifications, such as demonstrations, interventions, corrections, preferences, data-driven priors, and constraints. Outside of research, Ashwin enjoys thinking about developing creative ways to explain scientific ideas to promising young scientists in the context of volunteering in the community and mentoring undergraduate students/early stage graduate researchers.
Priya Sundaresan is an EECS 5th Year Master’s student interested in robot learning with medical, home, and industrial applications in mind. Priya has studied robotic surgical automation, fabric/laundry folding, and cable manipulation in the past 3 years. In collaboration with other Berkeley labs and industry sponsors, her work has resulted in several publications atrobotics conferences. Priya was also accepted by UC Berkeley, MIT, and Stanford, and she will decide soon where she will undertake her PhD to focus on fine-grained robotic manipulation andperception in the real world by leveraging multisensory learning and human demonstrations. Outside of research, Priya enjoys teaching and mentorship. She recently began advising an undergraduate working on cable untangling.. Priya has also led lab-wide and department-wide (both EECS and BioE) lab tours for visiting middle/high school students
Varda Shrivastava is an undergraduate Computer Science major at UC Berkeley.
Andrew Head is a Ph.D. Candidate in Computer Science at UC Berkeley advised by Björn Hartmann and Marti Hearst. He researches how intelligent interfaces can help programmers share expertise—through code examples, tutorials, teacher feedback, and notebooks. He has also studied developer tool design as an intern at Microsoft Research and Google. His work is supported by an NDSEG Fellowship, and has received best paper awards and nominations at top conferences like CHI. Andrew had the opportunity to meet Tim and Cesar at the 2014 Cal visit days the two put on together.
Ahn Geun Ho is an undergrad studying Electrical Engineering and Computer Sciences at UC Berkeley. His nominating professor stated, “Geun Ho has proven himself to be a very creative and driven researcher. Although still an undergrad, he made two important research findings...He demonstrated that he can control strain in the grown monolayer semiconductors by relying on the mismatch between the coefficient of thermal expansion of the monolayer and substrate. Second, he demonstrated that by properly growing and relaxing the monolayers, he can achieve a high photoluminescence quantum yield of up to 30%. I sometimes forget that he is an undergrad!” This notable research within the context of his undergraduate studies reminded us all of Tim’s enthusiastic start at the University of Washington.
Tomás Vega Galvez innovates as an undergraduate much the same as Tim did in the labs. Eric Paulos shares Mr. Galvez is “one of the most dedicated and creative students” especially in Critical Making course work. Tomás said, “I plan to focus on heading back to Peru in order to improve the communities in which I was raised.” Tomás recently started the Masters Program at the MIT Media Lab.
Joanne Lo is the founder of Elysian Labs, Inc and an alumna of the Human-Computer Interaction - Electrical Engineering PhD program at UC Berkeley. She was advised by Professor Paulos to develop simple yet creative fabrications methods for the Maker's community. Joanne received her B.S. degree in Biomedical Engineering and M.S. degree in Electrical Engineering from UC Davis.,