I enjoy catching up with family and friends outside of work, playing hockey or rollerblading, and hanging out with Jax (my dog) in the pool, occasionally cooking, traveling, skiing and learning. Recently, hot yoga has become a go-to, along with PiYo, Yin, and other activities! I am a sports fan who would rather play than watch (except for playoff hockey). I am a NEU and Boston sports fan all day!
I am passionate about applying technical skills and advancing pattern recognition, machine intelligence, and HCI technology to a better society, be it security, entertainment, automation, or even fair AI: the intersection of technology, engineering, and intelligence is where I thrive. My research focuses on machine learning, with visual signals to better understand what we see; automatic recognition software that can learn from data without human intervention; or intelligent goal ability for devices to make decisions about their environment. However, a signal is only any data point in the universe of all possible representations. Whether it's a 2D image or a 1D sound wave, it's still just a signal. Therefore, I preferred to use multimodal and sensor fusion, along with multitasking, multi-view and self-control, wherever possible. The more data, the more information, the better.
My experience encapsulates data analytics topics: having been awarded best undergraduate teacher at Northeastern University upon designing and teaching Comp. Methods for Data Analytics several semesters. I am a team player who takes the initiative when needed. I've worked in diverse groups over the years and love the challenge of bringing new ideas into our work culture, while still juggling everything else that comes with being part of a larger whole! My experience managing logistics and communication, measuring practical significance (i.e., success), writing research papers, and acquiring strong coding skills - all these things have helped me tremendously.
Upon receiving a Ph.D. (2020), Joseph P. Robinson joined Vicarious Surgical as an AI Engineer, advancing the critical AI components for the next generation of surgical robotics. Specifically, Dr. Robinson deployed state-of-the-art ML models to enhance the surgical ability in ways that minimize invasion and the time needed to recover.
As part of his dissertation, he focused on modern-day, data-driven modeling (i.e., deep networks) based on multimodal inputs. He has a B.S. in Electrical and Computer Engineering from Northeastern University (NEU) class of 2014; Dr. Robinson received his Ph.D. in Computer Engineering from NEU, working under the supervision of Yun Raymond Fu and alongside the others of SMILE Lab (class of 2020). As a graduate student, Dr. Robinson also served part-time faculty for several years, teaching Computational Methods for Data Analytics. (voted Best Teacher by students in his final year, 2019-2020). Check out the Research Page and about 40 of his publications with 500+ citations (Scholar). In addition, he has completed two NSF REUs (2010 & 2011); co-oped at Analogic Corporation (2012) & Raytheon BBN Technology; interned at MIT Lincoln Labs (2014), System & Technology Research (2016 & 2017), Snap Inc. (i.e., Snapchat) (2018), and ISMConnect (2019).
Dr. Robinson started his Ph.D. by leading the joint NEU-MIT Lincoln Labs team to their TRECVid debut (MED, placed 3rd of many). He also built numerous image & video-based datasets, most notably Families In the Wild (FIW), which has recently extended with multimedia (i.e., FIW-Multimedia, aka FIW-MM, audio, video, and audio-visual). Balanced Faces in the Wild (BFW) is another face-based labeled dataset to support biased research in facial recognition. His dissertation includes novel work in robust real-time facial recognition, deep learning, and human-computer interaction, emphasizing the social implications of integrating AI in day-to-day society. Nowadays, his focus is on scene-level knowledge of human organs, bringing assistance to surgeons inside the medical room. His particular interests are in exploring the social challenges of integrating computing into surgery – and how this will change the medical field, procedures, and practices in the coming years.
Specifically, Dr. Robinson has published in several journals, such as IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI) and Transactions on Multimedia (T-MM), among other top-tier journals. Dr. Robinson also has various conference papers spanning CVPR, ICCV, AAAI, AMFG, ACM MM, and several other renowned publications. Lots of service in the research community: served as the organizing chair and host of several workshops (e.g., NECV2017@ NEU, RFIW2017@ MM [proceedings], RFIW18, 19, 20, 21@FG, AMFG@ CVPR2018-2021, FacesMM @ ICME 2018 -2019), tutorials (ACM-MM18 [slides], FG19 [video], CVPR19), and data challenges (Kaggle, Codalab) at the conferences above and others! Dr. Robinson has a reputation for delivering effective peer reviews, shown in many papers he is assigned regularly, and in winning Best Student Reviewer for three consecutive years (2018, 2019, 2020); upon graduating, he earned Best Overall Review (2021). As part of this, Dr. Robinson served as a Program Committee (PC) member for many venues and years (e.g. CVPR, FG, MIRP, MMEDIA, AAAI, ICCV, ECCV, IJCAI, ACM MM, NIPS), and journal reviewer (e.g., IEEE Trans. on Biomedical Circuits and Systems, Image Processing, TPAMI, TIP). He also held several leadership positions, like the president of IEEE@NEU & Relations Officer of IEEE SAC R1 Region.
Selected Awards and Scholarships
Best Reviewer, IEEE AMFG Conference (2021).
Best Teacher, College of Engineering (2019-20).
Best Student Reviewer, IEEE AMFG Conference (3x, 2018-2020)
DHS ALERT Graduate Student Scholarship (2015-2018).
Best Poster (05/2014).
Huntington 100: the 100 most influential members of the NEU community (05/2014).
1𝑠𝑡 Place ECE Department Senior Capstone (05/2014).
1𝑠𝑡 Place ECE Freshman Remote Control Design Contest (05/2011).
Invest in Tomorrow's Engineering Leaders Scholarship (2011-14).