Rice University associate professor Xia (Ben) Hu does not count his accomplishments in terms of his h-index, although 64 of his more than 100 research papers have been cited at least 64 times. Instead, he points to the accomplishments of his proteges. Four of his Ph.D. students graduated and accepted roles at prestigious companies or academic institutions in 2023, just two years after Hu joined the ranks of Rice’s computer science faculty.
Airbnb ML Engineer Daochen Zha
Daochen Zha was drawn to Airbnb’s unique ability to connect hosts and guests in a meaningful way. He said, “Leveraging machine learning to enhance this connection is both challenging and impactful. Additionally, I admire Airbnb's collaborative culture, which provides an ideal environment for tackling complex problems.”
He said his time at Rice played a pivotal role in his preparation to transition from academia to industry as an ML engineer. “The research and development experience I gained in my lab provided a strong foundation in machine learning principles. Additionally, Rice's reputation helped me secure internships at FAANG companies, which further refined my skills. While the transition involved some adjustments, many of the skills and concepts I learned at Rice were directly applicable to my industry role. The critical thinking, teamwork, and analytical mindset fostered at Rice continue to be invaluable assets in my career,” said Zha.
The thrill of discovery he experienced in Hu’s lab continues for Zha at Airbnb, where he said the research opportunities that excite him most stem from the direct impact they can have on Airbnb’s product and users.
“Unlike academic research, where the impact might be more theoretical or conceptual, at Airbnb, the technologies and solutions we develop can directly translate into features that improve the experience for hosts and guests,” Zha said. “For instance, I'm currently focused on application-driven and product-driven research, aiming to create solutions that help guests discover their ideal Airbnb listings and assist hosts in finding the right guests. It's a win-win situation that can have a meaningful impact on a large number of people. This practical and tangible aspect of research is particularly inspiring and rewarding.”
Apple ML Engineer Kwei-Herng (Henry) Lai
“Apple is one of the largest tech companies, boasting an enormous user base and significant computational resources,” said Kwei-Herng (Henry) Lai. “The data from Apple is invaluable, providing opportunities for me to recognize the value that my research and development could bring to the world, influencing the company's strategies and enhancing users' daily lives.
“While I can't disclose specific consumer applications, what truly excites me is validating the effectiveness of academic research papers in diverse business scenarios. Identifying potential enhancements to align academic findings more closely with industrial applications and recognizing their limitations is a particularly stimulating aspect. Working at Apple exposes me to novel problems rarely observed in academic papers, providing an exhilarating opportunity for exploration.”
Lai said working with Hu on multiple industry collaboration projects had a significant and positive impact on his transition to Apple. His collaborations with Hu helped Lai gain business know-how regarding industry positions and he learned about working patterns and deliverables beyond publishing papers.
“But working at Apple is also quite different from my experiences in Ben's lab,” said Lai. “I am still conducting research and development on challenging problems, but quite a bit of my time is spent communicating with cross-functional teammates and explaining complex ML concepts with intuitive ideas to better facilitate the adoption of newly developed ML techniques.
“Furthermore, assessing the success of a project is no longer solely dependent on publishing papers in top venues or citations. Instead, it hinges on factors such as the adoption rate within cross-functional teams and economic impacts, such as revenue gains and cost reductions.”
MIT postdoc & NC State Assistant Professor Kaixiong Zhou
For Kaixiong Zhou, the opportunity to work as a postdoctoral researcher with MIT’s James Collins on drug discovery and synthetic biology felt like a natural extension of his work with Hu. He said, “Advancing the frontiers of graph machine learning and extending it to science problems will be my main focus in the coming years. Collin’s lab has made significant progress in drug discovery, and North Carolina State University is well-reputed in engineering innovative research. I believe the research experience from DATA Lab at Rice and Collins’ lab will facilitate my future exploration.”
He has been working in building up language models and graph neural networks to predict the properties of drug molecules. “I benefited a lot from the Ph.D. research experience from DATA Lab led by Dr. Hu, where the daily work is similar to my current postdoctoral job. I analyzed the research problem, summarized the existing work, and designed the novel machine learning algorithms for bioinformatic applications. The research critical thinking is in the same strain.”
He has worked with research interns and plans to engage with several graduate students starting from 2024 Fall. “I will work hands-on with the junior Ph.D. students, and let them develop the good research tastes and the first publication quickly. This monitoring style is motivated by our DATA Lab, where most of the Ph.D. students step on the right research track under the close supervision of Dr. Hu. For the senior students, I will give them sufficient freedom to think about their research interests and the next career stage, and then provide my highest support.”
Working with Hu at Rice, Zhou co-authored over 25 research papers with impacts. One of his 2022 papers with Hu and their collaborators at LinkedIn, Samsung, and the Hong Kong Polytechnic University has been cited 139 times in its first year of publication. In addition to his own research, Zhou mentored undergraduate students in the Hu DATA lab and completed industry internships with Samsung Research America, Visa and Google.
Wake Forest Assistant Professor Fan Yang
“I am a firm believer in liberal arts education and have always believed that it should be the ultimate form of education and, over a long time scale, the best choice. Wake Forest University is one of the schools I have long admired, and its educational philosophy aligns very closely with my own thoughts. This is probably the most important reason for my choice of Wake,” said Fan Yang, an assistant professor in the computer science department.
He also looks forward to collaborations with colleagues in Wake Forest's medical school. Yang said, “Our school of medicine is renowned for its robust research teams and laboratories, many of which are closely aligning with the Explainable Artificial Intelligence (XAI) techniques I focused on throughout my Ph.D. My keen interest in applying research to socially impactful and high-stakes fields, like healthcare, dovetails seamlessly with Wake Forest's research strengths.”
Yang’s ability to secure a tenure-track faculty position immediately upon the culmination of his degree was directly related to two critical aspects of his mentor’s style of collaborating with his Ph.D. students. He said, “On one hand, it's the high-quality training in teaching and research that I received from Dr. Hu over the past few years. Whether as a guest lecturer or participating in course tutorials, these activities have thoroughly honed my teaching abilities, allowing me to easily handle my current daily teaching tasks.
“Additionally, I have been deeply involved in the application process for NSF research grants multiple times, which greatly enhanced my experience in project applications. These experiences are often only gained through postdoctoral experiences, so for me personally, the growth has been significant.”
He also credits his success to a unique interdisciplinary training initiative, the Rice Future Faculty Fellow (FFF) program. Yang was nominated and admitted to the program in 2022 as one of that year’s cohort of 10 Ph.D. and postdoctoral researchers. He said the committee of mentors and coaches provided him with a lot of help and valuable suggestions throughout his job hunt.
‘Stay curious,’ advises Hu
Hu is pleased that each of his recent alumni found the roles and organizations that best match their individual interests and priorities. He expects the research curiosity they expressed as Ph.D. students will continue serving as a catalyst in their careers and he advocates for the perspective of a marathoner as opposed to a sprinter.
“Be curious about the things you are working on and enjoy the process,” Hu advises both his alumni and his students. “But approach the journey in a slow and steady manner, and never give up.”