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Eleven new faculty join the Jacobs School faculty in fall 2024

Learn more about these new hires in our New Faculty PDF.

September 17, 2024-- The Â鶹´«Ã½ Jacobs School of Engineering is welcoming 11 incredible new faculty to its ranks in fall 2024. They join a group of nearly 300 faculty, 175 of whom have been hired in the last 11 years, dedicated to tackling humanity’s toughest challenges through a combination of technical excellence, clear-eyed determination, creativity, and discipline-bridging innovation.

“Please join me in welcoming our newest cohort of faculty to the Jacobs School of Engineering.  Our extraordinary community of innovators continues to strengthen,” said Albert P. Pisano, Dean of the Â鶹´«Ã½ Jacobs School of Engineering and Special Advisor to the Chancellor. “As engineering dean, I feel that it is my job to ensure that our new faculty have higher impact careers here at the Jacobs School of Engineering than they would have anywhere else. In order to make this a reality, our entire community must come together to fully empower our new faculty.”

In fact, Jacobs School new faculty are empowered to “go for it” from day one, pursuing bold research ideas with support from the Jacobs School and the broader Â鶹´«Ã½ research ecosystem, explained Pisano in his new faculty-welcome column.

The Jacobs School of Engineering ranks the #11 best in the nation in the U.S. News & World Report Rankings of Best Engineering Schools. The Jacobs School also ranks #1 in the nation among public engineering schools for citations per publication. 

This academic year's new faculty to the Jacobs School are, in alphabetical order:

 

Prithviraj Ammanabrolu, Computer Science and Engineering

Assistant Professor

Ammanabrolu works to create trustworthy and responsible language-based AI agents that can align to human preferences after getting feedback, and can use neurosymbolic world models to guide their actions in grounded environments. He aims to imbue these agents with the ability to understand and generate contextually relevant natural language.

Previously: Postdoctoral Researcher, Mosaic and Allen Institute for AI

Ph.D. Georgia Tech

 

Trevor Bonjour, Computer Science and Engineering

Assistant Teaching Professor
Bonjour’s work focuses on AI and AI education, with interests in machine learning, reinforcement learning, and causal inference. His current research focuses on developing reinforcement learning techniques for adaptive agents in novel, multi-agent environments. He also works on creating evidence-based approaches to enhance student learning of complex AI concepts.

Previously: Ph.D. Student, Purdue University

Ph.D. Purdue University

 

Erika Cyphert, Bioengineering

Assistant Professor

Cyphert’s research lies at the intersection of polymer chemistry, drug delivery, microbiology, the microbiome and bioinformatics. Her lab engineers responsive carriers for therapies to target microbiota communities and address diseases that are associated with microbiota composition (GI disorders, infectious diseases, cancer, bacterial vaginosis).

Previously: Postdoctoral Researcher, Cornell U and UC San Francisco

Ph.D. Case Western Reserve University

 

Loris D’Antoni, Computer Science and Engineering

Associate Professor

D’Antoni focuses on helping people write software they can trust. His research combines formal techniques and machine learning approaches to generate computer programs that match human intents and to help people understand what the software they wrote does. His work has been applied to decision making software, network configurations, and personalized education.

Previously: Assoc Professor, University of Wisconsin - Madison, and Visiting Academic, AWS

Ph.D. University of Pennsylvania

 

Nuria Gonzalez-Prelcic, Electrical and Computer Engineering

Professor

Gonzalez-Prelcic works in signal processing and machine learning for wireless communication and sensing. She develops next-generation cellular and WiFi systems that exploit multiple antenna transceivers to increase data rate and provide high accuracy localization and sensing information, with applications in automated vehicles, robotics and smart homes.

Previously: Associate Professor, North Carolina State University

Ph.D. Universidade de Vigo, Spain

 

Robert Heath, Electrical and Computer Engineering

Professor, Charles Lee Powell Chair in Wireless Communications

Heath specializes in the intersection of communication theory, signal processing and information theory. His research is centered on multiple-input multiple-output (MIMO) wireless communication systems that leverage multiple antennas. His work has significant applications in both commercial and defense-related wireless communication systems.Previously: Lampe Distinguished Professor, North Carolina State University

Ph.D. Stanford University

 

Deepak Kumar, Computer Science and Engineering

Assistant Professor

Kumar’s research focuses on sociotechnical cybersecurity—an area of security dealing with threats at the interface of society and technology. Threats include online harassment and abuse, and mis/disinformation–and more. He measures how these threats spread online and proposes new defenses, tools, and interventions to keep Internet users safe from unwanted harms.

Previously: Postdoctoral Researcher, Stanford University

Ph.D. University of Illinois at Urbana-Champaign

 

Jennifer Mullin, Mechanical and Aerospace Engineering

Associate Teaching Professor

Mullin focuses on engineering education research and curriculum development with an emphasis on creativity, design thinking and project-based pedagogy. Her work at the intersection of engineering design, technical communication and problem-solving utilizes informed instructional choices through a “learn-by-doing” approach to enhance and enrich the undergraduate educational experience.

Previously: Associate Professor of Teaching, UC Davis

Ph.D. Virginia Tech

 

Rahul Parhi, Electrical and Computer Engineering

Assistant Professor

Parhi’s research lies at the interface between signal processing, machine learning and statistics to develop a mathematical theory of deep learning. His work aims to provide a rigorous theoretical foundation for understanding the remarkable performance of deep learning models that underlie most state-of-the-art AI methods.

Previously: Postdoc Researcher, École Polytechnique Fédérale de Lausanne

Ph.D. University of Wisconsin-Madison

 

Lianhui Qin, Computer Science and Engineering

Assistant Professor

Qin works on natural language processing and machine learning. She focuses on machine reasoning and generation; understanding and improving large language/multi-modal models and AI/LLM for science, engineering, health, including reasoning for chemistry, weather/ climate, healthcare, and control engineering.

Previously: Ph.D, student, Univeristy of Washington

Ph.D. University of Washington

 

Noah Rubin, Electrical and Computer Engineering

Assistant Professor

Rubin’s work in the field of nanophotonics focuses on developing innovative components that control light using structures as small as its wavelength. Focused on manipulating light’s polarization state, his research aims to create new types of optics and optical systems with wide-ranging applications, including advancements in astronomy, sensing and beyond.

Previously: Postdoctoral Researcher, Harvard University

Ph.D. Harvard University

 

Media Contacts

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Daniel Kane
Jacobs School of Engineering
858-534-3262
dbkane@ucsd.edu