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Samuel D. Conte Distinguished Lecture Series

Samuel D. Conte (1917-2002) founded the Department of Computer Science at Purdue University in 1962. His vision and active involvement nationally and internationally played a vital role in defining the discipline of computer science worldwide. 

Each year, the Department of Computer Science faculty identify computer scientists who are recognized as leaders in the field and whose ideas and research command the attention of the students and faculty.  A select group of individuals are then invited to be a part of the annual Samuel D. Conte Distinguished Lecture Series on Computer Science.

In 1993, the Samuel D. Conte Endowment was established to honor Professor Emeritus Conte and his devotion to excellence in teaching and research in computer science. The Samuel D. Conte Lecture Series, sponsored by the endowment, serves as a permanent testimonial of his contributions to the Department of Computer Science, Purdue University, and the computing field.

Professor Somesh Jha

Professor Somesh Jha

Tuesday, September 5, 2023
10:30 am
Virtual option:
MeetingID: 986 8245 1267


Trustworthy Machine Learning and the Security Mindset


Fueled by massive amounts of data, models produced by machine-learning (ML) algorithms, especially deep neural networks (DNNs), are being used in diverse domains where trustworthiness is a concern, including automotive systems, finance, healthcare, natural language processing, and malware detection. Of particular concern is the use of ML algorithms in cyber-physical systems (CPS), such as self-driving cars and aviation, where an adversary can cause serious consequences. Interest in this area of research has simply exploded. In this work, we will emphasize the need for a security mindset in trustworthy machine learning, and then cover some lessons learned. Large Language Models (LLMs) as been a paradigm shift and towards the end we will touch on the subject of trustworthiness in the context of LLMs.



Somesh Jha received his B.Tech from Indian Institute of Technology, New Delhi in Electrical Engineering. He received his Ph.D. in Computer Science from Carnegie Mellon University under the supervision of Prof. Edmund Clarke (a Turing award winner). Currently, Somesh Jha is the Lubar Professor in the Computer Sciences Department at the University of Wisconsin (Madison). His work focuses on analysis of security protocols, survivability analysis, intrusion detection, formal methods for security, and analyzing malicious code. Recently, he has focused his interest on privacy and adversarial ML (AML). Somesh Jha has published several articles in highly-refereed conferences and prominent journals. He has won numerous best-paper and distinguished-paper awards. Prof. Jha received the CAV award for his work on CEGAR and also has received the IIT-Delhi Distinguished Alumni award. Prof. Jha is the fellow of the ACM, IEEE, and AAAS.


Raytheon Professor, Computer Science & Engineering: Robin Murphy

Raytheon Professor, Computer Science & Engineering: Robin Murphy

Robin Murphy

March 28, 2024 at 2:30pm

LWSN 3102 AB (In-person only)

Reception to follow in LWSN Commons.



Robots (and Research) to the Rescue



Ground, aerial, and marine robots are increasingly used by responders to save lives, mitigate ongoing threats, and accelerate economic recovery. The recent Surfside condo collapse and Hurricane Ian are two examples of the extreme environments that robots, and their operators, must function in. Clearly, rescue robots have great societal benefit; however our work at these two disasters illustrate why disaster robotics is important to robotics research in general. One reason is that research in the field at a disaster informs the virtuous research cycle, guiding both fundamental and convergent research. The use of robots at a disaster provides a “canary in the coal mine” indication of gaps in hardware, software, and human-robot interaction that might take years to discover through hypothesis-driven laboratory testing. The use of drones at the Surfside collapse has led to fundamental research in reconstructing voids using photogrammetry.  Hurricane Ian showed that drone pilots by the end of the second day of the response were showing fatigue and cognitive deficits equivalent to being legally drunk in most states. Surprisingly, the fatigue did not lead to aviation errors, possibly because of the robustness and automation of the drones being used, but squads made significant errors in collecting the imagery needed by incident command. Hurricane Ian has produced advances in computer vision and machine learning, including new schemas for coding, identifying alignment errors, and producing a massive labeled open-source dataset. A second reason why disaster robotics is valuable is that it, by necessity, is pioneering domain-inspired, interdisciplinary synthesis, which in turns calls for new pedagogical approaches for educating the next generation of scientists.



Robin Roberson Murphy

Dr. Robin R. Murphy, Ph.D. (’92) and M.S. (‘89) in computer science and B.M.E. (‘80) from the Georgia Institute of Technology,  is the Raytheon Professor of Computer Science and Engineering at Texas A&M University and a director of the Center for Robot-Assisted Search and Rescue. Her research focuses on artificial intelligence, robotics, and human-robot interaction for emergency management. She is an AAAS, ACM, and IEEE Fellow, a TED speaker, and author of over 400 papers and four books including the award-winning Disaster Robotics which captures much of her research deploying ground, aerial, and marine robots to over 30 disasters in five countries including the 9/11 World Trade Center, Fukushima, Hurricane Harvey, and the Surfside collapse. Her contributions to robotics have been recognized with the ACM Eugene L. Lawler Award for Humanitarian Contributions and a US Air Force Exemplary Civilian Service Award medal.  Dr. Murphy has served on numerous professional and government boards, including the Defense Science Board and National Science Foundation, as well as the AI for the Benefit of Humanity prize committee.

Last Updated: Mar 21, 2024 4:33 PM

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