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Vipul GoyalView profile

Associate Professor

• Cryptography
• Quantum Cryptography
• Security & Privacy
• +6 more

Vipul Goyal is an Associate Professor in the Computer Science Department at Carnegie Mellon University and a Senior Scientist at NTT Research . He previously spent 7 years at Microsoft Research before joining CMU. His academic journey includes a PhD from UCLA under advisors Rafi Ostrovsky and Amit Sahai , and a B.Tech. from IIT (BHU) Varanasi . Research Interests: Cryptography, Quantum Cryptography, Security & Privacy, Theoretical Computer Science Grants: NSF, DARPA, Department of Energy NETL, JP Morgan, Cisco, PNC, Ripple, DoS Networks, CyLab initiatives Education: PhD in Computer Science (UCLA, 2009) B.Tech. in Computer Science (IIT BHU Varanasi) His recent work focuses on Quantum Cryptography , Secure Multi-Party Computation , and Unclonable Security . Notable awards include the 2019 JP Morgan Faculty Award and the 2016 ACM CCS Test of Time Award . He advises the CMU Blockchain Group and has served on program committees for Crypto 2025 , FOCS 2024 , and others. Scientific Awards: 2019 JP Morgan Faculty Award 2016 ACM CCS Test of Time Award Microsoft Research Graduate Fellowship Google Outstanding Graduate Student Award Forbes 30 Under 30 in Science and Healthcare (2013) Students & Postdocs: He has mentored numerous PhD students and Postdocs , many of whom are now faculty at institutions like Tsinghua University, Max Planck Institute, and UT Austin. Former research assistants include Yifan Song and Elisa Masserova .

• Combinatorial Optimization
• Distributed and Parallel Computing
• Coding Theory
• +4 more

Bernhard Haeupler is a Professor at INSAIT (Institute for Computer Science, Artificial Intelligence and Technology) under Sofia University "St. Kliment Ohridski" since 2024. He is also a Post-Professor and Researcher at ETH Zurich 's Computer Science Department since 2020 and an Adjunct Professor at Carnegie Mellon University 's Computer Science Department since 2022. His roles span theoretical computer science, algorithm design, and distributed/parallel systems. Research Interests : Haeupler focuses on algorithms for combinatorial optimization, distributed and parallel computing, coding theory, graph/network algorithms, and information theory. His work bridges theoretical foundations with practical applications in network resilience, synchronization, and quantum/parallel optimization. Article Trends : His 15 most recent articles (2023-2025) emphasize distributed algorithms (e.g., dynamic routing, fault-tolerant spanners), parallel computing (e.g., low-congestion shortcuts, near-linear work), and coding theory (e.g., synchronization strings, insertion-deletion codes). Topics include graph theory , network design , and quantum shortest paths . Scientific Awards : ERC Starting Grant (2020) Sloan Research Fellow (2019) NSF CAREER Award (2018) ACM-EATCS Doctoral Dissertation Award (2014) George Sprowls Award for MIT PhD Thesis Advising & Grants : Haeupler has advised eight PhD students, including Jason Li (CMU, now at Google Research Zurich) and Nicolas Resch (University of Amsterdam). He has secured multiple NSF grants for projects like Distributed Optimization Beyond Worst-Case Topologies and New Coding Techniques for Synchronization Errors .

Kanat TangwongsanView profile

Researcher

• Algorithms
• Parallel Computing
• Streaming Algorithms
• +6 more

Kanat Tangwongsan is a researcher and educator in computer science, with a PhD from Carnegie Mellon University and prior roles at IBM T.J. Watson Research Center. He has extensive experience in algorithm design, parallel computing, and self-adjusting computation, with publications in top-tier venues like DEBS, ICDE, SPAA, and TOCS. Education: PhD in Computer Science (Carnegie Mellon University), B.S. in Computer Science and Mathematics (Carnegie Mellon University) Research Interests: His work spans algorithms , parallel computing , streaming data structures , and self-adjusting programs , focusing on theoretical improvements and practical implementations for graph problems, convex hulls, and network design. Article Trends: His publications emphasize low-latency streaming , parallel SDD solvers , k-means clustering , and triangle enumeration , with applications in large-scale graph analysis, numerical systems, and cache-oblivious methods. Advising and Collaborations: He has collaborated with prominent researchers like Guy E. Blelloch, Martin Hirzel, and Anupam Gupta, contributing to open-source algorithm frameworks and educational materials.

• Wireless Systems
• Satellite Networks
• Artificial Intelligence
• +3 more

Jingxian Wang is an NUS Presidential Young Professor in the Department of Computer Science at the National University of Singapore (NUS). He leads research in next-generation wireless systems, satellite networks, and AI-driven applications. Previously, he was a Research Scientist at Microsoft Research in Redmond, where he initiated the Smart Surface for 6G and Space project. He holds a Ph.D. from Carnegie Mellon University. His research spans wireless communication, backscatter technology, RFID systems, and soft robotics, with emphasis on low-latency networks and energy-efficient solutions. Work includes satellite traffic engineering, AI-enhanced LoRa reception, and wireless actuation for electronics-free robots. Publications demonstrate consistent focus on wireless innovation, with trends toward satellite networks (2025), generative AI in communication (2024), and soft robotics (2023). Earlier work established foundations in RFID and material sensing. Awards & Honors: ACM SIGMOBILE Doctoral Dissertation Award Microsoft Research Fellowship Emerging Rockstar in IEEE Pervasive Computing Best Paper Awards (UbiComp, IPSN, IJCAI) Research Highlights in ACM Communications (3×) and SIGMOBILE Team & Advising: He leads PhD students (Jinfan Liu, Kin Whye Chew, Jiahao Xu) and post-docs (Yijie Li, Zehua Sun), supported by initiatives like Microsoft's Accelerating Foundation Models program. The lab focuses on wireless systems, AI, and satellite networks.

Todd C. MowryView profile

Professor

• Computer Architecture
• Compiler Optimization
• Operating Systems
• +6 more

Todd C. Mowry is a Professor in the Computer Science Department at Carnegie Mellon University. His work focuses on computer systems design across multiple domains, including hardware architecture, compiler optimization, operating systems, and database performance. He explores techniques for parallel processing, memory management, and efficient execution of machine learning workloads.

Aditi RaghunathanView profile

Assistant Professor

• Machine Learning
• AI Safety
• Reliability of Large Language Models
• +7 more

Aditi Raghunathan is an Assistant Professor in the Computer Science Department at Carnegie Mellon University , with affiliations to the Machine Learning Department . She holds a PhD from Stanford University (2021) , advised by Percy Liang , and a B.Tech in Computer Science from IIT Madras (2016) . Her research focuses on advancing the scientific understanding of frontier models , addressing their reliability, safety, and unlearning challenges. Education PhD, Stanford University (2021) B.Tech, IIT Madras (2016) Research Themes Overtraining effects in LLMs Memorization sinks for unlearning Algorithmic creativity beyond next-token prediction Scalable frameworks for AI safety Her work at ICML 2025 revealed critical limitations in LLM pre-training, including catastrophic overtraining and imperfect unlearning due to entangled memorization-generalization circuits. She has developed seed-conditioning and multi-token learning to enhance structured diversity and creativity in models. Scientific Recognition includes: NSF CAREER Award Arthur Samuel Best Thesis Award at Stanford Google Research Scholar Forbes 30 Under 30 in Science She supervises PhD and Master’s students such as Jacob Mitchell Springer , Christina Baek , and Taeyoun Kim , and actively collaborates with CMU graduate students. Her teaching includes courses on Trustworthy AI and Graduate Artificial Intelligence .

• Distributed Systems
• Network Architectures
• Fault Diagnosis
• +3 more

Ronald Bianchini is an Adjunct Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University’s College of Engineering. His research focuses on Distributed Systems and Network Architectures, addressing challenges in peer-to-peer coordination, fault diagnosis in distributed systems, and scalable high-performance networks. He is affiliated with the university’s Department of Electrical and Computer Engineering. Education: PhD in Electrical and Computer Engineering, Carnegie Mellon University (1989) MS in Electrical Engineering and Computer Engineering, Carnegie Mellon University (1986) BS in Electrical Engineering, Massachusetts Institute of Technology (1983) Research Interests: His work includes developing algorithms for distributed system diagnosis, such as the Distributed System Monitor (DSM) leveraging SNMP for network monitoring. Additionally, he contributed to the Tera switch architecture for Asynchronous Transfer Mode (ATM) networks, emphasizing robust performance under varying traffic conditions and scalability for large networks. Awards & Grants: No specific awards or grants are mentioned in the provided text. Labs & Teams: His research involves collaborations on projects like the DSM and Tera switch, though specific lab affiliations are not detailed.

Bob IannucciView profile

Adjunct Professor

• Mobile and embedded computing
• Scalable systems
• Sensor networks
• +11 more

Bob Iannucci is an Adjunct Professor in Electrical and Computer Engineering at Carnegie Mellon University (CMU), with a courtesy appointment at CMU Silicon Valley. He previously served as Chief Technology Officer of Nokia and Head of the Nokia Research Center (NRC), where he pioneered open innovation initiatives like 'lablets' at top universities. His research focuses on mobile/embedded systems, scalable architectures, wireless networks, and energy-efficient IoT technologies. Education: Ph.D. in Computer Science from MIT (1988), with a thesis on hybrid dataflow-von Neumann architectures. He has led engineering teams at startups and major firms like DEC/Compaq, co-founding Exa Corporation (now part of Siemens) for computational fluid dynamics. Key Projects: MoCCA (mobile computing architecture, now in Smithsonian), VIPER (drone curiosity training), PowerDué (energy-aware IoT prototyping). Awards: IDEA Gold Award (MoCCA), IPSN Best Paper (2018), Millennium Technology Prize committee member (2008). Current activities include advising on wireless networking, developing WiFi IoT devices, and an award-winning radio direction-finding iPhone app. He actively collaborates on NSF-funded projects addressing spectrum interference and emergency communication systems.

Pradeep K. KhoslaView profile

Adjunct Professor

• Electrical Engineering
• Computer Engineering
• Robotics
• +4 more

Pradeep K. Khosla serves as the eighth Chancellor of the University of California, San Diego (UCSD), a position he has held since August 1, 2012, while maintaining an adjunct faculty appointment in Electrical and Computer Engineering. As Chancellor, he leads a campus with over 45,000 students across 11 academic schools and eight undergraduate colleges, with annual revenues of $9.1 billion in fiscal year 2024. UCSD, home to the Scripps Institution of Oceanography and UCSD Health System, attracts more than $1.73 billion in sponsored research funding annually. Prior to UCSD, Khosla spent most of his career at Carnegie Mellon University, rising from Assistant Professor in 1986 to Dean of the College of Engineering in 2004. His academic foundation includes a BTech from Indian Institute of Technology Kharagpur (1980), followed by MS (1984) and PhD (1986) degrees in Electrical and Computer Engineering from Carnegie Mellon. Chancellor Khosla's research expertise centers on electrical and computer engineering with emphasis on robotics and intelligent systems. His work focuses on developing enabling technologies for 'Rapidly Deployable Systems' through composition of hardware/software building blocks and collaboration among autonomous robots. His research vision involves creating specialized components that rapidly form systems capable of achieving desired behaviors through collaboration. Dr. Khosla has received numerous prestigious awards recognizing his leadership and academic contributions: 2012 Light of India Award Lifetime Achievement Award from ASME George Westinghouse Award for engineering education W. Wallace McDowell Award from IEEE Apolitical's 100 Most Influential Academics (2022) SiliconIndia Leadership Award He maintains significant professional affiliations as an elected member of the American Academy of Arts and Sciences, National Academy of Engineering, and American Society for Engineering Education. Additionally, he holds fellowships with IEEE, ASME, AAAS, AAAI, Indian National Academy of Engineering, National Academy of Inventors, and Indian National Science Academy.

• Cloud Computing
• Resource Management
• Software-Defined Infrastructure
• +3 more

Akkarit Sangpetch is an Adjunct Professor in the Department of Electrical and Computer Engineering at King Mongkut's Institute of Technology (KMITL), and also serves as a Lecturer in the same department. He holds a Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University (2013), and previously worked at VMware, Inc. during his academic training. His primary research focuses on cloud computing resource management, software-defined infrastructure, and distributed application platforms. These areas emphasize optimizing computational resources and infrastructure efficiency in dynamic environments. No scientific awards or specific grants are explicitly mentioned. He has not listed any advisee students in the provided information. His professional activities include contributions to curriculum development and academic advising within the department. Further details about his involvement in research labs or collaborative teams are not detailed in the text.

Reeja JayanView profile

Professor

• Materials Science
• Electromagnetic Field Applications
• Energy Storage Systems
• +6 more

Reeja Jayan is a Professor in Mechanical Engineering at Carnegie Mellon University (CMU), with courtesy appointments in Materials Science & Engineering, Chemical Engineering, and Electrical & Computer Engineering. She leads the Far-from-Equilibrium Materials Laboratory (J-Lab), focusing on electromagnetic field-driven material synthesis and energy-efficient manufacturing. Her research spans ceramics, polymers, and energy storage systems, with breakthroughs in low-temperature material processing and data-driven discovery. Jayan holds prestigious awards including the ARO and AFOSR Young Investigator Awards, and is a CMU Engineering Dean’s Early Career Fellow. She pioneered game-based learning using Minecraft to teach materials science. J-Lab’s work includes additive manufacturing of ceramics, field-assisted synthesis, and autonomous robotic platforms for materials engineering. Jayan advises a dynamic team of graduate and undergraduate students, with notable alumni in academia and industry. Education: M.S. in Electrical Engineering, The University of Texas at Austin Ph.D. in Materials Science and Engineering, The University of Texas at Austin Postdoctoral Associate in Chemical Engineering, MIT Research Interests: Materials synthesized under electromagnetic fields, far-from-equilibrium processing, additive manufacturing of ceramics, energy storage systems, and data-driven autonomous synthesis. J-Lab’s work merges experiments with computational models to explore novel material behaviors and sustainable manufacturing techniques. Key thrusts include low-temperature ceramic synthesis, field-induced phase transitions, and machine learning-guided robotics for materials discovery. Publications: Over 50 peer-reviewed articles in top journals like Advanced Materials and Journal of the American Ceramic Society , focusing on electromagnetic field applications, battery interfaces, and ceramic processing innovations. Grants & Awards: NSF CAREER Award (2018) CMU Scott Institute Seed Grant (2020) Air Force Research Lab (AFRL) Center of Excellence funding Labs & Teams: J-Lab collaborates with industry and national labs, including the AFRL and NIST. Projects include developing closed-loop robotic systems for materials synthesis and low-emission ceramic manufacturing processes.

• Physical Metallurgy
• Magnetic Materials
• Phase Transformations
• +4 more

David Laughlin is a Professor of Materials Science and Engineering at Carnegie Mellon University (CMU), holding a courtesy appointment in the Electrical and Computer Engineering Department. He also serves as the ALCOA Professor of Physical Metallurgy and Editor of Metallurgical and Materials Transactions . With a PhD from MIT (1973) and BS from Drexel University (1969), his research focuses on phase transformations, magnetic materials, and transmission electron microscopy (TEM) analysis of microstructures. Notable contributions include studies on FePt alloys, boron nitride interfaces, and heat-assisted magnetic recording (HAMR) media. He has authored over 400 publications and five co-edited books, with awards including the G. T. Ladd Teaching Award (1975), B. R. Teare Award (1999), and the 2003 College of Engineering Outstanding Research Award. His work bridges metallurgy, materials science, and engineering applications, emphasizing practical solutions for advanced materials systems. Education: PhD in Metallurgy & Materials Science (MIT, 1973), BS in Metallurgical Engineering (Drexel University, 1969) Research Themes: Phase transformations, magnetic thin films, FePt-based alloys, boron nitride interfaces, HAMR media, and TEM-based microstructural analysis His recent publications emphasize granular media fabrication, thermal conductivity interfaces, and plasmonic transducer designs, reflecting ongoing contributions to magnetic storage technologies and nanomaterials.

Elisaweta MasserovaView profile

Research Fellow

• Cryptography
• Distributed Systems
• Blockchain Technology
• +3 more

Elisaweta Masserova is a Research Fellow in the Computer Science Department at Carnegie Mellon University , affiliated with the College of Engineering . She works in the Gates and Hillman Centers , focusing on advanced cryptographic protocols and decentralized systems. Research Interests : Elisaweta specializes in Cryptography , Blockchain Technology , and Secure Multi-Party Computation . Her work addresses challenges in Distributed Systems , including Atomic Swaps , Zero-Knowledge Proofs , and Privacy-Preserving Algorithms . Recent Publications highlight her contributions to scalable cryptographic frameworks, blockchain-based secret management, and collusion-resistant protocols. While no awards or student advisement details are provided, her research intersects Theoretical Computer Science , Security , and Applied Cryptography .

Jingao XuView profile

Research Fellow

• Event Cameras
• Drone Systems
• SLAM
• +5 more

Jingao Xu is a Research Fellow in the Computer Science Department at Carnegie Mellon University's School of Computer Science, based in room 9120 of the Gates and Hillman Centers. His research bridges computer vision, robotics, and edge computing with a focus on real-world applications in drone systems and mobile sensing. His work addresses critical challenges in resource-constrained environments through innovative sensor fusion techniques. Xu's primary research centers on event camera technology , where he pioneers applications in drone navigation, SLAM, and environmental monitoring. His contributions include deraining algorithms using state space models (PRE-Mamba), mmWave radar-event camera fusion for drone landing, and multi-robot gas source localization (SniffySquad). He specializes in extracting value from high-frequency event streams under challenging conditions like rain, low light, and high-speed motion, with significant work in fall detection systems and urban air quality monitoring through mobile crowd-sensing (CatUA). Analysis of his 15 most recent publications (2024-2025) reveals three dominant trends: (1) Adoption of state space models (particularly Mamba variants) for efficient event stream processing, (2) Integration of event cameras with complementary sensors (mmWave radar, depth, IMU) for robust perception, and (3) Development of edge-assisted frameworks for real-time drone operations in wildfire suppression and autonomous navigation. His work consistently targets practical deployment on mobile platforms with severe computational constraints. No scientific awards or honors were mentioned in the available information. Details regarding student advising, research grants, laboratory affiliations, or team structures were not provided in the source material.

Babu PillaiView profile

Teaching Professor

• Computer Science
• Software Engineering
• Algorithms
• +3 more

Babu Pillai is an Associate Teaching Professor in the Computer Science Department at Carnegie Mellon University. His office is located in Room 7123 of the Gates and Hillman Centers. He can be reached via email at pspillai@andrew.cmu.edu or by phone at (412) 268-2565. Professor Pillai teaches courses such as 15-410 (Operating Systems), 15-605 (Advanced Programming), 15-821 (Compilers), 15-440 (Computer Networks), and 15-640 (Distributed Systems), spanning both Fall and Spring semesters from 2024 to 2025. His academic support is managed by Emily Spencer (15410). No specific research interests or awards are listed, reflecting a focus on teaching and academic administration.