Quantum Computing Algorithms Professors and Supervisors in Qatar | ApplySharif

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Sridhar R. TayurView profile

Academic

Carnegie Mellon UniversityQatar

Sridhar R. Tayur is the Ford Distinguished Research Chair and University Professor of Operations Management at Carnegie Mellon University’s Tepper School of Business. He holds a Ph.D. in Operations Research from Cornell University and a B.Tech. in Mechanical Engineering from IIT Madras. His research focuses on quantum computing applications in operations research, healthcare systems optimization, and supply chain management. He has held visiting roles at MIT, Stanford, and Cornell, and founded companies like SmartOps and OrganJet. His recent work spans quantum-inspired optimization algorithms, healthcare decision support systems, and fair resource allocation policies. He has contributed to over 110 publications, including high-impact papers in Management Science , Operations Research , and IEEE Transactions . Awards include INFORMS Fellow and NAE membership. He teaches courses in quantum integer programming, healthcare operations, and service management at the Tepper School. Education: Ph.D. (Cornell), B.Tech. (IIT Madras) Research Labs: Quantum Technology Group, OrganJet Key Awards: INFORMS Fellow, NAE Member, MSOM Distinguished Fellow Teaching: MBA Operations Management, PhD Quantum Optimization, Healthcare Systems His interdisciplinary work bridges quantum computing, healthcare policy, and logistics, supported by collaborations with industry and government institutions.

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Franz FranchettiView profile

Professor

Carnegie Mellon UniversityQatar

Franz Franchetti is the Kavčić-Moura Professor of Electrical & Computer Engineering at Carnegie Mellon University. He serves as Associate Dean for Research and Director of the Engineering Research Accelerator at CMU. Education: Ph.D. in Computational Mathematics (Vienna University of Technology, 2003) M.Sc. in Technical Mathematics (Vienna University of Technology, 2000) His research interests focus on automatic performance tuning and program generation for emerging parallel computing platforms , including multicore CPUs , GPUs , and 3DIC chip design . He leads the SPIRAL effort to automate highly optimized software libraries and explores domain-specific compiler transformations in HPC applications for smart grids and material sciences . Recent work extends SPIRAL to quantum computing . The scientific awards Franchetti has received include the Gordon Bell Prize (2006) , HPC Challenge Class II Award (2010) , and the CIT Dean's Early Career Fellowship (2013) . He and his students have won multiple Best Paper Awards at HPEC, DAC, and ISPA ACM TODAES Best Paper (2014) Student Research Competition wins (PACT 2024, CGO 2023) Franchetti has advised students like Richard Veras and Thom Popovici . He has secured significant grants from agencies such as DARPA, DOE, NSF, and industry partners (Intel, NVIDIA, Mercury). He co-founded SpiralGen, Inc. and holds leadership roles in organizations like ASciNA Western Pennsylvania and as Honorary Consul of Austria in Pittsburgh.

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Tathagata SrimaniView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Tathagata Srimani is an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He previously served as a Postdoctoral Scholar in Electrical Engineering at Stanford University. His academic journey includes a Ph.D. and S.M. in EECS from MIT (2022 and 2018 respectively) and a B.Tech. in E&ECE from IIT Kharagpur (2016). Research Focus: Srimani’s work centers on nanoelectronics and transformative NanoSystems. Key areas include: Carbon nanotube field-effect transistors (CNFETs) and their monolithic 3D integration with silicon Ultra-dense 3D integration of logic and memory to address the 'memory wall' in AI/ML Technology-architecture co-design frameworks for energy-efficient computing Key Achievements: Developed first silicon fab-compatible CNFET processes (TNANO ’18, Nature ’19) Enabled CNFET RISC-V microprocessor and monolithic 3D integration with Analog Devices/SkyWater Recipient of MIT Presidential Fellowship (2016) and Morris Joseph Levin Award (2018) Teaching & Outreach: Teaches semiconductor devices and hardware design, including hands-on 'Hacker Fab' courses. Leads the NEXUS Research Group exploring heterogeneous nanomaterials (e.g., magnetic and oxide semiconductors) and thermal/power management in 3D systems. Future Directions: Expanding into probabilistic computing hardware, co-design frameworks for application-specific systems, and scaling 3D NanoSystem technologies for industrial adoption.

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Venkatesan GuruswamiView profile

Professor

Carnegie Mellon UniversityQatar

Venkatesan Guruswami is a Chancellor's Professor in the Department of Electrical Engineering and Computer Sciences and Professor in the Department of Mathematics at the University of California, Berkeley. He previously served as faculty at Carnegie Mellon University for 13 years and held a Miller Research Fellowship at UC Berkeley. His research focuses on Theoretical Computer Science , particularly in Error-Correcting Codes , Approximation Algorithms , Quantum Computing , and Hardness of Approximation . Guruswami has made groundbreaking contributions to list decoding and quantum code constructions, with works featured in Science Magazine and the Journal of the ACM (where he serves as Editor-in-Chief). Education : B.Tech (1997, IIT Madras), Ph.D. (2001, MIT), Miller Research Fellowship (2001-02, UC Berkeley) Research Areas : Theory of error-correcting codes, approximation algorithms, pseudorandomness, probabilistically checkable proofs, and quantum coding theory Guruswami's recent work explores quantum LDPC codes , parameterized inapproximability , and stream decodable codes . He has received prestigious awards including the NSF CAREER award , David and Lucile Packard Fellowship , and Sloan Research Fellowship . His advising spans a wide range of students and postdocs, with notable contributions to coding theory and computational complexity .

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Riad S. WahbyView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Riad S. Wahby is an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. His work focuses on designing secure hardware and software systems, with recent emphasis on cryptographic proof systems. He actively mentors PhD students and collaborates across disciplines in cybersecurity, blockchain, and formal verification. PhD in Computer Science, Stanford University MEng in Electrical Engineering, Massachusetts Institute of Technology SB in Electrical Engineering, Massachusetts Institute of Technology Wahby's research spans cryptography , blockchain security , zero-knowledge proofs , and secure hardware-software co-design . His work addresses challenges in verifiable computation, privacy-preserving protocols, and hardware subversion resistance. Recent publications reveal trends in zero-knowledge proof systems (SNARKs, MPC), blockchain security (anonymous blocklisting, decentralized auctions), and hardware-crypto integration (weird machines, verifiable ASICs). Technical focus areas include formal verification, side-channel analysis, and cryptographic compilers. Distinguished Student Paper Award, IEEE Symposium on Security and Privacy (Oakland16), 2016 Best Paper Award, USENIX Annual Technical Conference (ATC18), 2018 Wahby collaborates with researchers across institutions and industries, including Dan Boneh at Stanford, Mike Walfish at NYU, and Silicon Labs in industrial roles. His CyLab affiliations connect him to over $400K in seed funding opportunities and blockchain initiatives at CMU.

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Aayush JainView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Aayush Jain is an Assistant Professor in the Computer Science Department at Carnegie Mellon University. Previously, he was a Postdoctoral Fellow at NTT Research and a PhD student at UCLA, advised by Professor Amit Sahai. His work bridges theoretical and applied cryptography with core computer science principles. Education PhD in Computer Science, University of California, Los Angeles (UCLA) Postdoctoral Fellowship, NTT Research Research Focus His research explores: foundational cryptography, indistinguishability obfuscation, functional encryption, lattice-based cryptography, secure multi-party computation, and post-quantum security. Work emphasizes rigorous theoretical frameworks with practical implications. Publication Trends Recent articles (2021-2024) demonstrate consistent focus on cryptographic primitives, obfuscation techniques, and security reductions. Dominant venues include CRYPTO, EUROCRYPT, FOCS, and STOC with emerging work in machine learning interfaces. Awards Best Paper Award at STOC 2021 for foundational contributions to indistinguishability obfuscation Advising and Collaboration Current PhD advisees: Alper Cakan, Quang Dao (co-advised), Sagnik Saha, Noah Singer (co-advised). Mentored postdocs: Mitali Bafna (2022-2023) and Rex Fernando (2022-2023). Teaches graduate courses in cryptography and theoretical tools. Leadership Leads the CMU Cryptography research group; organized the CMU Cryptography Workshop. Program committee member for FOCS, TCC, ITCS, and ICALP.

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Noa MaromView profile

Associate Professor

Carnegie Mellon UniversityQatar

Noa Marom is an Associate Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU), holding courtesy appointments in Chemistry and Physics. She is a member of the Pittsburgh Quantum Institute (PQI) and an affiliate of the Wilton E. Scott Institute for Energy Innovation. Her research focuses on computational materials science, energy security, and quantum materials. Marom earned a B.A. in Physics and B.S. in Materials Engineering (cum laude) from the Technion-Israel Institute of Technology (2003) and a Ph.D. in Chemistry from the Weizmann Institute of Science (2010). She held postdoctoral positions at the University of Texas at Austin’s Institute for Computational Engineering and Sciences (ICES) before joining Tulane University as an Assistant Professor (2013–2016) and CMU in 2016. Her research interests include computational design of semiconductor materials, topological quantum computing, and crystal structure prediction. Key projects involve machine learning for materials discovery and quantum computing applications, such as optimizing semiconductor interfaces for stable qubits. Marom has received numerous awards, including the NSF CAREER Award (2016), DOE INCITE Awards (2017–2019), and the IUPAP Young Scientist Prize (2018). She serves as Associate Editor of npj Computational Materials. Her work spans collaborations with institutions like the Paul Scherrer Institute (Switzerland) and the Pittsburgh Supercomputing Center. Research highlights include computational studies of InAs/InSb semiconductors for quantum bits and machine learning-driven discovery of organic semiconductors.

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David YaronView profile

Professor

Carnegie Mellon UniversityQatar

David Yaron is a Professor of Chemistry at Carnegie Mellon University's Mellon College of Science. His research focuses on computational chemistry, machine learning applications in chemical modeling, and educational technology. He holds a Ph.D. from Harvard University (1990) and a B.S. from Wilkes College (1983). Yaron's work includes developing semiempirical quantum chemical models, designing dyes for biological imaging, and creating virtual labs like ChemCollective and ChemVLab+. He has received numerous awards, including the Richard Moore Award (2023) and the Henry Dreyfus Teacher-Scholar Award (2000). His educational initiatives emphasize data-driven learning and open-ended problem-solving. Research Interests: Machine Learning for Chemistry, Photophysics, Materials Theory, Chemical Education Key Projects: Quantum chemical models via ML, design of fluorogenic dyes, light-driven molecular motors Education: Ph.D. Harvard (1990), B.S. Wilkes College (1983) Awards highlight both research (e.g., Camile & Henry Dreyfus Foundation) and teaching (e.g., Teaching Innovation Awards). His lab has advised over 30 graduate and undergraduate students. Publications span quantum chemistry methods, polymer science, and educational technology.

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Gabriel GomesView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Gabriel Gomes is an Assistant Professor in the Departments of Chemistry and Chemical Engineering at Carnegie Mellon University, where he leads the Gomes Group research program focused on the intersection of machine learning and chemistry. His work centers on developing new chemical reactions, catalysts, and materials using state-of-the-art machine learning and automated synthesis techniques. Dr. Gomes received his Ph.D. in Chemistry from Florida State University in 2018 under Professor Igor V. Alabugin, where he researched stereoelectronic effects. Prior to joining CMU in 2022, he was a Banting Postdoctoral Fellow at the University of Toronto in the Matter Lab led by Professor Alán Aspuru-Guzik. He earned his B.S. in Chemistry from Federal University of Rio de Janeiro, Brazil in 2013. His research program focuses on developing autonomous platforms for reaction discovery, with emphasis on catalysis. Gomes aims to create inverse design frameworks where algorithms can propose new functional catalysts from scratch based on desired properties. His work integrates quantum mechanics with machine learning to teach computers chemical intuition, enabling novel approaches to catalyst design and chemical synthesis. He strongly advocates for the integration of AI with human creativity to transform chemical research. Gomes' recent publications demonstrate a clear trend toward integrating large language models with chemical discovery, developing transferable machine learning potentials for catalysis, and advancing molecular representations with quantum chemical insights. His work spans from fundamental quantum chemistry to practical applications in biocatalysis and materials design. Scialog Fellow (2023) C&EN Talented Twelve (2022) NSERC Banting Postdoctoral Fellowship (2020-2021) CAS SciFinder Future Leaders Program (2018) ACS COMP Chemical Computing Group Excellence Award (2018) FSU's Graduate Student Research and Creativity Award (2018) IBM Ph.D. Scholarship (2017) Dr. Gomes mentors several graduate students including Robert MacKnight and Daniil Boiko, who have contributed to projects like the Catnip web application for biocatalyst prediction. His research has received funding through prestigious programs like the Scialog Automating Chemical Laboratories awards. Gomes actively promotes open science initiatives and has contributed to the Open Reaction Database to improve data accessibility for machine learning in chemistry. The Gomes Group operates at the cutting edge of AI-driven chemistry research, developing tools like Coscientist that bridge the gap between natural language prompts and actual chemical reactions. Their work on autonomous reaction discovery systems represents a significant step toward fully automated chemical laboratories where machines can 'dream of molecules' with specific desired properties.

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Fraser BrownView profile

Adjunct Professor

Carnegie Mellon UniversityQatar

Fraser Brown is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, affiliated with the College of Engineering. His research focuses on the intersection of systems, programming languages, and security, with particular emphasis on verified compilers, cryptographic applications, and finding vulnerabilities in real systems. He holds a position at the university's Pittsburgh campus located at 5000 Forbes Avenue. His research interests include compiler optimization verification, cryptographic protocol compilation, and secure execution environments. Notable projects involve verified components of browser JIT compilers and compilation infrastructure for cryptographic use cases. He has contributed to frameworks like WaVe (verifiably secure WebAssembly runtime) and Icarus (trustworthy JIT compilers). Recent publications (2021–2025) explore topics such as zero-knowledge proof compilers, secure MPC protocols, and microarchitectural vulnerability mitigation. His work frequently combines formal verification techniques with practical system implementations to enhance software and hardware security. Fraser has collaborated on grants like the SaTC-funded project on verified secure sandboxed systems. While no formal advisees are listed, his research contributions reflect collaborative efforts in academic and industrial contexts. His work is disseminated through venues like programming language and security workshops (e.g., PLAS 2023) and peer-reviewed journals/conferences.

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Yang LiuView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Yang P. Liu is an Assistant Professor in the Computer Science Department at Carnegie Mellon University. Previously, he was a Postdoctoral Member at the Institute for Advanced Study and earned his PhD from Stanford University under the supervision of Aaron Sidford. His research focuses on theoretical computer science and mathematics, emphasizing graph algorithms, optimization, high-dimensional geometry, and additive combinatorics. He has received notable awards including the A.W. Tucker Prize and Google PhD Fellowship, alongside multiple best paper recognitions at major conferences like FOCS, STOC, and ITCS. Education: PhD in Computer Science from Stanford University (2023); BS from MIT (2018). Research Interests: Graph Algorithms Optimization (especially convex and high-dimensional) Algorithmic Techniques in Additive Combinatorics Geometric and Structural Aspects of Computation Teaching: Currently instructing CS 15-759: A Principled Approach to Optimization (Spring 2025), covering topics like gradient descent, interior-point methods, and sparsification techniques. Course emphasizes rigorous mathematical foundations. Awards: Recognized for contributions to optimization theory and algorithmic complexity. His work bridges discrete mathematics and continuous optimization paradigms.

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Marc DandinView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Marc Dandin is an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He joined CMU in July 2019 after co-founding a medical diagnostics startup and working in intellectual property law in Washington, D.C. His research focuses on bioelectronics, microsystems engineering, and integrated circuits, aiming to bridge electronics and biological systems for novel diagnostic tools and therapies. Education: Ph.D., Bioengineering, University of Maryland, College Park (2016) M.S. and B.S., Electrical Engineering, University of Maryland, College Park (2011 and 2009) Research Interests: Dr. Dandin’s work integrates CMOS bioelectronics, lab-on-chip systems, and machine learning for applications in cancer cell analysis, single-photon detection, and cybersecurity. Key areas include: Capacitance sensing platforms for real-time cell viability measurements Single-photon avalanche diodes (SPADs) for quantum imaging and hardware security Translational bioengineering for unmet medical needs Awards & Grants: NSF CAREER Award (2025) ARPA-H $42M grant for implantable bioelectric devices (2024) Oracle Research Project Award for single-cell cancer research (2022) IEEE Senior Member (2017) Advising & Outreach: His Integrated Circuits and Bioengineering Lab engages students in multidisciplinary projects, including entrepreneurship practicums and educational frameworks for middle/high school optoelectronics training. Research collaborations emphasize translational impact, combining lab-on-CMOS platforms with cloud-based data analysis. Labs/Teams: Leads the Integrated Circuits and Bioengineering Lab, collaborating with CMU’s Robotics Institute and biomedical engineering groups to advance cell-based diagnostics and cybersecurity in healthcare systems.

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Ken MaiView profile

Research Professor

Carnegie Mellon UniversityQatar

Ken Mai is a Principal Systems Scientist in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.S., M.S., and Ph.D. in Electrical Engineering from Stanford University. His research focuses on high-performance circuit design, secure IC design, radiation hardening, reconfigurable computing, and computer architecture. He has received prestigious awards including the NSF CAREER Award and the George Tallman Ladd Research Award. Education: Ph.D., Electrical Engineering, Stanford University, 2005 M.S., Electrical Engineering, Stanford University, 1997 B.S., Electrical Engineering, Stanford University, 1993 Research Interests: Dr. Mai’s work addresses challenges in nanometer-scale CMOS technology, including interconnect delay, leakage, and soft errors. His projects include secure IC design against hardware attacks, robust memory techniques using digital communications, 100GHz logic via cryogenic cooling, and bio-implantable computing platforms. He collaborates with neurosurgeons at the University of Pittsburgh for medical applications. Key Projects: Secure IC Design: Countermeasures against invasive/non-invasive attacks Robust Memory Design: Error correction codes for resilience 100GHz Logic: Cryogenically cooled CMOS for high-speed applications Bio-Implantable Systems: Low-power, high-density computing for medical devices Awards: NSF CAREER Award George Tallman Ladd Research Award Eta Kappa Nu Excellence in Teaching Award Teaching and Advising: He teaches courses like 18-322 (Digital Circuits), 18-617 (Memory Systems), and advises students including Mudit Bhargava and Mark McCartney. His lab, the VLSI Design Group, develops tools and methodologies linking circuit design to architectural design. Contact: Email: kenmai@ece.cmu.edu Website: Carnegie Mellon VLSI Design Group

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Marijn HeuleView profile

Associate Professor

Carnegie Mellon UniversityQatar

Marijn Heule is an Associate Professor in the Computer Science Department at Carnegie Mellon University. He received his PhD from Delft University of Technology in the Netherlands. His academic career has been focused on advancing the theory and practice of satisfiability (SAT) solving and its applications. Dr. Heule's research primarily centers on solving hard combinatorial problems in formal verification, number theory, and extremal combinatorics. His work has made significant contributions to both theoretical foundations and practical implementations of SAT solvers. He has developed award-winning SAT solvers, and his preprocessing techniques are incorporated into state-of-the-art SAT solvers used worldwide. His current research focuses on two major challenges: exploiting high-performance computing for SAT solving and validating results from SAT solvers and related tools. Dr. Heule pioneered the "cube-and-conquer" paradigm, a novel parallel SAT solving approach that enables linear time speedups on many hard problems. His first publication on this topic won the best paper award at HVC 2011. He also designed a new proof format with a corresponding fast proof checker for SAT and QBF solvers. This proof logging format has been mandatory for SAT Competitions since 2013, significantly increasing confidence in tool correctness. His work on the Boolean Pythagorean Triples problem, which produced a 200 TB proof that was validated, demonstrated that proof logging and verification is feasible even for the most complex problems. Dr. Heule is one of the editors of the 900+ page "Handbook of Satisfiability," which has become a standard reference in the SAT community. He serves as an Associate Editor of the Journal on Satisfiability, Boolean Modeling and Computation and previously co-chaired the SAT 2015 conference in Austin. Best paper award at HVC 2011 for cube-and-conquer publication Multiple best paper awards/nominations at major conferences including IJCAR, SAT, TACAS Work featured in New York Times, Quanta Magazine, Nature, and other major media outlets Dr. Heule has advised several PhD students including Emre Yolcu, Joseph Reeves, Bernardo Subercaseaux, Cayden Codel, James Gallicchio, and Amar Shah. He has developed important software tools including DRAT-trim (a proof checking utility), QRAT-trim, and implementations of the cube-and-conquer paradigm that have become standard in the SAT solving community.

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Sarah SchefflerView profile

Assistant Professor

Carnegie Mellon UniversityQatar

Sarah Scheffler is an Assistant Professor at Carnegie Mellon University, jointly appointed between the School of Computer Science and the College of Engineering. She holds roles in the departments of Software and Societal Systems and Engineering and Public Policy, focusing on applied cryptography and its intersections with policy, law, and societal impact. Her research explores end-to-end encryption, privacy-preserving technologies, and their regulatory challenges, including content moderation, compelled decryption, and autonomous systems. Scheffler earned her Ph.D. in 2021 from Boston University under Mayank Varia, with postdoctoral roles at MIT and Princeton. She advises students in EPP and S3 programs and actively engages in interdisciplinary projects addressing privacy and cybersecurity. Her work emphasizes cryptographic protocols tailored to real-world use cases, such as zero-knowledge proofs, multi-party computation, and privacy engineering. Scheffler frequently contributes to policy discussions on encryption, data protection, and the societal implications of technology. She is a core member of CyLab, CMU's Security and Privacy Institute. Publications highlight advancements in secure computation, privacy-preserving algorithms, and legal-technical analyses. Current research includes privacy in age verification systems and scalable content moderation under encryption. She advocates for robust encryption standards despite regulatory pressures, as seen in her CNN commentary on Apple's UK data protection policies.

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