Conic Optimization Professors and Supervisors | ApplySharif

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Sonia CorianiView profile

Professor

Technical University of DenmarkDenmark

Sonia Coriani is a Professor in Physical Chemistry at DTU Chemistry, Technical University of Denmark, since 2017. She leads a research group focused on theoretical chemistry and computational spectroscopy. Her academic journey includes a PhD from Aarhus University (2000), a permanent research scientist position at the University of Trieste (1999-2014), and associate professorship there since 2014. She held an adjunct associate professor position at the Centre for Theoretical and Computational Chemistry in Oslo (2007-2011) and was a Marie Curie IEF fellow (2010-2012) and AIAS-COFUND senior fellow (2015-2016). Education: Chemistry, University of Modena (1993) PhD in Theoretical Chemistry, Aarhus University (2000) Her research centers on developing quantum-chemical methodologies for static and dynamic molecular properties, particularly for systems with high dimensionality, complex environments, or novel spectroscopic phenomena. Key areas include non-linear optical experiments, magnetic circular dichroism, X-ray spectroscopies, and quantum computing applications in chemistry. Her recent publications highlight advancements in quantum linear response theory, polarizable embedding environments, X-ray absorption in water, and quantum algorithms for molecular properties. Collaborative work spans interdisciplinary projects with experimentalists, covering gas-phase molecules to biomolecular systems. Scientific Awards: Marie Curie IEF fellowship AIAS-COFUND senior fellowship Her work addresses challenges in ultrafast dynamics, photoionization, and the intersection of chemistry with physics and computational science, emphasizing accuracy and novel experimental guidance.

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Georgina HallView profile

Assistant Professor

HHL Leipzig Graduate School of ManagementGermany

Georgina Hall serves as Assistant Professor of Decision Sciences at INSEAD, holding the prestigious Patrick and Valentine Firmenich Fellowship for Business and Society. She officially joined the institution in September 2019 after completing a postdoctoral position at INRIA's DYOGENE team from January to September 2019. Her educational background includes a PhD from Princeton University's Department of Operations Research and Financial Engineering (2018), where she was a Gordon Y.S. Wu fellow under Professor Amir Ali Ahmadi's supervision. She earned both her Bachelor of Science (2011) and Master of Science (2013) from Ecole Centrale Paris, where she was valedictorian. Dr. Hall's research focuses on optimization theory, particularly polynomial optimization , semidefinite programming , and convex relaxations of NP-hard problems . Her work bridges theoretical mathematics with practical applications in business decision-making. She has made significant contributions to shape-constrained regression using sum of squares polynomials, demonstrating how semidefinite programming hierarchies can effectively fit shape-constrained polynomials to noisy data. Her recent publications reveal a research trajectory that increasingly connects optimization theory with machine learning applications and supply chain decision-making. The 2025 Operations Research paper on shape-constrained regression represents her theoretical contributions, while the Management Science paper demonstrates practical business applications of her optimization framework. Her scientific recognition includes: Médaille de l'Ecole Centrale from the French Académie des Sciences Princeton School of Engineering and Applied Sciences Award for Excellence 2016 Informs Computing Society Prize for Best Student Paper Multiple teaching awards from Princeton University Patrick and Valentine Firmenich Fellowship for Business and Society Dr. Hall teaches Probability and Statistics at the PhD level and has received significant recognition for her teaching excellence, including the Princeton University's Engineering Council Teaching Award and the Excellence in Teaching Award from the Princeton Graduate School. Her research has practical applications in areas including optimal transport maps for color transfer tasks and estimating optimal value functions for conic programs, with real-time applications in inventory management contract negotiation.

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Qi LuoView profile

Assistant Professor

University of IowaUnited States

Qi Luo is an Assistant Professor in the Department of Business Analytics at Tippie College of Business, University of Iowa. His research focuses on developing data-driven decision-making models in supply chain management, emerging mobility services, and healthcare systems, alongside designing efficient algorithms for online learning, dynamic games, and nonlinear optimization. Education: While specific educational background details are not provided in the text, Dr. Luo's extensive research portfolio and academic position suggest advanced training in operations research, business analytics, or related quantitative fields. Research Interests: Core Areas: Data-driven decision making, supply chain optimization, urban transportation systems, healthcare operations Methodological Focus: Online learning algorithms, dynamic game theory, stochastic optimization, nonlinear programming Application Domains: Emerging mobility services (ride-sharing, autonomous vehicles), multimodal transit systems, inventory management with fixed costs, clinical trial optimization Research Impact: Dr. Luo's work spans from theoretical algorithmic developments to practical applications in transportation and healthcare. His publications demonstrate a consistent focus on solving real-world problems through advanced optimization techniques, with particular emphasis on stochastic modeling and learning-based approaches. The research addresses critical challenges in modern transportation systems including ride-pooling, multimodal transit, and autonomous vehicle operations, as well as healthcare applications like clinical trial design and robotic surgery optimization. Scientific Recognition: TRB Kikuchi-Karlaftis Best Paper Award INFORMS APS Best Student Paper (finalist) IEEE I-Sim Best Student Paper Award Research Funding & Support: Principal Investigator: "Early-Stage Clinical Trials with Patient Choice" - National Science Foundation (NSF), funded June 2023 - August 2026 ($XXX,XXX) Investigator: "Exploring Passenger-Parcel Comodality Transportation in Rural Regions" - Tippie College of Business, funded March 2025 - February 2026 Professional Affiliations: Dr. Luo maintains active memberships in leading professional organizations including the Association for Computing Machinery (ACM) since 2020, Institute of Electrical and Electronics Engineers (IEEE) since 2019, and Institute for Operations Research and the Management Sciences (INFORMS) since 2015.

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Ulrich DierkesView profile

Professor

University of Duisburg-EssenGermany

Ulrich Dierkes is a Professor in Mathematical Computer Science at the University of Duisburg-Essen, specializing in geometric analysis and variational problems. His research investigates minimal surfaces, singular PDEs, and multidimensional optimization. Research Focus: Key contributions include foundational work on singular minimal surfaces, Bernstein theorems in controlled growth settings, and n-dimensional extensions of classical variational problems. Recent studies resolve questions about cylindrical and symmetric minimal surfaces. Publications: Authored seminal monographs like 'Minimal Surfaces' (Springer, 2010) and published extensively on geometric PDEs. Articles emphasize existence theorems, regularity, and singular solutions in variational calculus.

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José Manuel FernándezView profile

Professor

Polytechnic University of Madrid (UPM)Spain

Dr. José Manuel Fernández is a Full Professor at the Polytechnic University of Madrid (UPM), specializing in antenna engineering, microwave systems, and millimeter-wave technologies. His research focuses on innovative designs for 5G communication systems, including phased arrays, 3D-printed components, and reconfigurable antennas. He leads projects involving W-band filters, Ka-band SATCOM systems, and low-cost phased array prototypes. His work emphasizes practical applications in aerospace, telecommunications, and energy harvesting. Fernández is affiliated with the Interspace5G research group and contributes to educational initiatives, such as bachelor’s and master’s thesis guidance. He has authored numerous peer-reviewed articles on topics like gradient-index lenses, frequency selective surfaces, and manufacturing processes for mm-wave devices. Research Interests: Dr. Fernández’s expertise spans antenna design, waveguide technologies, and additive manufacturing for RF components. His recent work addresses challenges in beam steering, polarization control, and robust filter designs for high-frequency systems. He also investigates cost-effective fabrication methods, such as electroplating and 3D printing, to enhance mm-wave device performance. Grants & Projects: Fernández has secured funding for predoctoral contracts and scholarships, supporting doctoral research in antenna engineering and related fields. He collaborates on initiatives like DEMERSTEM, focusing on stock identification for sustainable fisheries, and LEHA projects involving measurement systems for 5G terminals. Labs & Teams: His research is anchored in UPM’s advanced labs, including the Interspace5G group, which develops cutting-edge antenna solutions for 5G and satellite communication. He also contributes to interdisciplinary efforts in materials science and aerospace engineering.

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Sivakumar RathinamView profile

Professor

Texas A&M UniversityUnited States

Dr. Sivakumar Rathinam is a Professor in the Department of Mechanical Engineering at Texas A&M University, affiliated with the College of Engineering and the Computer Science & Engineering department. He holds certifications as a Fellow of ASME (2021) and Senior Member of IEEE (2019). His research focuses on motion planning for autonomous vehicles, collaborative decision-making, combinatorial optimization, and vision-based control systems. He leads the Autonomy Lab, addressing challenges in multi-agent systems, path planning, and rural autonomous vehicle accessibility. Education: Ph.D., Civil Systems Engineering, University of California, Berkeley (2007) M.S., Electrical Engineering & Computer Science, UC Berkeley (2006) M.S., Mechanical Engineering, Texas A&M University (2001) B.Tech., Mechanical Engineering, Indian Institute of Technology Madras (1999) Research Highlights: Dr. Rathinam's work spans autonomous vehicle navigation, UAV coordination, and sensor fusion for adverse conditions. His lab develops algorithms for multi-agent pathfinding and persistent monitoring missions. Recent efforts include rural road detection datasets (R2D2) and thermal/LIDAR sensor fusion for safety in challenging environments. Awards: Outstanding Faculty Contribution Award (2021) Best Paper Runner-Up, ICAPS (2021) Teaching Excellence Award (2012) Labs & Teams: Directs the Autonomy Lab, collaborating with industry partners through the Mechanical Engineering Industry Advisory Council. Active in NSF-funded projects on equitable rural autonomy and multi-UAV recharging frameworks.

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Ryan Cory-WrightView profile

Assistant Professor

Princeton UniversityUnited States

Ryan Cory-Wright is an Assistant Professor in the Analytics and Operations Group at Imperial College Business School . He previously held a Goldstine Postdoctoral Fellowship at IBM Research and earned his PhD in Operations Research from MIT in 2022 under Dimitris Bertsimas , after obtaining a BE (1st class Hons) in Engineering Science from the University of Auckland. Education : MIT (PhD), University of Auckland (BE) Affiliations : Imperial College Business School, IBM Research, MIT His research bridges optimization, machine learning, and sustainability, focusing on extending optimization methods to solve practical problems like rank-constrained product recommendations and low-carbon economy transitions . Collaborations include projects with OCP to guide two billion USD solar-battery investments . Recent work includes AI-Hilbert (2024 Nature Communications , Outstanding Technical Achievement Award ), Stability Regularized Cross-Validation , and Matrix Goemans-Williamson Rounding . He has developed scalable algorithms for sparse portfolio selection and certifiably optimal matrix completion . Honors : Goldstine Fellowship (2022-23) Nicholson Prize (2020) Pierskalla Award (2020) INFORMS DMDA Best Paper (2024) ICS Student Paper Award (2019) Advising : Co-advises Lingjun Meng as a doctoral student. He teaches Decision Making Under Uncertainty (PhD), Optimization and Decision Models (Online MSc), and Data Structures/Algorithms (UG Econ/Finance), with a focus on Python-based computational methods.

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Ralf WernerView profile

Professor

University of AugsburgGermany

Professor Ralf Werner serves as Professor of Business Mathematics at the University of Augsburg, where he leads the Computational Statistics and Data Analysis working group within the Institute of Mathematics at the Faculty of Mathematics, Natural Sciences and Technology. His academic career spans both theoretical research and practical industry applications in quantitative finance. Werner's research interests encompass: Computational Statistics and Data Analysis Optimization under Uncertainty Financial Engineering and Risk Management Actuarial Science and Insurance Mathematics Portfolio Optimization and Asset Allocation His scholarly output demonstrates a consistent focus on robust mathematical methods applied to financial problems, particularly in replicating portfolios for insurance applications, credit risk modeling, and statistical approaches to financial risk management. Werner's publications appear in leading journals across operations research, mathematical finance, and actuarial science. Professional qualifications include his habilitation at the Karlsruhe Institute of Technology (2011) and doctorate from Friedrich-Alexander University Erlangen (2001). He maintains active industry connections through his role as Scientific Advisor for DEVnet since 2010. Werner serves as Internship Coordinator and DAV (German Actuarial Society) correspondent, supporting students pursuing actuarial careers. He is an active member of multiple professional organizations including the Society for Operations Research (GOR), German Mathematical Society (DMV), and German Society for Insurance and Financial Mathematics (DGVFM).

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Victor ChernozhukovView profile

Professor

Massachusetts Institute of TechnologyUnited States

Victor Chernozhukov is a Professor at the Department of Economics and Center for Statistics at the Massachusetts Institute of Technology (MIT) . He also holds international fellowships at the University College London's CEMMAP and is a Professor by Courtesy at the New Economic School in Russia. His research spans econometrics, high-dimensional statistics, quantile regression, and causal inference. Education: Ph.D. in Economics from Stanford University (2000), M.S. in Statistics from University of Illinois at Urbana-Champaign (1997) His work focuses on developing statistical methods for high-dimensional data, including central limit theorems , post-selection inference , and quantile regression . He has contributed to partial identification , Bayesian inference , and extreme value analysis , with applications to economic policy evaluation. Recent publications emphasize high-dimensional causal inference , adaptive confidence bands , and set estimation . His research has been supported by the National Science Foundation and recognized with the Alfred P. Sloan Research Fellowship . Scientific Awards: Alfred P. Sloan Research Fellowship (2005-2007) Castle-Krob Career Development Chair (2004-2007) Grants include long-term support from the National Science Foundation since 2001 and software development collaborations for Stata and MATLAB implementations.

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Guilherme BarrosView profile

Research Fellow

University of Newcastle Australia (UON)Australia

Dr. Guilherme Barros serves as a Research Fellow at the University of Newcastle within the School of Engineering and Centre for Geotechnical Science and Engineering, specializing in computational geomechanics and machine learning applications for rockfall hazard prediction. His academic credentials include: B.Sc. in Civil Engineering from Fluminense Federal University (UFF) M.Sc. in Civil Engineering from Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Ph.D. in Civil Engineering from the University of Newcastle Barros' research centers on Modelling and simulation (30% focus), Geomechanics and resources geotechnical engineering (30%), and Deep learning (20%), with additional expertise in Granular mechanics and Solid mechanics. His work pioneers hybrid approaches combining physics-based numerical methods (BEM, DEM, FEM) with machine learning to address rockfall hazards in mining, seismic wave propagation in unbounded domains, and computational limit analysis. This interdisciplinary framework significantly enhances predictive accuracy for geotechnical risk assessment in complex terrain. His publication record reveals a clear trajectory toward advanced multi-scale numerical coupling, particularly BEM-DEM integration for dynamic geomechanical problems across 1D to 3D domains. These works address critical challenges in infinite domain modeling, wave propagation discontinuities, and rockfall fragmentation prediction, demonstrating strong applicability to mining safety and civil infrastructure resilience. His scientific recognition includes: AGS NSW Research Award (Australian Geomechanics Society, 2025) Barros has co-supervised two Master's students on rockfall analysis projects: one at the University of Parma investigating material layer impacts on hazard prediction, and another at Newcastle comparing machine learning techniques (Random Forest, KNN) for trajectory modeling. His international research network spans Brazil (6 publications), Australia (5), and Poland (5), supported by funding from the Australian Geomechanics Society. As an active contributor to the Centre for Geotechnical Science and Engineering, he develops computational frameworks for real-world mining safety challenges, with current projects focusing on machine learning-enhanced rockfall prediction systems for NSW and QLD open-pit mines.

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Ralph A. BrasacchioView profile

Associate Clinical Professor

University of RochesterUnited States

Ralph A. Brasacchio, M.D. serves as Associate Professor of Clinical Radiation Oncology at the University of Rochester School of Medicine and Dentistry, Department of Radiation Oncology. Board-certified by the American Board of Radiology, he practices at Sands Cancer Center in Canandaigua, NY, and is part of the University of Rochester Medical Faculty Group and Accountable Health Partners network, currently accepting new patients. His educational foundation includes: MD from Jefferson Medical College (1990) Internal Medicine Residency at Mercy Catholic Medical Center Inc. (1990-1991) Radiation Oncology Residency and Fellowship at University of Rochester Medical Center (1991-1995) Brasacchio's research centers on advancing prostate cancer treatment through robotic-assisted brachytherapy, with significant contributions to needle insertion mechanics, prostate stabilization, and image-guided therapy optimization. His work addresses critical challenges in radiation oncology including cancer-related fatigue management and gastrointestinal complications from radiotherapy, demonstrating consistent innovation from 1998 through 2014 publications. Analysis of his 15 most recent publications reveals a dominant focus on prostate brachytherapy robotics (12/15 articles), emphasizing surgical precision through force modeling, motion measurement, and conical implant optimization. Secondary themes include metastasis biology and radiation-induced secondary cancers, reflecting his dual expertise in technical innovation and clinical oncology outcomes. Key recognitions include: Philip Rubin / Mayer Mitchell Award for Excellence in Teaching (1998) Clinical Oncology Fellowship (1993-1994) NIH Research Traineeship Grant (1987) Clinical Research Elective in immunologic disease mechanisms (1990) His research portfolio features NIH-funded projects and leadership in multi-institutional trials like the Phase III pentosanpolysulfate study for radiation-induced gastrointestinal toxicity. Brasacchio maintains active clinical research in prostate cancer brachytherapy optimization while contributing to textbook chapters in prostate cancer treatment and CNS tumor management.

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Robert ConnellyView profile

Professor

Cornell UniversityUnited States

Robert Connelly is a Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences. His research focuses on Discrete Geometry, Rigidity Theory, and Computational Geometry , particularly exploring tensegrity structures, flexible surfaces, and their applications in robotics, protein folding, and materials science. He has taught courses including Calculus I and supervised graduate research. Key research interests include the rigidity of discrete structures, sphere packings, and geometric optimization. His work on the 'Bellows Conjecture' demonstrated that flexible surfaces maintain constant volume during deformation, merging algebraic geometry and topology. He has authored over 150 publications and contributed to foundational texts in rigidity theory. Teaching roles include leading the Calculus II course in 2020 and supervising independent research projects. His work spans theoretical advancements and applications in engineering and physics, emphasizing interdisciplinary approaches to geometric problems.

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Lixin LuView profile

Researcher

Stanford UniversityUnited States

Lixin Lu is a Researcher (Postdoctoral Scholar) in the Department of Chemistry at Stanford University, affiliated with the School of Humanities and Sciences. Their work focuses on theoretical and computational chemistry, particularly in developing advanced electronic structure methods and applying them to study molecular dynamics, spectroscopy, and materials science. They are part of affiliated programs including CMAD (Center for Molecular Analysis and Design), ChEM-H (Chemistry, Engineering & Medicine for Human Health), and SSRL (Stanford Synchrotron Radiation Lightsource). Research interests include relativistic quantum chemistry, X-ray spectroscopy, ultrafast phenomena, and computational modeling of molecular systems. Their contributions span multiconfiguration methods, ab initio dynamics, and the analysis of radiation effects in materials. Theoretical frameworks developed by Lu address challenges in high-performance computing and accurate description of molecular excitations. Affiliations with SSRL and ChEM-H highlight collaborative efforts in experimental-theoretical interfaces, such as attosecond X-ray spectroscopy and liquid-phase dynamics. Lu’s work bridges computational innovation with cutting-edge experimental techniques to uncover fundamental insights into chemical and physical processes at the molecular level.

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Juliette ChabassierView profile

Researcher

InriaFrance

Juliette Chabassier is a Researcher at the MAGIQUE-3D project team within Inria Bordeaux Sud-Ouest and affiliated with Université de Pau et des Pays de l'Adour . She holds a Ph.D. in Applied Mathematics from École Polytechnique (2012), advised by Patrick Joly and Antoine Chaigne. Roles: Junior Research Scientist (since 2013), Post-Doc at University of Pau (2012-2013) Research Focus: Acoustics of musical instruments, wave propagation modeling, numerical simulation of piano and wind instruments, energy-preserving discretization schemes, and viscothermal effects in ducts. Her work emphasizes physical modeling and computational acoustics , particularly in piano acoustics, wind instrument design, and heritage instrument digitization. She develops tools like OpenWind for simulating instrument responses and collaborates on projects involving piano soundboard analysis and historical instrument reconstruction. Her recent articles explore topics such as: Simulation of brass instruments using finite element models Thermoviscous effects in conical tubes Energy-conserving discretization for nonlinear wave equations Digital twins for heritage instruments like Besson trumpets She advises doctoral students including Elvira Shishenina and Izar Azpiroz , focusing on applied mathematics and acoustics. Her contributions include advanced numerical methods for acoustic-elastic coupling and boundary layer phenomena in exponential media. Current projects involve homogenization techniques for porous materials, real-time instrument simulation tools, and interdisciplinary work on acoustics education through open-source software.

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Danny WongView profile

Research Fellow

Macquarie UniversityAustralia

Danny Wong is a Research Fellow and Honorary Senior Lecturer in the Department of Applied BioSciences at Macquarie University. His research focuses on advanced biosensor development, electrochemical techniques for neurotransmitter detection, and nanomaterial applications in biomedical engineering. Wong has led multiple research projects, including the development of antifouling carbon electrodes and biofuel cells for self-powered sensing. Research Fellow, Applied BioSciences (Macquarie University) Honorary Senior Lecturer, Applied BioSciences Principal Investigator for projects on biosensor design (2006–2021) His research interests span electrochemistry, nanomaterials, and biomedical applications. Key areas include dopamine detection, enzymatic biosensor optimization, and field-deployable sensing systems. Wong’s work emphasizes minimizing sensor fouling through surface modification techniques like hydrogenation and nanocomposite integration. Publications highlight advancements in MOF-based nanocomposites, photoelectrochemical sensors, and biofuel cell design. Collaborations include interdisciplinary projects on mitochondrial superoxide detection and environmental monitoring of toxins in infant foods. No scientific awards were explicitly mentioned. Wong has advised on numerous research projects but no student names were listed. His work includes grants for projects such as plasma-enhanced CVD systems (2021) and rapid isolation systems (2020). Labs/Teams: Active in Macquarie’s biosensor engineering group, collaborating with materials scientists and biomedical researchers.

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