Find Academic Supervisors

• Combinatorial Optimization
• Logistics Network Design
• Arc Routing Problems
• +4 more

Maria João Cortinhal is an Associate Professor at ISCTE-IUL, serving as Director of ISCTE Business School since 2023 and holding various academic management positions including coordinator of the third year of the Bachelor's in Management, elected member of the Scientific Council and General Council, and department director. She is affiliated with the Department of Quantitative Methods for Management and Economics at ISCTE Business School. Director of School of Management (2023-2027) President of Scientific Committee (2023-2027) Director of Institutional Course at School of Management (2023-2024) Former Director of School of Management (2019-2023) Former President of Scientific Committee (2019-2023) Her educational background includes a PhD in Statistics and Operational Research from Faculty of Sciences - UL (2005), Master's degree in the same field (1994), and Bachelor's degree (1990). Dr. Cortinhal's research focuses on combinatorial optimization problems, with special emphasis on logistics network design, sectorization and route design, using metaheuristics. Her work spans supply chain management, vehicle routing, waste collection optimization, and energy systems. She has participated as a researcher in FCT-funded projects, including the definition of logistics models for forest biomass supply and expansion of the national network of Justices of the Peace. Her research has evolved from fundamental facility location problems to applied logistics and sustainability projects. Her scientific production shows a strong focus on operational research with applications in logistics and sustainability. The publications demonstrate progression from theoretical optimization problems to practical applications in waste management, supply chain design, and renewable energy systems. Recent work increasingly addresses sustainability challenges in energy systems while maintaining strong methodological foundations in combinatorial optimization. Dr. Cortinhal has supervised 2 doctoral theses to completion, 2 master's dissertations in progress, 6 completed master's dissertations, and 4 master's final projects. Her students' work reflects her research interests, with topics spanning energy sustainability, logistics optimization, community detection in networks, and business applications of operations research. She has contributed to numerous national projects including development of methodologies for vehicle routing for collecting valuables (2016-2019) and planning household waste collection for Seixal municipality (2012-2015). Her external engagement includes media appearances where she discusses management education, economic development through education, and the role of business schools in preparing future executives.

Oktay GunlukView profile

Professor

• Discrete Optimization
• Integer Programming
• Mathematical Optimization
• +5 more

Oktay Gunluk is the Gary C. Butler Family Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology (Georgia Tech). Prior to joining Georgia Tech, he was a professor of practice in the School of Operations Research and Information Engineering at Cornell University and the manager of the Mathematical Optimization and Algorithms group at IBM Research. He also spent three years as a researcher in the Operations Research group at AT&T Labs, where he worked on various large-scale applied optimization projects. His educational background includes: Ph.D. in Operations Research (1995) from Columbia University M.Phil. in Operations Research (1993) from Columbia University M.S. in Industrial Engineering (1989) from Boğaziçi University B.S. in Industrial Engineering (1987) from Boğaziçi University Professor Gunluk's research focuses on theoretical and computational aspects of discrete optimization problems, primarily in integer programming. His seminal work centers on cutting planes for mixed-integer sets, and more recently he has developed integer programming approaches to classification and clustering problems in machine learning with considerations for fairness and interpretability. His work bridges theoretical optimization with practical applications in areas such as quantum computing, fair machine learning, and supply chain optimization. The interdisciplinary nature of his research is reflected in his publications spanning operations research journals, computer science conferences, and machine learning venues. His notable recognition includes: Gary C. Butler Family Professorship at Georgia Tech Professor Gunluk has advised several PhD students including Reka Agnes Kovacs (Oxford, 2023), Connor Lawless (Cornell, 2024), and Ishan Bansal (Cornell, 2024). His research has been supported by collaborations with industry partners including IBM Research where he led the Mathematical Optimization and Algorithms group. His work has addressed optimization challenges in telecommunications, quantum computing, and machine learning with practical implementations. At IBM Research, Gunluk managed the Mathematical Optimization and Algorithms group, leading a team focused on developing advanced optimization techniques for both theoretical advancement and practical application. His work has bridged the gap between academic research and industrial implementation, particularly in the areas of network design, quantum computing algorithms, and fair machine learning systems, demonstrating the real-world impact of his optimization expertise.

Aysun BozantaView profile

Assistant Professor

• Reinforcement Learning
• Natural Language Processing
• Data Science
• +4 more

Aysun Bozanta is an Assistant Professor at Bogazici University, specializing in data-driven research with applications in reinforcement learning, NLP, and social network analytics. She holds a Ph.D. in Management Information Systems from Bogazici University and completed postdoctoral research at Toronto Metropolitan University's Data Science Lab. Education Undergraduate: Işık University, Mathematical Engineering, MIS (DM) M.A.: Boğaziçi University, MIS Ph.D.: Boğaziçi University, MIS Postdoc: Toronto Metropolitan University - Data Science Lab Research Focus Her work bridges machine learning and real-world problems, with emphasis on: reinforcement learning for logistics (food delivery, courier routing), NLP (sentiment analysis, LLM evaluation), and social media analytics (misinformation, public policy responses). Epidemiologic modeling of COVID-19 interventions and recommender systems are additional key areas. Publication Trends Recent articles (2021-2025) reveal a strong focus on applied AI: reinforcement learning optimizes delivery systems; NLP research evaluates Turkish language models and classifies software requirements; COVID-19 studies model policy impacts; and social media analyses explore misinformation propagation. Transformer architectures and replication studies feature prominently. Awards & Recognition Best Paper Award at CASCON'21 for transformer-based requirements classification TUBITAK Post-Doctoral Research Fellowship (2019-Present) Projects & Collaboration Toronto Metropolitan University Project: "Intraday Trading Data Analytics with Financial News from Twitter" (2019-Present, TUBITAK-funded) Toronto Metropolitan University Project: "Getir-Courier Assignment by Reinforcement Learning" (2019-2020) Erasmus+ Project: "Online Vocational Education Platform" (2017-2019) Boğaziçi University Project: "Industry 4.0 Standardization Roadmap for Turkey" (2017-2019) Boğaziçi University Project: "Context-Aware Location Recommender System" (2016-2019) Labs & Teams Affiliated with Toronto Metropolitan University's Data Science Lab during postdoctoral work, focusing on reinforcement learning and NLP projects.

• Operations Research
• Quantitative Methods for Business and Economics
• Multiobjective Optimization
• +3 more

Concepcion Paralera Morales is an Associate Professor at the Universidad Pablo de Olavide, affiliated with the Department of Economics, Quantitative Methods and Economic History. Her research focuses on Quantitative Methods for Business and Economics within the "Quantitative Methods in Business and Economics" research group. PhD in Economics from Universidad Pablo de Olavide (2005) Supervised by Dr. Rafael Caballero Fernández and Dr. Flor María Guerrero Casas Her work primarily addresses multiobjective optimization problems in operational research, particularly location routing and waste management. She has applied metaheuristics like tabu search to real-world case studies in Andalusia, incorporating both economic and social criteria in decision-making processes. Key trends in her publications (2005-2007) include: multicriteria approaches for infrastructure location, integration of equity considerations in risk assessment, and combinatorial optimization techniques. Her research intersects operations research (90-XX) with applications in environmental policy and industrial logistics.

Milad GhasrikhouzaniView profile

Senior Lecturer

• Travel Behaviour
• Transport Modelling
• Behavioural Modelling
• +8 more

Milad Ghasrikhouzani serves as a Senior Lecturer at UNSW Canberra within the School of Engineering and Technology. His academic position focuses specifically on Travel Behaviour and Transport Modelling, where he contributes to both teaching and research activities in transportation systems. Dr. Ghasrikhouzani specializes in behavioral modeling, discrete choice analysis, and consumer preference research related to transport innovation adoption. His research examines how individuals and communities respond to emerging mobility solutions including autonomous vehicles (AVs), electric vehicles (EVs), and other new transport technologies. A distinctive aspect of his work investigates the role of social influence in facilitating behavioral shifts and accelerating adoption of innovations in the transport sector. His research framework considers both individual decision-making processes and broader social/systemic factors that shape travel behavior in evolving mobility landscapes. Analysis of Dr. Ghasrikhouzani's recent publication record (2022-2025) reveals consistent research output across multiple high-impact transportation journals. His work spans diverse subfields including sustainable transport consumption, demand-responsive transport systems, behavioral modeling of transportation choices, and the psychological drivers of mobility decisions. A notable trend shows increasing focus on integrated transport systems, particularly examining micromobility-public transport integration, trust in navigation technologies, and the impact of neighborhood characteristics on travel behavior. His research methodology frequently employs advanced statistical techniques including survival analysis, hybrid choice modeling, and discrete choice experiments. Dr. Ghasrikhouzani has secured research funding from significant government and industry partners including the National Housing Research Program through the Australian Housing and Urban Research Institute (AHURI), the ACT Government, the NSW Department of Premier and Cabinet, and the NSW Office of Environment and Heritage. These partnerships demonstrate the practical relevance and policy impact of his research in transportation planning and urban development contexts.

Casiano Alberto Manrique De Lara PeñateView profile

Professor

• Tourism Economics
• Maritime Transport Economics
• Applied Economics
• +7 more

Casiano Alberto Manrique De Lara Peñate is a Professor in the Department of Applied Economic Analysis at the Universidad de Las Palmas de Gran Canaria, School of Economics Business and Tourism. His academic work spans multiple research groups including GIR Economy Trade and Maritime Transport, Institute of Tourism and Sustainable Economic Development, and GIR Quantitative Finance and Computational Finance. His research interests focus on Tourism Economics , Maritime Transport Economics , and Applied Economic Modeling . Professor Manrique has developed innovative approaches to social accounting matrices, value-added accounting, and tax fraud detection using network analysis. His work bridges theoretical economics with practical applications in tourism, transportation, and business accounting. Professor Manrique's recent publications demonstrate consistent high-impact research in top-tier journals across tourism economics, operations research, and economic modeling. His work shows particular strength in applying quantitative methods to solve complex economic problems in tourism and maritime sectors. Among his notable contributions are: Methodologies for measuring input inefficiencies in the hotel industry Models for understanding fraud in consumption taxes using evolutionary game theory Multi-criteria frameworks for fleet deployment considering environmental impacts Innovative approaches to value-added accounting and business accounting matrices Professor Manrique maintains active research collaborations across Europe, particularly with institutions in Sweden and Germany, focusing on maritime transport optimization and tax compliance systems. His work combines rigorous economic theory with practical applications that address contemporary challenges in tourism management, sustainable transportation, and financial accountability.

Belma TuranView profile

Researcher

• City Logistics
• Vehicle routing problems
• Stochastic optimization
• +1 more

Belma Turan is a University Assistant (post doc) at the Institute of Transport Economics and Logistics, Vienna University of Economics and Business (WU), where she has conducted research since 2018. Her work centers on optimizing urban freight systems through advanced computational methods. Her academic credentials include: PhD in Logistics and Operations Management, University of Vienna (2011-2016) Master of Business Administration, University of Vienna (2009-2011) Bachelor of Business Administration, University of Graz (2005-2009) Dr. Turan specializes in City Logistics, Vehicle Routing Problems, Stochastic Optimization, and Metaheuristics. She develops algorithmic solutions for complex urban freight challenges, particularly focusing on stochastic elements in routing and sustainability transitions. Her methodology combines theoretical optimization frameworks with real-world case studies in Vienna's urban environment. Analysis of her 7 publications (2017-2024) reveals a consistent trajectory toward sustainable urban mobility. Early work established foundations in vehicle synchronization and routing algorithms, while recent research (2022-2024) directly addresses European sustainability initiatives, electric scooter fleet management, and cargo bike logistics. Her publications demonstrate increasing interdisciplinary engagement with environmental policy and practical implementation of optimization models. No major scientific awards are publicly documented for Dr. Turan. She has secured substantial research funding through 5 projects between 2018-2023: Sustainability Initiatives (2022-2023): Deputy project lead on European urban freight sustainability Electric Scooters in Vienna (2021-2022): Principal researcher on e-scooter fleet optimization INNS'PAKET (2020-2021): Co-lead on innovative parcel delivery systems MUKE (2020-2021): Critical success factors analysis in freight logistics Sustainable Distribution System (2018-2021): Vienna-focused two-tier delivery model Dr. Turan operates within WU's Institute of Transport Economics and Logistics research ecosystem, collaborating closely with Professors Vera Hemmelmayr and Thomas Wakolbinger. Her team specializes in computational logistics, with active projects spanning optimization algorithms, sustainable mobility transitions, and urban freight policy implementation.

Natalia ChernovaView profile

Associate Professor

• Queueing Theory
• Probability Theory
• Mathematical Statistics
• +3 more

Natalia Chernova is an Associate Professor at Novosibirsk State University, affiliated with the Department of Probability Theory and Mathematical Statistics since 2001. She earned her PhD in 1996 with a dissertation on "Ergodic theorems for complex stochastic service models" under S.G. Foss. Her academic career at NSU includes roles as assistant (1990–1997), senior lecturer (1997–2001), and associate professor since 2001. She has taught courses in probability theory and mathematical statistics across multiple faculties, including Mathematics, Economics, Natural Sciences, and Philosophy. Her research focuses on Ergodicity of queueing systems with complex structures Polling systems Non-fully accessible systems with multiple devices and call types Monotonicity properties and comparison theorems for queueing systems She has authored or co-authored numerous publications in journals such as Siberian Mathematical Journal , Problems of Information Transmission , and Operations Research Letters , alongside textbooks and educational materials. Her recent work (2012–2013) investigates stability regions of polling systems dependent on service time distributions and adaptive mechanisms. She has collaborated with scholars like Sergey Foss and Bara Kim, contributing to theoretical advancements in stochastic models and queueing networks.

Maximilian SchifferView profile

Associate Professor

• Operations Research
• Management Science
• Machine Learning
• +7 more

Prof. Dr. Maximilian Schiffer is an Associate Professor at the Professorship of Business Analytics & Intelligent Systems , TUM School of Management , Technical University of Munich. He holds a Ph.D. in Operations Research from RWTH Aachen University (2017) and has previously served as a visiting postdoctoral scholar at Stanford University and a postdoctoral scholar at RWTH Aachen. Education: Ph.D. in Operations Research, RWTH Aachen University (2017) Maximilian’s research focuses on developing operations research and prescriptive analytics methods to address societal mobility and transportation challenges, including electric vehicles , autonomous mobility-on-demand systems , and multi-modal transportation networks . His interdisciplinary work bridges robotics , computer science , and transport engineering . Recent publications highlight advancements in autonomous fleet control , electric vehicle charging infrastructure , and collusion detection in dynamic pricing . Scientific Awards: INFORMS TSL Dissertation Prize GOR Doctoral Dissertation Prize Best Paper Award, IEEE Conference on Intelligent Transportation Systems Maximilian is an associate member of the GERAD research group and serves on the editorial board of OR Spectrum and the TSL Dissertation Prize committee . His lab, the Professorship of Business Analytics & Intelligent Systems , trains students in machine learning, optimization, and future mobility systems.

Pia AmmannView profile

Researcher

• Mathematical Modeling
• Optimization
• Transportation and Logistics
• +2 more

Pia Ammann, M.Sc., is a research associate and doctoral candidate at the Chair of Operations Management at Technische Universität München (TUM) since 2019. She is associated with the RTG 'Advanced Optimization in a Networked Economy' (AdONE) and holds the GOR Master’s Thesis Prize 2020 and the Heureka Student Award 2019. B.Sc. and M.Sc. in Management and Technology at TUM (2012–2019) Study abroad at National Taiwan University (2016) Scholar of the Academic Training Program (Dieter Schwarz Stiftung) since 2021 Her research focuses on mathematical modeling and optimization in transportation and logistics, particularly addressing vehicle routing and scheduling challenges. She has explored synchronization constraints, automated truck platooning, and real-world multi-attribute problems using advanced heuristics like Adaptive Large Neighborhood Search. Her publications span journals like Transportation Research Part B: Methodological, arXiv working papers, and conference contributions at events such as Operations Research (2023), VeRoLog (2022), and the International Conference on Operations Research (2021). She is currently on parental leave until March 2025. GOR Master’s Thesis Prize (2020) Heureka Student Award (2019)

Issmaïl El HallaouiView profile

Professor

• Operations Research
• Optimization
• Mathematical Modeling
• +5 more

Issmaïl El Hallaoui is a Full Professor in the Department of Mathematical and Industrial Engineering at Polytechnique Montréal. His research focuses on operations research, optimization, and mathematical modeling, with applications in transportation, vehicle routing, and software development. He is affiliated with the Institute for Data Valorization (IVADO) and the Research Group in Decision Analysis (GERAD). Operations Research and Management Science Combinatorial Optimization Online Optimization Vehicle Scheduling Transportation Logistics Software Development With over 116 publications, his work spans 2025 INFORMS Journal on Applied Analytics, 2024 Transportation Research Part E, and 2023 European Journal of Operational Research. His recent projects include supply chain optimization for OCP, real-time dial-a-ride problem solving, and energy system modeling via game theory. Dr. El Hallaoui has supervised 11 PhD and 3 Master's students, including Bani, A., Er Raqabi, E. M., and Tahir, A. His teaching portfolio includes courses on Integer Programming (MTH6404) and Real-time Optimization (MTH6601).

Ollivier HyrienView profile

Professor

• Statistical methods for bioassays
• Machine learning
• Dynamic modeling
• +7 more

Ollivier Hyrien is an Affiliate Professor of Biostatistics at Fred Hutchinson Cancer Center, where he also holds professorships in the Biostatistics, Bioinformatics and Epidemiology Program within the Vaccine and Infectious Disease Division, and the Herbold Computational Biology Program within the Public Health Sciences Division. He is additionally a Member of the Translational Data Science Integrated Research Center (TDS IRC) at Fred Hutch. Dr. Hyrien earned his PhD in Statistics from the University of Rennes 1 in Rennes, France in 2001. His academic journey has led him to become a prominent figure in biostatistics with a focus on applying advanced statistical methods to complex biological problems. Dr. Hyrien is a biostatistician who applies advanced technologies such as machine learning and dynamic modeling to address problems in laboratory experiments and clinical studies. His research focuses on statistical methods for flow cytometry, single-cell sequencing and other bioassays. His lab specializes in developing and applying statistical methods, computational tools, and mathematical models to study the immune system and other complex biological systems, such as the microbiome, the hematopoietic system, and the central nervous system, using high-dimensional, high-throughput data. A core focus of his current research is supporting the development of vaccines and passive immunization strategies against diseases caused by pathogens such as the Human Immunodeficiency Virus (HIV), malaria, SARS-CoV-2, herpes simplex virus (HSV), as well as treatments against cancer. One exciting area of Dr. Hyrien's research is the study of the evolution of the B-cell repertoire. Understanding this process involves solving how B cells, through somatic hypermutation (SHM) and clonal selection, adapt to recognize foreign antigens and neutralize pathogens. This work involves using machine learning and statistical tools as well as stochastic processes (e.g., branching processes) to quantify and predict how SHM accumulate over time in the immunoglobulin genes and how these mutations impact the structure and binding properties of the receptors and antibodies produced by B cells. Dr. Hyrien's recent publications demonstrate a strong focus on HIV vaccine development, statistical methods for bioassays, and immune response modeling. His work spans multiple disciplines including biostatistics, immunology, virology, and computational biology, with particular emphasis on HIV broadly neutralizing antibodies, vaccine efficacy trials, and statistical modeling of biological processes. His research often involves large collaborative efforts across multiple institutions, reflecting the interdisciplinary nature of modern biomedical research. The Hyrien Lab is highly collaborative, working closely with numerous research groups across Fred Hutch and other institutions. Dr. Hyrien's work frequently involves statistical analysis for major vaccine trials, including those for HIV and COVID-19, where his expertise in biostatistics and mathematical modeling contributes significantly to understanding immune responses and vaccine efficacy.

Enrique Ruiz ZunigaView profile

Associate Professor

• Production Engineering
• Logistics Systems
• Robotics
• +7 more

Enrique Ruiz Zuniga serves as Associate Professor in Production Engineering at the University of Skövde's School of Engineering Science in Sweden, while simultaneously holding a JSPS research fellowship at Kyoto University's Systems Design Laboratory and collaborating with Japan Manned Space Systems Corporation (JAMSS). His career bridges academic research and industrial applications across Europe and Asia, focusing on optimizing complex manufacturing and logistics systems through advanced computational methods. University of Skövde, School of Engineering Science JSPS Research Fellow, Kyoto University Japan Manned Space Systems Corporation (JAMSS) collaborator Dr. Ruiz Zuniga's educational background includes a B.Eng. in industrial engineering from the University of Malaga, Spain, a BSc in automation engineering from the University of Skövde, Sweden, followed by an MSc in industrial informatics and a 2020 PhD in informatics from the University of Skövde, completed in partnership with Xylem Water Solutions Manufacturing. His doctoral research focused on facility layout design using simulation-based optimization methodologies. His primary research interests encompass the design, verification, and improvement of logistics, robotics, and complex production systems, with methodological expertise in Lean Production, Discrete-Event Simulation, System Dynamics, Simulation-Based Optimization, and the Functional Resonance Analysis Method. Dr. Ruiz Zuniga's work demonstrates a consistent focus on international collaboration and practical implementation of theoretical models in real-world industrial settings across healthcare and manufacturing sectors. Analysis of his publication record reveals an evolution from foundational work in facility layout design toward more recent explorations of AI integration, human-centered design, and resilient production systems. His research shows increasing sophistication in combining simulation approaches with functional analysis methods, with a growing emphasis on human factors and system resilience in complex production environments. REFUSE (2023-2026): Resource efficient use of reconfigurable machining systems Dynamic SALSA (2023-2024): AI scheduling for assembly and logistics systems Envisioned world problems (2021-2023): Functional approaches for system design Emergency Department Modeling (2012-2016): Healthcare production systems Dr. Ruiz Zuniga has coordinated international engineering programs in Industrial Engineering, Product Design Engineering, and Mechanical Engineering (all 60 credits), while teaching courses including Introduction to Lean Philosophy, Methods Engineering, Mechatronics/Electronics, and Production and Logistic Simulation. His work demonstrates a strong commitment to bridging theoretical research with practical industrial applications in production engineering through international collaboration and methodological innovation.

Zuzana ČičkováView profile

Associate Professor

• Operations Research
• Game Theory
• Econometrics
• +2 more

Zuzana Čičková is an Associate Professor at the Department of Operations Research and Econometrics, Faculty of Economic Informatics, University of Economics in Bratislava. Her work bridges computational intelligence, game theory, and economic modeling, with a focus on spatial competition, logistics, and market dynamics. Academic Rank: Associate Professor Department: Operations Research and Econometrics University: University of Economics in Bratislava Her research spans game theory, vehicle routing, and econometric modeling. Recent projects include multi-criteria game theory applications in spatial allocation (2022), analysis of Arctic shipping routes (2022), and optimization of recycling networks under VEGA grants. She has contributed to algorithm design (SOMA/DE) and market concentration indicators like the Herfindahl-Hirschman Index. Her publications reflect expertise in computational intelligence for economic problems, including vehicle routing with time windows , spatial competition models , and data-driven decision support systems . While no explicit awards are listed, her leadership in VEGA projects (2017-2025) and international collaborations with institutions like Bifröst University and Óbuda University underscores her academic impact. 31 Web of Science/Scopus publications with 98 citations 8 invited lectures at international/national conferences PhD in Econometrics and Operations Research (2005) Teaching since 2001, advising 38 master’s theses She has undertaken international mobilities in Iceland (2014, 2022), Germany (2007), Czech Republic (2022), and Spain (2022), focusing on research and pedagogical innovation. Her current projects include VEGA 1/0115/23 on cooperative game theory in international relations (2023-2025).

• Combinatorial Optimisation
• Vehicle Routing Problems
• Exact Algorithms
• +2 more

Dr. Thu Dang is a Lecturer in Management Science at Lancaster University, specializing in Combinatorial Optimization Problems. She is affiliated with the Department of Management Science and participates in the Data Science Institute, Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRA), and the STOR-i Centre for Doctoral Training. Her research focuses on both exact methods for solving problems to proven optimality and heuristic methods for real-life problems, particularly Vehicle Routing Problems. She completed her PhD with the STOR-i CDT, working on exact algorithms and heuristic methods for large-scale and complex Vehicle Routing Problems under the supervision of Prof. Adam Letchford and Dr. Burak Boyaci at Lancaster University in collaboration with Routeware, Inc. Dr. Dang's publication record shows consistent contributions to combinatorial optimization, with recent work spanning theoretical aspects of flowshop scheduling to practical applications in school bus routing and vehicle routing on road networks. Her research increasingly incorporates hybrid approaches combining traditional optimization techniques with reinforcement learning. She has received professional recognition through the YoungWomen4OR Prize and the Kingman Prize. Dr. Dang supervises PhD students Sebastian Caceres Gelvez (researching Optimization) and Lauren Durrell (affiliated with STOR-i Centre for Doctoral Training). She actively participates in academic conferences including the Operational Research Society's annual conference, the International Symposium on Combinatorial Optimization, and the Conference on Optimization, Modeling, Simulation and Analytics (COMOSA 2025). Her research group involvement includes the LIRA Centre's Fundamentals Optimisation team and the STOR-i Centre for Doctoral Training, reflecting her commitment to both theoretical and applied optimization research.