KEYNOTE SPEAKERS<\/h1><\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Tomi Medved<\/h2>\n
Laboratory of Energy Strategies (LEST), Faculty of Electrical Engineering, University of Ljubljana<\/p>\n<\/div>
![](\"https:\/\/sst-conference.org\/wp-content\/uploads\/2026\/10\/Tomi-Medved.jpg\" "\\"Tomi-Medved\\"")
<\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div> Title: <\/strong>Where is the flexibility everybody talks about?<\/h2>\n<\/div><\/div><\/div><\/div>Abstract:<\/strong>
\nThe energy transition is filling low-voltage networks with heat pumps, electric vehicles, rooftop PV and home batteries. Together, these devices hold a large amount of flexibility that could support both distribution and transmission system operation. Yet very little of it is used today. The technology to control these devices largely exists. What is missing are the building blocks that let small, scattered resources take part in the power system reliably and at scale.<\/p>\nThis keynote looks at those missing blocks from different angles. The first is visibility: system operators and market parties need to know which flexible devices exist, where they are connected and what they can do. That calls for interoperable device registries and open, data-driven infrastructure. The second, and often decisive, is value: households and small businesses will only take part if the remuneration is clear and fair. That raises the question of how local flexibility markets, energy services and wholesale and balancing markets can share revenues along the value chain.<\/p>\n
The talk draws on two Horizon Europe projects. STREAM develops an ecosystem of service and market innovations that link consumer flexibility capacity to system needs, and tests it at four pilot sites. OPENTUNITY works to lower interoperability barriers between prosumers, grid operators and market actors through standards-based tools and a federated data space, with demonstrations in Greece, Slovenia, Spain and Switzerland. The central message is that unlocking low-voltage flexibility is no longer mainly a technical problem. It depends on putting the right data, coordination and market building blocks in place so that the flexibility already in our homes reaches the system.<\/p>\n<\/div>
<\/div><\/div><\/div>Biography:<\/strong>
\nTomi Medved is Head of the Laboratory of Energy Strategies (LEST) at the Faculty of Electrical Engineering, University of Ljubljana, a position he has held since 2022. He graduated from the same faculty in 2012 and then worked at LEST as a researcher while completing his PhD. From 2013 to 2017 he also worked in risk management and market analytics at the electricity supplier Elektro Energija. Between 2015 and 2016 he was a visiting researcher at the UCLA Smart Grid Energy Research Center, where he worked on machine learning for agent-based modelling of demand response.<\/p>\nHis research covers smart grids, renewable integration, demand response, electricity market modelling and energy policy design. He has worked on many European research projects, including APRAISE, INCREASE, STORY, CONSEED, CROSSBOW and X-FLEX. He is currently deputy coordinator of the Horizon Europe project STREAM and takes part in several ongoing Horizon Europe projects, including OPENTUNITY.<\/p>\n<\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Francisco Mart\u00ednez \u00c1lvarez<\/h2>\n
Data Science & Big Data Lab, Pablo de Olavide University<\/p>\n<\/div>
![](\"https:\/\/sst-conference.org\/wp-content\/uploads\/2026\/09\/fma.jpg\" "\\"fma\\"")
<\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div> Title: <\/strong>Quantum Machine Learning for Electrical Engineering and Electronics:
\nFoundations, Opportunities and Emerging Applications<\/h2>\n<\/div><\/div><\/div><\/div>Abstract:<\/strong>
\nQuantum computing is emerging as a new computational paradigm with the potential to address problems that remain challenging for classical approaches. Among its most promising areas, Quantum Machine Learning (QML) combines quantum computing with machine learning to explore new models for optimization, classification, pattern recognition, and high-dimensional data analysis. This keynote introduces the basic principles of quantum computing and QML and reviews the current technological landscape. The talk also addresses the limitations of current Noisy Intermediate-Scale Quantum devices and the role of hybrid quantum-classical approaches. The aim is to provide a realistic view of where QML stands today, which applications are most promising, and what opportunities it may create for future electrical and electronic systems.<\/p>\n<\/div><\/div><\/div><\/div>Biography:<\/strong>
\nFrancisco Mart\u00ednez \u00c1lvarez is a Full Professor in the Computer Science Division at Pablo de Olavide University. He received his Degree in Telecommunication Engineering in 2005, his M.S. Degree in Computer Science in 2007, and his Ph.D. in Computer Science in 2010. His main research areas include time series, quantum machine learning, explainable artificial intelligence, and big data analytics, with over 200 published papers. He has supervised nine doctoral theses and led several national and international research projects. In 2015, together with Prof. Alicia Troncoso, he founded the Data Science & Big Data Lab. He has also served as principal investigator in numerous knowledge transfer projects in collaboration with more than 10 companies. Since 2013, he has held several management positions at Pablo de Olavide University. According to Stanford University\u2019s analysis, he has been ranked among the world\u2019s top 2% scientists for single-year impact every year since 2022, and for career-long impact from 2024.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3282","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages\/3282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/comments?post=3282"}],"version-history":[{"count":11,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages\/3282\/revisions"}],"predecessor-version":[{"id":3408,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages\/3282\/revisions\/3408"}],"wp:attachment":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/media?parent=3282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Tomi Medved<\/h2>\n
Laboratory of Energy Strategies (LEST), Faculty of Electrical Engineering, University of Ljubljana<\/p>\n<\/div>
<\/span><\/div><\/div> Title: <\/strong>Where is the flexibility everybody talks about?<\/h2>\n<\/div><\/div><\/div><\/div>Abstract:<\/strong>
\nThe energy transition is filling low-voltage networks with heat pumps, electric vehicles, rooftop PV and home batteries. Together, these devices hold a large amount of flexibility that could support both distribution and transmission system operation. Yet very little of it is used today. The technology to control these devices largely exists. What is missing are the building blocks that let small, scattered resources take part in the power system reliably and at scale.<\/p>\nThis keynote looks at those missing blocks from different angles. The first is visibility: system operators and market parties need to know which flexible devices exist, where they are connected and what they can do. That calls for interoperable device registries and open, data-driven infrastructure. The second, and often decisive, is value: households and small businesses will only take part if the remuneration is clear and fair. That raises the question of how local flexibility markets, energy services and wholesale and balancing markets can share revenues along the value chain.<\/p>\n
The talk draws on two Horizon Europe projects. STREAM develops an ecosystem of service and market innovations that link consumer flexibility capacity to system needs, and tests it at four pilot sites. OPENTUNITY works to lower interoperability barriers between prosumers, grid operators and market actors through standards-based tools and a federated data space, with demonstrations in Greece, Slovenia, Spain and Switzerland. The central message is that unlocking low-voltage flexibility is no longer mainly a technical problem. It depends on putting the right data, coordination and market building blocks in place so that the flexibility already in our homes reaches the system.<\/p>\n<\/div>
<\/div><\/div><\/div>Biography:<\/strong>
\nTomi Medved is Head of the Laboratory of Energy Strategies (LEST) at the Faculty of Electrical Engineering, University of Ljubljana, a position he has held since 2022. He graduated from the same faculty in 2012 and then worked at LEST as a researcher while completing his PhD. From 2013 to 2017 he also worked in risk management and market analytics at the electricity supplier Elektro Energija. Between 2015 and 2016 he was a visiting researcher at the UCLA Smart Grid Energy Research Center, where he worked on machine learning for agent-based modelling of demand response.<\/p>\nHis research covers smart grids, renewable integration, demand response, electricity market modelling and energy policy design. He has worked on many European research projects, including APRAISE, INCREASE, STORY, CONSEED, CROSSBOW and X-FLEX. He is currently deputy coordinator of the Horizon Europe project STREAM and takes part in several ongoing Horizon Europe projects, including OPENTUNITY.<\/p>\n<\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Francisco Mart\u00ednez \u00c1lvarez<\/h2>\n
Data Science & Big Data Lab, Pablo de Olavide University<\/p>\n<\/div>
<\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div> Title: <\/strong>Quantum Machine Learning for Electrical Engineering and Electronics:
\nFoundations, Opportunities and Emerging Applications<\/h2>\n<\/div><\/div><\/div><\/div>Abstract:<\/strong>
\nQuantum computing is emerging as a new computational paradigm with the potential to address problems that remain challenging for classical approaches. Among its most promising areas, Quantum Machine Learning (QML) combines quantum computing with machine learning to explore new models for optimization, classification, pattern recognition, and high-dimensional data analysis. This keynote introduces the basic principles of quantum computing and QML and reviews the current technological landscape. The talk also addresses the limitations of current Noisy Intermediate-Scale Quantum devices and the role of hybrid quantum-classical approaches. The aim is to provide a realistic view of where QML stands today, which applications are most promising, and what opportunities it may create for future electrical and electronic systems.<\/p>\n<\/div><\/div><\/div><\/div>Biography:<\/strong>
\nFrancisco Mart\u00ednez \u00c1lvarez is a Full Professor in the Computer Science Division at Pablo de Olavide University. He received his Degree in Telecommunication Engineering in 2005, his M.S. Degree in Computer Science in 2007, and his Ph.D. in Computer Science in 2010. His main research areas include time series, quantum machine learning, explainable artificial intelligence, and big data analytics, with over 200 published papers. He has supervised nine doctoral theses and led several national and international research projects. In 2015, together with Prof. Alicia Troncoso, he founded the Data Science & Big Data Lab. He has also served as principal investigator in numerous knowledge transfer projects in collaboration with more than 10 companies. Since 2013, he has held several management positions at Pablo de Olavide University. According to Stanford University\u2019s analysis, he has been ranked among the world\u2019s top 2% scientists for single-year impact every year since 2022, and for career-long impact from 2024.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3282","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages\/3282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/comments?post=3282"}],"version-history":[{"count":11,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages\/3282\/revisions"}],"predecessor-version":[{"id":3408,"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/pages\/3282\/revisions\/3408"}],"wp:attachment":[{"href":"https:\/\/sst-conference.org\/index.php\/wp-json\/wp\/v2\/media?parent=3282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Abstract:<\/strong> This keynote looks at those missing blocks from different angles. The first is visibility: system operators and market parties need to know which flexible devices exist, where they are connected and what they can do. That calls for interoperable device registries and open, data-driven infrastructure. The second, and often decisive, is value: households and small businesses will only take part if the remuneration is clear and fair. That raises the question of how local flexibility markets, energy services and wholesale and balancing markets can share revenues along the value chain.<\/p>\n The talk draws on two Horizon Europe projects. STREAM develops an ecosystem of service and market innovations that link consumer flexibility capacity to system needs, and tests it at four pilot sites. OPENTUNITY works to lower interoperability barriers between prosumers, grid operators and market actors through standards-based tools and a federated data space, with demonstrations in Greece, Slovenia, Spain and Switzerland. The central message is that unlocking low-voltage flexibility is no longer mainly a technical problem. It depends on putting the right data, coordination and market building blocks in place so that the flexibility already in our homes reaches the system.<\/p>\n<\/div> Biography:<\/strong> His research covers smart grids, renewable integration, demand response, electricity market modelling and energy policy design. He has worked on many European research projects, including APRAISE, INCREASE, STORY, CONSEED, CROSSBOW and X-FLEX. He is currently deputy coordinator of the Horizon Europe project STREAM and takes part in several ongoing Horizon Europe projects, including OPENTUNITY.<\/p>\n<\/div> Data Science & Big Data Lab, Pablo de Olavide University<\/p>\n<\/div> Abstract:<\/strong> Biography:<\/strong>
\nThe energy transition is filling low-voltage networks with heat pumps, electric vehicles, rooftop PV and home batteries. Together, these devices hold a large amount of flexibility that could support both distribution and transmission system operation. Yet very little of it is used today. The technology to control these devices largely exists. What is missing are the building blocks that let small, scattered resources take part in the power system reliably and at scale.<\/p>\n
\nTomi Medved is Head of the Laboratory of Energy Strategies (LEST) at the Faculty of Electrical Engineering, University of Ljubljana, a position he has held since 2022. He graduated from the same faculty in 2012 and then worked at LEST as a researcher while completing his PhD. From 2013 to 2017 he also worked in risk management and market analytics at the electricity supplier Elektro Energija. Between 2015 and 2016 he was a visiting researcher at the UCLA Smart Grid Energy Research Center, where he worked on machine learning for agent-based modelling of demand response.<\/p>\nFrancisco Mart\u00ednez \u00c1lvarez<\/h2>\n
<\/span><\/div><\/div> Title: <\/strong>Quantum Machine Learning for Electrical Engineering and Electronics:
\nFoundations, Opportunities and Emerging Applications<\/h2>\n<\/div>
\nQuantum computing is emerging as a new computational paradigm with the potential to address problems that remain challenging for classical approaches. Among its most promising areas, Quantum Machine Learning (QML) combines quantum computing with machine learning to explore new models for optimization, classification, pattern recognition, and high-dimensional data analysis. This keynote introduces the basic principles of quantum computing and QML and reviews the current technological landscape. The talk also addresses the limitations of current Noisy Intermediate-Scale Quantum devices and the role of hybrid quantum-classical approaches. The aim is to provide a realistic view of where QML stands today, which applications are most promising, and what opportunities it may create for future electrical and electronic systems.<\/p>\n<\/div>
\nFrancisco Mart\u00ednez \u00c1lvarez is a Full Professor in the Computer Science Division at Pablo de Olavide University. He received his Degree in Telecommunication Engineering in 2005, his M.S. Degree in Computer Science in 2007, and his Ph.D. in Computer Science in 2010. His main research areas include time series, quantum machine learning, explainable artificial intelligence, and big data analytics, with over 200 published papers. He has supervised nine doctoral theses and led several national and international research projects. In 2015, together with Prof. Alicia Troncoso, he founded the Data Science & Big Data Lab. He has also served as principal investigator in numerous knowledge transfer projects in collaboration with more than 10 companies. Since 2013, he has held several management positions at Pablo de Olavide University. According to Stanford University\u2019s analysis, he has been ranked among the world\u2019s top 2% scientists for single-year impact every year since 2022, and for career-long impact from 2024.<\/p>\n<\/div>